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MARKETING RESEARCH AN APPLIED APPROACH

FIFTH EDITION

NARESH K. MALHOTRA DANIEL NUNAN • DAVID F. BIRKS

Marketing Research An Applied Approach

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Marketing Research An Applied Approach Fifth Edition

Naresh K. Malhotra Daniel Nunan David F. Birks

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Pearson Education Limited Edinburgh Gate Harlow CM20 2JE United Kingdom Tel: +44 (0)1279 623623 Web: www.pearson.com/uk Original 6th edition entitled Marketing Research: An Applied Orientation published by Prentice Hall Inc., a Pearson Education company Copyright Prentice Hall Inc. First edition published 2000 (print) Second edition published 2003 (print) Third edition published 2007 (print) Fourth edition published 2012 (print) Fifth edition published 2017 (print and electronic) © Pearson Education Limited 2000, 2003, 2007, 2012 (print) © Pearson Education Limited 2017 (print and electronic) The rights of Naresh K. Malhotra, Daniel Nunan, David F. Birks and Peter Wills to be identified as authors of this work has been asserted by them in accordance with the Copyright, Designs and Patents Act 1988. The print publication is protected by copyright. Prior to any prohibited reproduction, storage in a retrieval system, distribution or transmission in any form or by any means, electronic, mechanical, recording or otherwise, permission should be obtained from the publisher or, where applicable, a licence permitting restricted copying in the United Kingdom should be obtained from the Copyright Licensing Agency Ltd, Barnard’s Inn, 86 Fetter Lane, London EC4A 1EN. The ePublication is protected by copyright and must not be copied, reproduced, transferred, distributed, leased, licensed or publicly performed or used in any way except as specifically permitted in writing by the publishers, as allowed under the terms and conditions under which it was purchased, or as strictly permitted by applicable copyright law. Any unauthorised distribution or use of this text may be a direct infringement of the authors’ and the publisher’s rights and those responsible may be liable in law accordingly. All trademarks used herein are the property of their respective owners. The use of any trademark in this text does not vest in the author or publisher any trademark ownership rights in such trademarks, nor does the use of such trademarks imply any affiliation with or endorsement of this book by such owners. Pearson Education is not responsible for the content of third-party internet sites. ISBN:

978-1-292-10312-9 (print) 978-1-292-10315-0 (PDF) 978-1-292-21132-9 (ePub)

British Library Cataloguing-in-Publication Data A catalogue record for the print edition is available from the British Library Library of Congress Cataloging-in-Publication Data Names: Malhotra, Naresh K., author. | Nunan, Daniel, author. | Birks, David F., author. Title: Marketing research : an applied approach / Naresh K. Malhotra, Daniel Nunan, David F. Birks. Description: Fifth Edition. | New York : Pearson, [2017] | Revised edition of Marketing research, 2012. | Includes bibliographical references and index. Identifiers: LCCN 2017007654 | ISBN 9781292103129 Subjects: LCSH: Marketing research. | Marketing research—Methodology Classification: LCC HF5415.2 .M29 2017 | DDC 658.8/3—dc23 LC record available at https://lccn.loc.gov/2017007654 10 9 8 7 6 5 4 3 2 1 19 18 17 16 15 Print edition typeset in 10/12 pt Times LT Pro by Aptara Printed in Slovakia by Neografia NOTE THAT ANY PAGE CROSS REFERENCES REFER TO THE PRINT EDITION

Brief contents

Prefacexiii Publisher’s acknowledgements xv About the authors xvii

1. Introduction to marketing research

2. Defining the marketing research problem and developing a research approach

3. Research design

4. Secondary data collection and analysis

5. Internal secondary data and analytics

121

6. Qualitative research: its nature and approaches

147

7. Qualitative research: focus group discussions

179

8. Qualitative research: in-depth interviewing and projective techniques207 9. Qualitative research: data analysis

233

10. Survey and quantitative observation techniques

267

11. Causal research design: experimentation

302

12. Measurement and scaling: fundamentals, comparative and non-comparative scaling

333

13. Questionnaire design

371

14. Sampling: design and procedures

409

15. Sampling: determining sample size

442

16. Survey fieldwork

471

17. Social media research

491

18. Mobile research

513

19. Data integrity

528

20. Frequency distribution, cross-tabulation and hypothesis testing

556

21. Analysis of variance and covariance

601

Marketing Research

22. Correlation and regression

632

23. Discriminant and logit analysis

673

24. Factor analysis

707

25. Cluster analysis

735

26. Multidimensional scaling and conjoint analysis

762

27. Structural equation modelling and path analysis

795

28. Communicating research findings

831

29. Business-to-business (b2b) marketing research

854

30. Research ethics

881

Glossary908 Subject index

926

Name index

952

Company index

954

Contents

Prefacexiii Publisher’s acknowledgements xv About the authors xvii

1 Introduction to marketing research

Objectives2 Overview2 What does ‘marketing research’ mean? 3 A brief history of marketing research 6 6 Definition of marketing research The marketing research process 9 A classification of marketing research 12 The global marketing research industry 15 Justifying the investment in marketing research 19 The future – addressing the marketing research skills gap 22 Summary25 Questions26 Exercises26 Notes27

2 Defining the marketing researchproblem and developing aresearch approach

Objectives30 Overview30 Importance of defining the problem 31 32 The marketing research brief Components of the marketing research brief 33 The marketing research proposal 36 The process of defining the problem and developing a research approach 39 42 Environmental context of the problem Discussions with decision makers 42 Interviews with industry experts 44 Initial secondary data analyses 45 Marketing decision problem and marketing researchproblem46 Defining the marketing research problem 49 Components of the research approach 50 Objective/theoretical framework 51

Analytical model 52 Research questions 53 Hypothesis54 Summary54 Questions55 Exercises56 Notes57

3 Research design

Objectives60 Overview60 Research design definition 61 Research design from the decision makers’ perspective62 Research design from the participants’ perspective 63 Research design classification 69 Descriptive research 73 Causal research 79 Relationships between exploratory, descriptive 80 andcausal research Potential sources of error in research designs 82 Summary85 Questions86 Exercises86 Notes87

4 Secondary data collection and analysis

Objectives91 Overview91 Defining primary data, secondary data and marketing intelligence 92 Advantages and uses of secondary data 94 Disadvantages of secondary data 96 Criteria for evaluating secondary data 96 Classification of secondary data 99 Published external secondary sources 100 Databases104 Classification of online databases 104 Syndicated sources of secondary data 106 Syndicated data from households 109

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Syndicated data from institutions 115 Summary117 Questions118 Exercises119 Notes119

5 Internal secondary data and analytics121 Objectives122 Overview122 Internal secondary data 125 Geodemographic data analyses 128 Customer relationship management 132 Big data 134 Web analytics 136 Linking different types of data 139 Summary144 Questions144 Exercises145 Notes146

6 Qualitative research: its nature and approaches

147

Objectives148 Overview148 Primary data: qualitative versus quantitative research 150 152 Rationale for using qualitative research Philosophy and qualitative research 155 Ethnographic research 162 Grounded theory 168 Action research 171 Summary174 Questions176 Exercises176 Notes177

7 Qualitative research: focus group discussions

179

Objectives180 Overview180 Classifying qualitative research techniques 182 Focus group discussion 183 Planning and conducting focus groups 188 The moderator 193 Other variations of focus groups 194 Other types of qualitative group discussions 195 Misconceptions about focus groups 196 Online focus groups 198 Advantages of online focus groups 200 Disadvantages of online focus groups 201 Summary202

Questions203 Exercises204 Notes205

8 Qualitative research: in-depth interviewing and projective techniques207 Objectives208 Overview208 In-depth interviews 209 Projective techniques 221 Comparison between qualitative techniques 227 Summary228 Questions229 Exercises230 Notes230

9 Qualitative research: data analysis 233 Objectives234 Overview234 The qualitative researcher 235 The process of qualitative data analysis 239 251 Grounded theory Content analysis 254 Semiotics256 Qualitative data analysis software 259 Summary262 Questions263 Exercises264 Notes264

10 Survey and quantitative observation techniques

267

Objectives268 Overview268 269 Survey methods Online surveys 271 Telephone surveys 275 Face-to-face surveys 276 A comparative evaluation of survey methods 279 Other survey methods 288 289 Mixed-mode surveys Observation techniques 289 Observation techniques classified by mode ofadministration292 A comparative evaluation of the observationtechniques295 Advantages and disadvantages ofobservationtechniques296 Summary297 Questions297 Exercises298 Notes299

Contents

11 Causal research design: experimentation302 Objectives303 Overview303 Concept of causality 304 Conditions for causality 305 Definitions and concepts 308 Definition of symbols 310 Validity in experimentation 310 Extraneous variables 311 Controlling extraneous variables 313 A classification of experimental designs 315 Pre-experimental designs 316 True experimental designs 317 Quasi-experimental designs 318 Statistical designs 320 Laboratory versus field experiments 323 Experimental versus non-experimental designs 325 Application: test marketing 326 Summary328 Questions329 Exercises330 Notes330

12 Measurement and scaling: fundamentals, comparative and non-comparative scaling

333

Objectives334 Overview334 335 Measurement and scaling Scale characteristics and levels of measurement 336 Primary scales of measurement 337 A comparison of scaling techniques 342 Comparative scaling techniques 343 347 Non-comparative scaling techniques Itemised rating scales 349 Itemised rating scale decisions 352 Multi-item scales 356 Scale evaluation 358 Choosing a scaling technique 363 Mathematically derived scales 364 Summary364 Questions365 Exercises366 Notes367

13 Questionnaire design

371

Objectives372 Overview372 Questionnaire definition 374 Questionnaire design process 375 Specify the information needed 378 Specify the type of interviewing method 379

Determine the content of individual questions 380 Overcoming the participant’s inability and unwillingness to answer 381 Choose question structure 385 Choose question wording 389 Arrange the questions in proper order 394 Identify the form and layout 396 Reproduce the questionnaire 397 Eliminate problems by pilot-testing 398 Summarising the questionnaire design process400 Designing surveys across cultures and countries 402 Summary403 Questions404 Exercises405 Notes405

14 Sampling: design and procedures

409

Objectives410 Overview410 Sample or census 412 The sampling design process 414 A classification of sampling techniques 419 Non-probability sampling techniques 420 425 Probability sampling techniques Choosing non-probability versus probability sampling 433 Summary of sampling techniques 434 Issues in sampling across countries and cultures 436 Summary437 Questions438 Exercises439 Notes439

15 Sampling: determining sample size

442

Objectives443 Overview443 Definitions and symbols 445 The sampling distribution 446 Statistical approaches to determining sample size 447 The confidence interval approach 448 Multiple characteristics and parameters 454 Other probability sampling techniques 454 Adjusting the statistically determined sample size 455 Calculation of response rates 456 Non-response issues in sampling 457 Summary464 Questions464 Exercises465 Appendix: The normal distribution 466 Notes468

Marketing Research

16 Survey fieldwork

471

Objectives472 Overview472 The nature of survey fieldwork 474 Survey fieldwork and the data-collection process 475 Selecting survey fieldworkers 475 Training survey fieldworkers 476 Recording the answers 479 Supervising survey fieldworkers 481 Evaluating survey fieldworkers 482 Fieldwork and online research 483 Fieldwork across countries and cultures 485 Summary487 Questions487 Exercises488 Notes489

17 Social media research

491

Objectives492 Overview492 492 What do we mean by ‘social media’? The emergence of social media research 494 Approaches to social media research 495 Accessing social media data 497 Social media research methods 499 508 Research with image and video data Limitations of social media research 509 Summary510 Questions510 Exercises511 Notes511

18 Mobile research

513

Objectives514 Overview514 What is a mobile device? 514 Approaches to mobile research 516 Guidelines specific to mobile marketing research 518 Key challenges in mobile research 522 Summary525 Questions526 Exercises526 Notes526

19 Data integrity

528

Objectives529 Overview529 The data integrity process 530 Checking the questionnaire 531 Editing532 Coding533 Transcribing539

Cleaning the data 541 Statistically adjusting the data 543 Selecting a data analysis strategy 545 Data integrity across countries and cultures 548 Practise data analysis with SPSS 549 Summary552 Questions552 Exercises553 Notes554

20 Frequency distribution, crosstabulation and hypothesis testing

556

Objectives557 Overview557 Frequency distribution 560 Statistics associated with frequency distribution 562 A general procedure for hypothesis testing 565 Cross-tabulations570 576 Statistics associated with cross-tabulation Hypothesis testing related to differences 580 Parametric tests 582 Non-parametric tests 588 Practise data analysis with SPSS 593 Summary596 Questions596 Exercises597 Notes598

21 Analysis of variance and covariance 601 Objectives602 Overview602 Relationship among techniques 604 One-way ANOVA 605 606 Statistics associated with one-way ANOVA Conducting one-way ANOVA 606 Illustrative applications of one-way ANOVA 610 n-way ANOVA 614 Analysis of covariance (ANCOVA) 619 Issues in interpretation 620 Repeated measures ANOVA 622 Non-metric ANOVA 624 Multivariate ANOVA 624 Practise data analysis with SPSS 625 Summary626 Questions627 Exercises627 Notes630

22 Correlation and regression

632

Objectives633 Overview633 Product moment correlation 634 Partial correlation 638

Contents

Non-metric correlation 640 Regression analysis 641 Bivariate regression 641 Statistics associated with bivariate regression analysis642 Conducting bivariate regression analysis 642 Multiple regression 651 Statistics associated with multiple regression 652 Conducting multiple regression analysis 653 Multicollinearity661 Relative importance of predictors 662 Cross-validation662 Regression with dummy variables 663 Analysis of variance and covariance 664 with regression Practise data analysis with SPSS 665 Summary666 Questions667 Exercises667 Notes670

23 Discriminant and logit analysis

673

Objectives674 Overview674 Basic concept of discriminant analysis 675 Relationship of discriminant and logit analysis to ANOVA and regression 676 Discriminant analysis model 676 Statistics associated with discriminant analysis677 Conducting discriminant analysis 678 Conducting multiple discriminant analysis 688 Stepwise discriminant analysis 696 696 The logit model Conducting binary logit analysis 696 Practise data analysis with SPSS 702 Summary703 Questions704 Exercises705 Notes705

24 Factor analysis

707

Objectives708 Overview708 Basic concept 709 Factor analysis model 710 Statistics associated with factor analysis 711 Conducting factor analysis 712 Applications of common factor analysis 724 Practise data analysis with SPSS 729 Summary730 Questions731 Exercises731 Notes733

25 Cluster analysis

735

Objectives736 Overview736 Basic concept 737 Statistics associated with cluster analysis 739 Conducting cluster analysis 739 Applications of non-hierarchical clustering 750 Applications of TwoStep clustering 752 Clustering variables 754 Practise data analysis with SPSS 757 Summary758 Questions759 Exercises759 Notes760

26 Multidimensional scaling and conjoint analysis

762

Objectives763 Overview763 765 Basic concepts in MDS Statistics and terms associated with MDS 765 Conducting MDS 766 Assumptions and limitations of MDS 773 Scaling preference data 773 775 Correspondence analysis Relationship among MDS, factor analysis anddiscriminant analysis 776 Basic concepts in conjoint analysis 776 Statistics and terms associated with 777 conjoint analysis Conducting conjoint analysis 778 Assumptions and limitations of conjoint analysis 786 Hybrid conjoint analysis 786 Practise data analysis with SPSS 788 Summary789 Questions790 Exercises790 Notes791

27 Structural equation modelling and path analysis

795

Objectives796 Overview796 Basic concepts in SEM 797 Statistics and terms associated with SEM 798 Foundations of SEM 800 Conducting SEM 802 813 Higher-order CFA Relationship of SEM to other multivariate techniques814 Application of SEM: first-order factor model 814 Application of SEM: second-order factor model 817 Path analysis 823

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Software to support SEM 826 Summary826 Questions828 Exercises828 Notes829

28 Communicating research findings

831

Objectives832 Overview832 Why does communication of research findings matter? 833 Importance of the report and presentation 835 Preparation and presentation process 836 Report preparation 837 Guidelines for graphs 842 Report distribution 845 Digital dashboards 845 Infographics847 847 Oral presentation Research follow-up 849 Summary850 Questions851 Exercises852 Notes852

29 Business-to-business (b2b) marketing research

854

Objectives855 Overview855 What is b2b marketing and why is it important? 856 The distinction between b2b and consumer marketing857 Concepts underlying b2b marketing research 858

Implications of the differences between business and consumer purchases for researchers 860 The growth of competitive intelligence 873 The future of b2b marketing research 876 Summary877 Questions877 Exercises878 Notes878

30 Research ethics

881

Objectives882 Overview882 Ethics in marketing research 884 Professional ethics codes 884 Ethics in the research process 888 Ethics in data collection 890 Data analysis 896 Ethical communication of research findings 898 Key issues in research ethics: informed consent 898 Key issues in research ethics: maintaining respondenttrust900 Key issues in research ethics: anonymity 901 and privacy Key issues in research ethics: sugging and frugging 905 Summary905 Questions906 Exercises906 Notes906 Glossary908 926 Subject index Name index 952 Company index 954

Supporting resources Visit www.pearsoned.co.uk/malhotra_euro to find valuable online resources For more information please contact your local Pearson Education sales representative or visit www.pearsoned.co.uk/malhotra_euro

Chapter 3 Research design

xiii

Preface

What’s new in this edition? Working as a marketing researcher remains an intellectually stimulating, creative and rewarding career. Globally, marketing research is an industry that turns over more than $40 billion a year and is at the forefront of innovation in many sectors of the economy. However, few industries can have been presented with as many challenges and opportunities as those faced by marketing research due to the growing amounts of data generated by modern technology. Founded upon the enormously successful US edition, and building upon the previous four European editions, the fifth edition of this book seeks to maintain its position as the leading marketing research text, focused on the key challenges facing marketing research in a European context. As with previous editions, this aims to be comprehensive, authoritative and applied. As a result, the book covers all the topics in previous editions while including a number of new chapters that reflect the changes and challenges that have impacted the marketing research sector since the fourth edition was published. This edition has been significantly updated, with new chapters, new content, updated cases studies and a major focus on the issues and methods generated by new technologies. Key improvements and updates in this edition include: 1 New chapters on social media research and mobile research. These chapters provide an in-depth and very current view of these two key areas of technology. Both social media and mobile research provide researchers with a range of new opportunities to collect data. At the same time, they pose a threat to many of the existing ways in which research is carried out. 2 A dedicated chapter on research ethics. Research ethics has been an important part of this text in previous editions but the growing range of data collection

enabled through social media or other ‘big data’ sources has created a new range of ethical challenges around maintaining respondent privacy. This chapter includes recently updated research industry ethics codes and the discussion around the threats to core ethical principles of research (such as anonymity) that are posed by new technologies. 3 Focus on communicating research findings. The last stage of the marketing research model that forms the core of this and previous editions of the book has been renamed from ‘Reporting preparation and presentation’ to ‘Communicating research findings’. This recognises the increasing range of channels through which research is communicated and the need to look beyond the old-style research report to what influences today’s busy managers. Chapter 28 on communicating research findings has been updated to reflect this. 4 New and updated examples and data. A wide range of new examples, including more than 35 new and updated ‘Real Research’ case studies, are presented. Material referring to industry data and research firms has been updated to include the most recent data available at time of publication. 5 Data analysis with SPSS. Reflecting the feedback from previous editions, this book has focused upon SPSS – where step-by-step instructions for conducting the data analysis in each chapter on quantitative analysis are included. These are available to download at the text website, and instructions are suitable for both Windows and Mac versions of SPSS. Recognising that there are a wide range of software programs available for carrying out data analysis – including those suitable for qualitative analysis – we also include details of alternative and emerging software programs, where appropriate. These include lower-cost or opensource programs.

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6 Updated references. The book contains many more recent references, including articles, conference papers and academic research, as well as retaining the classic references.

examples and cases from around the world and embeds key cross-cultural issues within the wider discussion of research techniques and methods.

If you take advantage of the following special features, you should find this text engaging, thought provoking and even fun:

5 Contemporary focus. We apply marketing research to current challenges, such as customer value, experiential marketing, satisfaction, loyalty, customer equity, brand equity and management, innovation, entrepreneurship, relationship marketing, creativity and design and socially responsible marketing.

1 Balanced orientation. This book contains a blend of scholarship and a highly applied and managerial orientation, showing how researchers apply concepts and techniques and how managers use their findings to improve marketing practice. In each chapter, we discuss real marketing research challenges to support a great breadth of marketing decisions.

6 Statistical software. We illustrate data analysis procedures, with emphasis upon SPSS and SAS. SPSS sections in the relevant chapters discuss the programs and the steps you need to run them. On our website we also describe and illustrate NVivo qualitative data analysis software and provide details of other key software tools for statistical and other forms of data analysis.

Integrated learning package

2 Real-life examples. Real-life examples (‘Real research’ boxes) describe the kind of marketing research that companies use to address specific managerial problems and how they implement research to great effect. 3 Hands-on approach. You will find more real-life scenarios and exercises in every chapter. The end-ofchapter exercises challenge you to research online and role play as a researcher and a marketing manager. You can tackle real-life marketing situations in which you assume the role of a consultant and recommend research and marketing management decisions. 4 International focus. Reflecting the increasingly globalised nature of marketing research, the book contains

7 Companion website. The companion website has been updated to reflect the changes in this edition. There are new European case studies with discussion points and questions to tackle. All the referenced websites within the text are described, with notes of key features to look for on a particular site. 8 Instructor’s manual. The instructor’s manual is very closely tied to the text, but is not prescriptive in how the material should be handled in the classroom. The manual offers teaching suggestions, answers to all end-of-chapter questions, ‘Professional Perspective’ discussion points and case study exercises. The manual includes PowerPoint slides, incorporating all the new figures and tables.

Publisher’s acknowledgements

We are grateful to the following for permission to reproduce copyright material:

Tables Table 6.1 from ‘Divided by a common language: diversity and deception in the world of global marketing’, Journal of the Market Research Society, vol. 38(2), p. 105 (Goodyear, M., 1996); Table 7.2 adapted from ‘Online audio group discussions, a comparison with face to face methods’, International Journal of Market Research, vol. 51 (2), pp. 219–41 (Cheng, C.C., Krumwiede, D. and Sheu, C., 2009).

Text Extract on p. 21 from ‘James Dyson: He sweeps as he cleans as he spins. What’s next from the ideas factory? A day in the life of the chairman and founder of Dyson’, The Independent, 27/05/2006, p. 55 (Mesure, S.), http:// www.independent.co.uk/news/business/analysis-and-features/james-dyson-he-sweeps-as-he-cleans-as-he-spinswhats-next-from-the-ideas-factory-479931.html; Extract on p. 103 from Social and Welfare News Release, Social Trends, Crown Copyright material is reproduced with permission under the terms of the Click-Use Licence; Extract on p. 412 adapted from ‘Down with random sampling?’, Research World, November, p. 44–5 (Scheffler, H., Zelin, A. and Smith, P., 2007); Extract on pp. 411–12 adapted from ‘Down with random samples’, Research World, May, p. 31 (Kellner, P., 2007); Extract on pp. 480–1 from ‘How was it for you?’, Research, Fieldwork Supplement (July), pp. 8–9 (Park, C., 2000); Extract on pp. 886–7 from ESOMAR news ‘It’s here: What the new EU Data Protection law means for market research’, https://www.esomar.org/utilities/news-multimedia/news. php?idnews=195; Extract on pp. 901–2 from ‘Viewpoint - MR confidential: anonymity in market research’, International Journal of Market Research, vol. 50 (6), pp. 717–18 (Griffiths, J. 2008).

Photographs The publisher would like to thank the following for their kind permission to reproduce their photographs: (Key: b – bottom; c – centre; l – left; r – right; t – top) 123RF.com: 22, 64, 134, 243, 257, 525, 735, 869, bonninstudio 491, sirylok 673, siuwing 516, Tono Balaguer 271, vizafoto 556; Pearson Education Ltd: Ann Cromack. Ikat Design 222, Cheuk-king Lo 428, Debbie Rowe 585, Gareth Dewar 541, Jules Selmes 382, Naki Kouyioumtzis 116, 796, Sian Bradfield. Pearson Education Australia Pty Ltd 694, Studio 8 728; Shutterstock.com: 1279606 632, 3024425 799, aastock 573, Adam Gregor 207, alexskopje 443, alphaspirit 795, Amble Design 13, AMC Photography 169, Amy Johansson 290, Angela Waye 519 Apples Eyes Studio 954, arek_malang 431, ariadna de raadt 818, auremar 41, bikeriderlondon 886, Bikeworldtravel 726, Bloomua 361, 513, Bob Denelzen 233, Brocreative 97, CandyBox Images 685, Catalin Petolea

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787, Catherine Murray 153, clivewa 147, Dean Drobot 179, Denis Pepin 601, Djomas 79, dotshock 486, Doug Stevens 752, Dusit 91, 267, ejwhite 255, Gergo Orban 533, Gunnar Pippel 755, gyn9037 314, Hellen Grig 215, iconspro 651, igor.stevanovic 764, Ioannis Pantzi 481, iofoto 617, Ivelin Radkov 506, ivosar 427, Jaimie Duplass 890, Jeff Banke 143, Jeff Dalton 3, Johan Swanepoel 736, JohnKwan 388, KKulikov 714, koh sze kiat 29, koh sze kiat 29, Kovalchuk Oleksandr 302, kRie 371, kubais 859, Kzenon 339, 609, LANBO 707, Lichtmeister 881, Login 1, Marcio Eugenio 192, Mark Herreid 809, Matej Kastelic 322, Meg Wallace Photography 444, 456, MJTH 459, Monkey Business Images 866, Nata-Lia 71, Nickolay Stanev 51, Olivier Le Queinec 544, ollyy 307, Pavel L Photo and Video 398, Pixsooz 471, Rawpixel 195, Richard Peterson 181, Rido 484, Robnroll 333, Roger Asbury 842, scyther5 500, Sinisa Botas 680, Stephen Coburn 131, Stephen Rees 220, StockLite 633, SvetlanaFedoseyeva 164, Tan Kian Khoon 836, Tim Scott 278, trendywest 762, Tyler Olson 496, 831, 848, 903, viki2win 35, vinzstudio 59, Vladimir Wrangel 602, Vlue 409, wellphoto 107, William Perugini 528, Yuttasak Jannarong 659, zimmytws 349, 557 All other images © Pearson Education

Chapter 3 Research design

xvii

About the authors

Dr Naresh K. Malhotra is Senior Fellow, Georgia Tech CIBER and Regents’ Professor Emeritus, Scheller College of Business, Georgia Institute of Technology, USA. He has published more than 135 papers in major refereed journals, including the Journal of Marketing Research, Journal of Consumer Research, Marketing Science, Management Science, Journal of Marketing, Journal of Academy of Marketing Science, Journal of Retailing, Journal of Health Care Marketing and leading journals in statistics, management science, information systems and psychology. He was Chairman, Academy of Marketing Science Foundation, 1996–1998, and was President, Academy of Marketing Science, 1994–1996 and Chairman, Board of Governors, 1990–1992. He is a Distinguished Fellow of the Academy and Fellow of the Decision Sciences Institute. He is the founding Editor of Review of Marketing Research and served as an Associate Editor of Decision Sciences for 18 years. His book entitled Marketing Research: An Applied Orientation has been translated into eight languages and is being used in over 100 countries. Dr Malhotra has consulted for business, non-profit and government organisations in the USA and abroad and has served as an expert witness in legal and regulatory proceedings. He is the winner of numerous awards and honours for research, teaching and service to the profession. Dr Daniel Nunan is Lecturer in Marketing at Birkbeck, University of London, having previously been a member of faculty at Henley Business School, University of Reading. Dan has published in journals including the Journal of Business Ethics, New Technology, Work and Employment, International Journal of Market Research and Journal of Marketing Management. He is a member of the Editorial Board of the International Journal of Market Research and has been a reviewer for a number of leading journals. Dan was nominated for the Market Research Society Silver Medal in 2012 and 2014, and won the MRS Award for Innovation in Research Methodology in 2012. DrNunan is a Fellow of the Higher Education Academy and the Royal Statistical Society. Prior to his academic career, Dan held senior marketing roles in the financial services and technology sectors. Professor David F. Birks is Professor of Marketing at the University of Winchester. He is Dean of the Faculty of Business, Law and Sport and Director of Winchester Business School. Prior to working at Winchester, David worked at the Universities of Southampton, Bath and Strathclyde. David has over 30 years’ experience in universities, primarily working on postgraduate research, marketing, management and design programmes. David is a committee member of the Association for Survey Computing (ASC), the world’s leading society for the advancement of knowledge in software and technology for research surveys and statistics. He has continued to practise marketing research throughout his university career, managing projects in financial institutions, retailers, local authorities and charities.

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1 Stage 1

Problem definition

Stage 2 Research approach developed

Stage 3 Research design developed

Stage 4 Fieldwork or data collection

Stage 5 Data integrity and analysis

Stage 6 Communicating research findings

Introduction to marketing research Marketing research supports decision making through collecting, analysing and interpreting information to identify and solve marketing problems.

Marketing Research

Objectives After reading this chapter, you should be able to: 1 understand the nature and scope of marketing research and its role in supporting marketing decisions; 2 describe a conceptual framework for conducting marketing research, as well as the steps in the marketing research process; 3 distinguish between problem-identification and problem-solving marketing research; 4 appreciate the impact that technology is having on the marketing research industry; 5 appreciate the role of marketing research in different regions and countries throughout the world; 6 understand the types and roles of research suppliers, including internal and external, full-service and limited-service suppliers; 7 understand why some marketers may be sceptical of the value of marketing research; 8 appreciate the skills that researchers will need to succeed in the future world of marketing research.

Overview When you hear the term ‘marketing research’ what comes to mind? People with clipboards stopping you on the street to ask for your opinion? Reading the results of a political opinion poll in the media? A report on opportunities for new markets being presented to managers? All of these activities represent traditional types of marketing research activities, but they don’t even begin to capture the range and breadth of activities that encompass marketing research today. Marketing research is one of the most important, interesting and fastmoving aspects of marketing. In this chapter, we introduce the concept of marketing research, emphasising its key role in supporting marketing decision making, and provide several real-life examples to illustrate the basic concepts of marketing research. We discuss formal definitions of marketing research and show how these link to a six-stage description of the marketing research process. This description is extended to illustrate many of the interconnected activities in the marketing research process. We then subdivide marketing research into two areas: problem-identification and problem-solving research. Finally, an overview of the global marketing research sector is provided, including details of expenditure and key research firms. The marketing research industry is going through a huge period of change. Much of this change derives from technological developments that are affecting nearly all aspects of how consumers interact with companies. The growth of the internet, the shift to mobile computing and the emergence of ‘big data’ have raised fundamental questions over the relevance of traditional notions of marketing research. However, technology is not the only source of change. Both academics and practitioners have noted that it is getting more difficult to persuade people to take part in research, partly because research tools such as surveys are so commonly used in nearly all aspects of our day-to-day lives. Another emerging issue is the increasing interest from governments in the ways that companies are collecting and using data about their customers. This creates the potential for new forms of data protection legislation that could place tighter legal restrictions on the kinds of research that can be undertaken. On the other hand, change brings opportunity. New technologies have brought with them an exciting range of new research techniques. Above all, with organisations being awash with data, the need for researchers skilled in being able to turn this data into insight has never been greater. There are many successful marketing decisions that have been founded upon sound marketing research; however, marketing research does not replace decision making. We explore the need to justify investment in marketing research alongside the challenges facing marketing research as an industry. At the same time, these challenges create new ways for researchers to design and produce research that is actionable and relevant to marketing decision makers.

Chapter 1 Introduction to marketing research

What does ‘marketing research’ mean? The term ‘marketing research’ is broad in meaning and application. This breadth will be explored and illustrated throughout this chapter. What will become apparent is that it is related to supporting marketing decision making in many traditional and new ways. The following examples illustrate some of the different contexts in which marketing research can be applied.

Real research

Customer service on London Buses London’s bus network is one of the world’s largest, carrying more than 6.5 million passengers each day using a fleet of over 8,600 (mostly red) buses. The network is overseen by Transport for London (TfL) and keeping so many customers happy is not an easy job. TfL relies on research to make sure it understands the customer experience. In 2014 TfL realised that, despite major investment, thousands of customers were contacting it each month to complain about the service received. Working with agency research partners, TfL was able to bring together data from a wide range of sources including complaints data, social media analysis, customer satisfaction surveys, customer experience ethnographies, driver depth interviews and observations and bus staff surveys. Analysis of this data, particularly that of social media data, found that customers viewed their interactions with employees as nearly as important as the functional reliability of the bus services, such as the range of routes or a bus being on time. A lot of customer complaints were due to bus drivers not always stopping when expected or poor communication when something went wrong, such as a delay or disruption. On the other hand, analysis of employee data showed that bus drivers viewed their role as functional – simply driving the bus! Research identified the disconnect, which was then addressed via a series of workshops to help bus drivers understand the importance of customer experience. Follow-up research six months later indicated that the workshops had significantly increased employees’ engagement with customers.1

Real research

Steve Jobs on market research Steve Jobs, Apple CEO and founder, was one of the most influential business leaders of modern times and the wider impacts of his work are felt by hundreds of millions of people around the world each day. But what did he think of market research? At first glance not a great deal, as he was famously quoted as saying the following: Some people say, ‘Give the customers what they want.’ But that’s not my approach. Our job is to figure out what they’re going to want before they do. I think Henry Ford once said, ‘If I’d asked customers what they wanted, they would have told me, “A faster horse!” People don’t know what they want until you show it to them. That’s why I never rely on market research. Our task is to read things that are not yet on the page.2’

Marketing Research

You will find this quote widely used online when referring to the weaknesses of marketing research. However, it doesn’t quite tell the whole story. Information that came to light after Steve Jobs’ death found that Apple carried out plenty of market research to better understand what customers thought about both its products and competitors.3 As it turns out, what Steve Jobs was talking about was the role of focus groups in developing completely new and innovative products, such as the iPhone, where a customer lacks knowledge of what the product can actually do.

Real research

Moving on from ‘low-cost’ with easyJet Measured by the number of passengers carried, easyJet is the largest UK airline and the second largest in Europe. It has a history of using innovative research techniques to generate the highest returns from its marketing budget. For example, easyJet was an early adopter of online research communities to gain feedback from customers more quickly than was possible with traditional approaches.4 More recently, following a long period of success, easyJet has sought to improve its brand perception and move away from a marketing model purely based upon low prices. This involved moving to more of an affinitybuilding approach based around the ‘Europe by easyJet’ approach. One of the challenges it faced was finding a budget for brand advertising on television without damaging the results of expenditure on existing channels.5 By carrying out research on the effectiveness of search-engine advertising, it found that it could reduce expenditure on certain keywords, such as ‘easyJet’, without reducing the number of visitors to the website. This created savings of £8 million per year on search advertising alone, which could be reinvested in television advertising.6

These examples illustrate the variety of methods used to conduct marketing research, which may range from highly structured surveys with large samples to open-ended, in-depth interviews with small samples; from the collection and analysis of readily available data to the generation of ‘new’ quantitative and qualitative data; from personal face-to-face interactions to remote observations and interactions with consumers via the internet; from small local studies to large global studies. As is best highlighted by the case of Apple, marketing research techniques can’t be used to solve all business problems, but every company, even Apple, has a place for marketing research. This book will introduce you to the full complement of marketing research techniques and challenges. These examples also illustrate the crucial role played by marketing research in designing and implementing successful marketing plans. This book will introduce you to a broad range of marketing applications supported by marketing research. The role of marketing research can be better understood in light of a basic marketing paradigm depicted in Figure 1.1. The emphasis in marketing, as illustrated in the TfL example above, is on understanding customer experiences and the delivery of satisfaction. To understand customer experiences and to implement marketing strategies and plans aimed at delivering satisfying experiences, marketing managers need information about customers, competitors and other forces in the marketplace. In recent years, many factors have increased the need for more accurate and timely information. As firms have become national and international in scope, the need for information on larger and more distant markets has increased. As consumers have become more affluent, discerning and sophisticated, marketing managers need better information on how they will respond to new products and other new experiences. As competition has become more intense, managers need information on the effectiveness of their marketing tools. As the environment is changing more rapidly, marketing managers need more timely information to cope with the impact of these changes.

Chapter 1 Introduction to marketing research

Figure 1.1

Macroenvironmental factors • Economy • Technology • Competitors • Legal and political • Social and demographic

The role of marketing research within the marketing system

• • • •

Microenvironmental • Family • Peer groups • Opinion leaders

Controllable marketing variables

• Product

Marketing managers Market segmentation Target market selection Marketing programmes Performance and control

• Pricing

• Promotion • Distribution

Exchange of values

• • • •

Consumers Employees Shareholders Suppliers

Customer behaviour, satisfaction, loyalty

Time

Marketing research support: • The nature and scope of target markets • The forces that shape the marketing system • Evaluate marketing mix variables • Evaluate successes and failures of marketing decisions

Marketers make decisions about what they see as potential opportunities and problems, i.e. a process of identifying issues. They go on to devise the most effective ways to realise these opportunities and overcome problems they have identified. They do this based on a ‘vision’ of the distinct characteristics of the target markets and customer groups. From this ‘vision’ they develop, implement and control marketing programmes. This ‘vision’ of markets and subsequent marketing decisions may be complicated by the interactive effects of an array of environmental forces that shape the nature and scope of target markets. These forces also affect the marketers’ ability to deliver experiences that will satisfy their chosen target markets. Within this framework of decision making, marketing research helps the marketing manager link the marketing variables with their environment and customer groups. It helps remove some of the uncertainty by providing relevant information about marketing variables, environment and consumers. The role of the researcher in supporting the marketing decision maker can therefore be summarised as helping to: • • •

• •

describe the nature and scope of customer groups; understand the nature of forces that shape customer groups; understand the nature of forces that shape the marketer’s ability to satisfy targeted customer groups; test individual and interactive variables that shape consumer experiences; monitor and reflect upon past successes and failures in marketing decisions.

Traditionally, researchers were responsible for designing and crafting high-quality research and providing relevant information support, while marketing decisions were made by the managers. The clarity and distinction of these roles are blurring somewhat. Researchers are becoming more aware of decision making; conversely, marketing managers are becoming more aware of research and the use of an eclectic array of data sources that can support their decision making. This trend can be attributed to better training of marketing managers and advances in technology; the advances in technology are a theme that we will discuss in more detail throughout the text. There has also been a shift in the nature and scope of marketing research. Increasingly marketing research is being undertaken not only on an ongoing basis but on a ‘real-time’ basis, rather than a traditional notion of research being in response to

Marketing Research

specific marketing problems or opportunities.7 Major shifts are occurring in the marketing research industry that are impacting upon the perceived nature and value of marketing research. The nature of these shifts and their impact upon new approaches to marketing research will be addressed later in this chapter. The current and developing role of marketing research is recognised in its definition.

A brief history of marketing research Before defining marketing research, it is useful to consider some of the history of the field. This is not because marketing researchers need to be historians – far from it. Rather, history helps to give us context. In a time where the research sector is facing many changes and challenges, being able to understand the forces that have shaped the development of marketing research in the past and present will better enable us to understand the future. The first point to make is that while the term ‘marketing research’ is relatively recent, the concepts that underlie it are not new. As long as the opinions of the public have mattered, and traders have had a need to improve their level of trade, then some form of research has been undertaken. The bustling markets of ancient Rome have been characterised as a market economy, with traders seeking competitive advantage while dealing with suppliers, farmers and craftsmen in distant lands. As today, information such as the prices consumers were willing to pay for certain products was valuable to traders and much effort was spent on gathering and exchanging such information.8 Even many modern research techniques have origins far into the past. The Domesday Book, a research project completed in 1086 for the English King William the Conqueror, contained details of land holdings in England and Wales. Perhaps Europe’s oldest and most valuable statistical document, the original, and less ominous, name of the book was descriptio – the Latin word for ‘survey’. However, elements of what would be immediately recognisable as marketing research can be traced back to more recent times. For example, opinion polls in the USA can can be traced back to the 1820s, and questionnaires were being used widely to gauge consumer opinion of advertising as early as the 1890s.9 The first evidence of market research use becoming mainstream happened in the period from 1910–20 and it is generally accepted that the marketing research industry was well embedded in commercial life by the 1930s.10 Thus, when professional associations such as ESOMAR or the UK’s market research society (MRS) were established in the late 1940s, it didn’t represent the beginning of marketing research but rather the capstone on a longer period of development. We will discuss some of the innovations since this time, for example in the development of research ethics guidelines, in later chapters. The important point here is that marketing research has been a well-established part of commercial life for more than 100 years. It has successfully navigated the huge social, political and economic changes facing the world over this period and has continued to prosper. From television to the internet, marketing research has adapted to each new set of technologies, while the key focus on producing high-quality research, and doing so with integrity, has remained.

Definition of marketing research You might ask why we need a definition of marketing research – isn’t it obvious? The challenge is that when many managers think about marketing research, they focus on the data collection aspects of research. This ignores the importance of a wider research process and doesn’t tell us how marketing research might differ from other marketing activities. To understand these issues we can review two common definitions of marketing research. You might note that the first definition uses the term ‘market research’, while the second talks

Chapter 1 Introduction to marketing research

about ‘marketing research’; we will discuss this point later in this section. The first is from ESOMAR (originally the European Society for Opinion and Market Research), a global membership organisation for research firms and practitioners: Market research, which includes social and opinion research, is the systematic gath ering and interpretation of information about individuals or organisations using the statistical and analytical methods and techniques of the applied sciences to gain insight or support decision making. The identity of respondents will not be revealed to the user of the information without explicit consent and no sales approach will be made to them as a direct result of their having provided information.11 Several aspects of this definition are noteworthy. It includes opinion and social research within its definition, meaning that it’s not only for-profit companies that undertake market research. Charities, governments and other third- or public-sector organisations are also important users of research. Secondly, it makes it clear that the principle of anonymity applies to market research and that the identity of those partaking in research will not be revealed. Finally, it highlights the importance of gaining consent from research participants and not selling directly to them as a result of partaking in research. Consent and anonymity are key concepts of market research and we will return to them throughout this text. Our second definition comes from the American Marketing Association (AMA): Marketing research is the function that links the consumer, customer, and public to the marketer through information – information used to identify and define marketing opportunities and problems; generate, refine, and evaluate marketing actions; monitor marketing performance; and improve understanding of marketing as a process. Marketing research specifies the information required to address these issues, designs the method for collecting information, manages and implements the data collection process, analyzes the results, and communicates the findings and their implications.

Marketing research is the function that links the consumer, customer, and public to the marketer through information – information used to identify and define mar keting opportunities and problems; generate, refine, and evaluate marketing actions; monitor marketing performance; and improve understanding of market ing as a process. Marketing research specifies the information required to address these issues, designs the method for collecting information, manages and imple ments the data collection process, analyzes the results, and communicates the find ings and their implications.12 This definition has several aspects that differentiate it from the previous ESOMAR definition. Most importantly, it stresses the role of marketing research as a process of ‘linking’ the marketer to the consumer, customer and public to help improve the whole process of marketing decision making. It also sets out the challenges faced by marketing decision makers and thus where research support can help them make better decisions, and/or decisions with lower risks. Notably, it also alludes to the ethical issues surrounding market research (which will be covered in depth in Chapter 30). We should remember that definitions often reflect the interests of those who create them. Ultimately, ESOMAR exists to look after and promote the interests of its members, so it is not surprising that in defining marketing research it seeks to position it as something sep arate from marketing. On the other hand, the AMA takes a more integrative view of marketing research as part of marketing activity. With this in mind, neither definition is ‘best’ – they simply take different perspectives and both give us a useful understanding as to the scope of marketing research. One area of potential confusion is with distinctions between marketing research and mar ket research. In terms of usage, these distinctions are largely geographic in nature, with research practitioners in Europe preferring ‘market research’ and those in the USA ‘marketing research’. However, behind the semantics of the exact words used there lies slightly different views on how the industry should be seen. ‘Market research’ is more closely associated with the research industry and good practice. On the other hand, the AMA definition’s use of ‘marketing research’ refers to the broader consumer context that drives the undertaking of research. While there were once a number of regional differences reflecting local research cultures in different markets, as commerce has become increasingly globalised so too has the use of language. This means that ‘marketing research’ has become increasing commonly used around the world while, even within Europe, ‘market research’ and ‘marketing research’ are often used interchangeably.

Marketing Research

One final, final point of note on language is the use of the word ‘insight’. For many years, marketing and market research professionals and functions have been termed or associated with ‘consumer insight’, as illustrated by the following example from Diageo. There has been much debate about what consumer insight means and how this may give a ‘richer’ understanding of consumers compared with traditional notions of market research. At the heart of this debate is a clear recognition that the links to consumers and support given to marketing decision makers are being delivered by a much broader and diverse array of techniques and sources.

Real research

What consumer insight means to Diageo13 Diageo’s (www.diageo.com) strong belief is that in order to be a world-class company, it all starts with the consumer: ‘knowing them, understanding them, understanding their motivations, understanding what drives them, and subsequently utilising this information to better serve consumers’. ‘Consumer insight’ is at the heart of what they see makes them a world-class company. Consumer insight, as defined by Diageo, is: ‘A penetrating discovery about consumer motivations, applied to unlock growth’:

Marketing research process A set of six steps that define the tasks to be accomplished in conducting a marketing research study. These include problem definition, developing a research approach, research design, fieldwork or data collection, data analysis and communicating research findings.

•

Penetrating – same data, but much deeper understanding.

•

Discovery – ah-ha! eureka!

•

Motivations – understand the why?

•

Applied – leveraged for their brands.

•

Growth – organic from brand strategies based on deep consumer understanding.

At the core of the definitions of marketing and market research is an understanding of the consumer and what shapes consumers. Regardless of whether a research professional is defined as a ‘marketing researcher’, ‘market researcher’ or ‘consumer insight manager’, the focus upon consumers is paramount. However, the role and expectations of the marketing researcher can be argued to have the widest scope of practice. The expectations and demands of such a scope will be addressed later in this chapter, but for now we will use and adopt the broader definition of marketing research. Focusing upon ‘marketing research’ helps to encapsulate the profession of managing the process of measuring and understanding consumers in order to better support marketing decision making, a profession that strives for the highest levels of integrity in applying sound research methods in an ethical manner. It is recognised that marketing research can now include understanding the macro-business operating environment, monitoring market trends, conducting competitive analyses, answering business questions, identifying business opportunities and assessing potential risks. More analytics, insights and future outlooks are demanded from business leaders to help them better understand their customers, the marketplace and the overall business environment. Researchers have to adapt and respond to these demands. One of the major qualities of the American Marketing Association’s definition of marketing research is its encapsulation of the marketing research process. The process is founded upon an understanding of the marketing decision(s) needing support. From this understanding, research aims and objectives are defined. To fulfil defined aims and objectives, an approach to conducting the research is established. Next, relevant information sources are identified and a range of data collection methods are evaluated for their appropriateness, forming a research design. The data are collected using the most appropriate method(s); they are analysed and interpreted, and inferences are drawn. Finally, the findings, implications and recommendations are provided in a format that allows the information to be used for marketing decision making and to be acted upon directly. It is important that marketing research should aim to be objective. It should attempt to provide accurate information in an impartial manner. Although research is always influenced

Chapter 1 Introduction to marketing research

by the researcher’s research philosophy, it should be free from personal or political biases of the researcher or decision makers. Research motivated by personal or political gain involves a breach of professional standards. Such research is deliberately biased to result in predetermined findings. The motto of every researcher should be ‘Find it and tell it like it is’. Second, it is worth noting the term ‘total field of information’. This recognises that marketing decisions are not exclusively supported by marketing research. There are other means of information support for marketers, from management consultants, raw-data providers such as call centres, direct marketing, database marketing telebusinesses and social media. These alternative forms of support are now competing with the ‘traditional’ view of marketing research. The methods of these competitors may not be administered with the same scientific rigour and/or ethical standards applied in the marketing research industry. Nonetheless, many marketing decision makers are increasingly using these other sources, which collectively are changing the nature of skills demanded in researchers.

The marketing research process The marketing research process consists of six broad stages. Each of these stages is developed in more detail in subsequent chapters; thus, the discussion here is brief. The process illustrated in Figure 1.2 is of the marketing research seen in simple stages. Figure 1.3 takes the process a stage further to show the many iterations and connections between stages. This section will explain the stages and illustrate the connections between the stages. Step 1: Problem definition. The logical starting point in wishing to support the decision maker is trying to understand the nature of the marketing problem that requires research support. Marketing decision problems are not simple ‘givens’ (as will be discussed in Chapter 2). Many researchers are surprised to learn that clearly defining a research problem can be the most challenging stage in a research project. The symptoms and causes of a problem are not, in reality, as neatly presented as they may be in a case study, such as those found in marketing textbooks. In Figure 1.3, the first three stages show the iterations between the environmental context of the problem, the marketing decision problem and the marketing research problem. Understanding the environmental context of the problem has distinct stages (which will be discussed in Chapter 2). It involves discussion with decision makers, in-depth interviews with industry experts and the collection and analysis of readily available published information (from both inside and outside the firm). Once the problem has been precisely defined, the researcher can move on to designing and conducting the research process with confidence. Step 2: Developing a research approach. The development of an approach to the research problem involves identifying factors that influence research design. A key element of this step involves the selection, adaptation and development of an appropriate theoret ical framework to underpin a research design. Understanding the interrelated characteristics of the nature of target participants, the issues to be elicited from them and the context in which this will happen relies upon ‘sound’ theory. ‘Sound’ theory helps the researcher to decide ‘what should be measured or understood’ and ‘how best to encapsulate and communicate the measurements or understandings’. In deciding what should be either measured or encapsulated, the researcher also develops a broad appreciation of how the data collected will be analysed. (The issues involved in developing an approach are tackled in more detail in Chapter 2.) Step 3: Research design. A research design is a framework or blueprint for conducting a marketing research project. It details the procedures necessary for obtaining the required information. Its purpose is to establish a study design that will either test the hypotheses of interest or determine possible answers to set research questions, and ultimately provide the information needed for decision making. Conducting any exploratory techniques, precisely

Marketing Research

Figure 1.2 Simple description of the marketing research process

Stage 1: Problem definition

Stage 2: Research approach developed

Stage 3: Research design developed

Stage 4: Fieldwork or data collection

Stage 5: Data integrity and analysis

Stage 6: Communicating research findings

defining variables to be measured and designing appropriate scales to measure variables can also be part of the research design. The issue of how the data should be obtained from the participants (e.g. by conducting a survey or an experiment) must be addressed. (These steps are discussed in detail in Chapters 3 to 13.) Step 4: Fieldwork or data collection. In Figure 1.2, this stage could be simplified to ‘collecting the required data’. In Figure 1.3, a whole array of relationships between stages of data collection is shown, starting at secondary data collection and analysis through to quantitative research or qualitative research. The process starts with a more thorough collection and analysis of secondary data sources. Secondary data are data collected for some other purpose than the problem at hand. They may be held within the organisation as databases that detail the nature and frequency of customer purchases, through to surveys that may have been completed some time ago that may be accessed through libraries or through online sources. Going through this stage avoids replication of work and gives guidance in sampling plans and in deciding what to measure or encapsulate using quantitative or qualitative techniques. Secondary data collection and analysis may complete the research process, i.e. sufficient information may exist to interpret and report findings to a point whereby the information gaps that the decision maker has are filled. Secondary data form a vital foundation and essential focus to primary data collection. In Figure 1.3, the stage of ‘Identify and select individuals for primary research’ covers sampling issues for both quantitative and qualitative studies. This stage may include the selection of individuals for in-depth qualitative research. In qualitative research, issues of ‘representativeness’ are less important than the quality of individuals targeted for investigation and the quality of response elicited. However, as can be seen from the line leading up from ‘Qualitative research’ to ‘Identify and select individuals for primary research’, the qualitative research process may help in the identification and classification of individuals who may be targeted using more formal sampling methods. (These sampling methods are covered in detail in Chapters 14 and 15.)

Chapter 1 Introduction to marketing research

Figure 1.3 The marketing research process, detailing iterations between stages

Environmental context of the problem

Marketing decision problem

Marketing research problem

Marketer supported for set problem(s) but also a contribution made towards organisational learning in terms of building up marketing knowledge

Approach to the problem developed Marketer’s information gaps filled Research design developed

Secondary data collection and analysis Interpret and present research findings Identify and select individuals for primary research

Qualitative research

Quantitative research

Qualitative research

Beyond the issues of identifying and selecting individuals, the options available for primary data collection vary considerably. A stage of qualitative research alone may be sufficient to support the decision maker, as indeed could a stage of quantitative research. In their own right, qualitative techniques do not necessarily have to be followed by a survey or quantitative work to confirm the observations. (In-depth interviewing will be described and evaluated in Chapter 8). A research problem may require a stage of qualitative and quantitative research to run concurrently, perhaps measuring and encapsulating different characteristics of the problem under investigation. Alternatively, a stage of qualitative research could be used to precede a stage of quantitative research. For example, a sequence of focus groups may help to generate a series of statements or expectations that are subsequently tested out in a survey to a representative sample. Conversely, a survey may be conducted and, upon analysis, there may be clear, statistically significant differences between two distinct target markets. A series of qualitative in-depth interviews may follow to allow a more full exploration and understanding of the reasons for the differences between the two groups. Step 5: Data analysis. Data preparation includes the editing, coding, transcription and verification of data. This is perhaps the least glamorous aspect of market research but is critical in ensuring the integrity and accuracy of findings. In Figure 1.3, this stage is not drawn out

Marketing Research

as a distinct stage in its own right, but is seen as integral to the stages of secondary data collection and analysis through to quantitative research or qualitative research. The process of data integrity and analysis is essentially the same for both quantitative and qualitative techniques, for data collected from both secondary and primary sources. Considerations of data analysis do not occur after data have been collected; such considerations are an integral part of the development of an approach, the development of a research design and the implementation of individual quantitative or qualitative methods. If the data to be collected are qualitative, the analysis process can occur as the data are being collected, well before all observations or interviews have been completed. An integral part of qualitative data preparation and analysis requires researchers to reflect upon their own learning and the ways they may interpret what they see and hear. (These issues will be developed in Chapters 6 to 9.) If the data to be analysed are quantitative, each questionnaire or observation form is inspected or edited and, if necessary, corrected to ensure the integrity of data. The data from questionnaires are loaded, transcribed or keypunched into a chosen data analysis package. Verification ensures that the data from the original questionnaires have been accurately transcribed, whereas data analysis gives meaning to the data that have been collected. Univariate techniques are used for analysing data when there is a single measurement of each element or unit in the sample; if there are several measurements of each element, each variable is analysed in isolation. On the other hand, multivariate techniques are used for analysing data when there are two or more measurements of each element and the variables are analysed simultaneously. Step 6: Communicating findings. Even if steps one to five are followed in the best possible way, there is no use carrying out research unless it can be communicated effectively to stakeholders. The traditional route through which to carry out research would be to document the research with a written report that addresses the specific research questions identified, describes the approach, research design, data collection and data analysis procedures adopted, and presents the results and major findings. However, due to increasing pressures on managers’ time, researchers realise that they need to go beyond reports – that may never be read – and use alternative means. Frequently these are visual, and can include videos, images or infographics to enhance clarity and impact (see Chapter 28 for more on effective communication of research findings).

A classification of marketing research

Problem identification research Research undertaken to help identify problems that are not necessarily apparent on the surface, yet exist or are likely to arise in the future.

The ESOMAR definition provided earlier in this chapter encapsulates two key reasons for undertaking marketing research: (1) to identify opportunities and problems; and (2) to generate and refine marketing actions. This distinction serves as a basis for classifying marketing research into problem-identification research and problem-solving research, as shown in Figure 1.4. Linking this classification to the basic marketing paradigm in Figure 1.1, problem-identification research can be linked to the description of the nature and scope of customer groups, understanding the nature of forces that shape customer groups and understanding the nature of forces that shape the marketer’s ability to satisfy targeted customer groups. Problem-solving research can be linked to testing individual and interactive marketing mix variables that create consumer experiences, and to monitoring and reflecting upon past successes and failures in marketing decisions. Problem-identification research is undertaken to help identify problems that are, perhaps, not apparent on the surface and yet exist or are likely to arise in the future. Examples of problem-identification research include market potential, market share, brand or company image, market characteristics, sales analysis, short-range forecasting, long-range forecasting and business trends research. Research of this type provides information about the marketing environment and helps diagnose a problem. For example, a declining market potential indicates that the firm is likely to have a problem achieving its growth targets. Similarly, a problem exists if the market potential is increasing but the firm is losing market share. The

Chapter 1 Introduction to marketing research

Figure 1.4

Marketing research

A classification of marketing research Problemidentification research

Examples: • Market-potential research • Market-share research • Image research • Market-characteristics research • Sales-analysis research • Forecasting research • Business-trends research

Problem-solving research Research undertaken to help solve specific marketing problems.

Real research

Problemsolving research

Examples: • Segmentation research • Product research • Pricing research • Promotion research • Distribution research

recognition of economic, social or cultural trends, such as changes in consumer behaviour, may point to underlying problems or opportunities. Once a problem or opportunity has been identified, problem-solving research may be undertaken to help develop a solution. The findings of problem-solving research are used to support decisions that tackle specific marketing problems. Problem-solving research linked to problem-identification research is illustrated by the following example of developing a new cereal at Kellogg’s.

Crunchy Nut Red adds colour to Kellogg’s sales14 In the late 2000s Kellogg’s (www.kelloggs.com) experienced a slump in the market for breakfast-cereal sales. Through problem-identification research, Kellogg’s was able to identify the problem and, through problemsolving research, develop several solutions to increase cereal sales. Kellogg’s performed several tasks to identify the problem. Researchers spoke to decision makers within the company, interviewed industry experts, conducted analysis of available data, performed some qualitative research and surveyed consumers about their perceptions and preferences for cereals. Several important issues or problems were identified by this research. Current products were being targeted at children, alternatives to cereal, such as bagels, were becoming more favoured breakfast foods and high prices were turning consumers to generic brands. Other information also came to light during the research. Adults wanted quick foods that required very little or no preparation. Collectively, these issues helped Kellogg’s identify the problem. The company was not being creative in introducing new products to meet the needs of the adult market. After defining the problem, Kellogg’s went to work on

Marketing Research

s olutions. It developed and tested several new flavours of cereals based upon the results of survey interviews with adult consumers. Based on these results, Kellogg’s introduced new flavours that were more suited to the adult palate but were not the tasteless varieties of the past. Through creative problem-identification research, followed by problemsolving research, Kellogg’s not only saw an increase in sales, but also increased consumption of cereal at times other than breakfast.

This example illustrates how the careful crafting of problem-identification research can help to develop a clear focus to problem-solving research. The outcome was research that supported marketing decisions in many ways. A problem-solving perspective enabled the Kellogg’s decision makers to focus on issues of product development and an integrated communications campaign. Table 1.1 shows the different types of issues that can be addressed using problem-solving research. Table 1.1

Examples of problem-solving research

Segmentation research

Determine basis of segmentation Establish market potential and responsiveness for various segments Select target markets and create lifestyle profiles: demography, media and product image characteristics

Experiential-design research Determine the process of consuming products and services Online consumption experiences Social media engagement Sensory tests Product research

Determine optimal product design Test concept Package tests Product modification Brand positioning and repositioning Test marketing

Pricing research

Importance of price in brand selection Pricing policies Product-line pricing Price elasticity of demand Initiating and responding to price changes

Promotions research

Optimal promotional budget Optimal promotion mix Copy decisions Creative-advertising testing Evaluation of advertising effectiveness

Distribution research

Attitudes of channel members Intensity of wholesale and retail coverage Channel margins Retail and wholesale locations

Chapter 1 Introduction to marketing research

Problem-identification research and problem-solving research can go hand in hand, as seen in the Kellogg’s case, and a given marketing-research project may combine both types of research.

The global marketing research industry Huge changes in the marketing research industry have been developing for a number of years. In order to appreciate the nature and impact of these changes, we turn our attention to the relative rates of demand for marketing research and industry growth rates across the globe. To monitor rates of expenditure and growth, we evaluate the annual ESOMAR Global Market Research Industry Study (www.esomar.org)15, the latest available at time of writing being the 2015 report, including data up until the end of 2014. The figures presented in forthcoming tables are estimates of all the work conducted within individual countries, by research agencies. Not included in the data is marketing research undertaken by non-profit research institutes, governments, universities or advertising agencies using their own resources. The data also do not include the internal supply of marketing research, i.e. the costs of a marketing research function located within a firm. In addition, not included are costs incurred by the more sophisticated users of marketing research who integrate the data and analyses of their operational databases to understand customers and support marketing decision making. Though these estimates are static, and may therefore quickly go out of date, they are a vital means to illustrate developments in the marketing research industry.

Table 1.2

Top 20 countries with the highest research spend (2014 data in US$ million)

Country 1. USA 2. United Kingdom 3. Germany 4. France 5. China 6. Japan 7. Brazil 8. Italy 9. Australia 10. Spain 11. Netherlands 12. South Korea 13. Canada 14. Sweden 15. Russia 16. Mexico 17. India 18. South Africa 19. Switzerland 20. Poland

Research spend (US$ million)

Population (millions)

Research spend per capita (US$)

18,565 5,239 3,359 2,586 1,780 1,730 754 742 646 530 499 466 450 449 385 353 267 222 218 214

319 65 81 64 1,368 127 203 60 24 46 17 50 35 10 144 120 1260 54 8 38

58.19 81.21 44.00 40.45 1.30 13.62 3.72 12.37 27.40 11.41 29.58 9.24 12.67 46.11 2.68 2.95 0.21 4.12 26.79 5.63

Marketing Research

Table 1.3

Region Europe North America Asia – Pacific Latin America Middle East Africa Total world *

Turnover, growth rates and market share per region 2010–2015 in $US million Turnover 2010 ($USmillion) 13,196 13,897 5,168 1,688 334 261 34,544

Turnover 2015 ($USmillion) 16,164 15,512 6,096 1,856 404 273 43,861

Net growth %* −0.8 0.1 1.6 −0.3 9.1 2.6 0.1

Net growth takes into account local inflation rates.

Table 1.3 lists the regional and total global shares of marketing research expenditure and the net growth rates (taking into account local inflation) in these regions between 2010 and 2014. Although turnover grew in absolute terms from $35.5 billion to $43.8 billion, when inflation was taken into account growth was only 0.1%. Although this is an improvement over the previous period when the industry contracted following the 2008 financial crisis, it does indicate the challenges facing the industry. However, the low nature of growth in real terms should not take away from the large size of the industry, turning over more than $43 billion a year. While the overall global picture indicates static real-terms growth, there are also some important regional variations. In particular, strong growth remains in key emerging markets in Africa, Asia-Pacific and the Midde-East. This reflects an increased focus among global brands towards developing economies, and in Africa in particular. In terms of the major markets of Europe and the USA, continuing challenging economic circumstances can certainly explain part of the decline in growth rates. More troubling for the marketing research industry could be a switch in spending patterns by companies that commission marketing research, from ‘traditional’ sources to just about any alternative source of information that could apply insight. The result of the decline in the industry and the shift to alternative sources of insight has generated a greater competitive intensity between marketing research suppliers, exacerbating the demand for a broader mix of managerial and technical skills from researchers. This is reflected in attempts by ESOMAR to draw a wider boundary around the marketing research sector by including expenditure on survey technology that is used internally within firms, such as Survey Monkey (www.surveymonkey.com) or Qualtrics (www.qualtrics.com). How marketing research expenditure is spent on different research methods is illustrated in Table 1.4. Quantitative research methods account for 73% of global research spend, with qualitative accounting for 16%. The remaining 11% includes desk and secondary research. This table makes distinctions between different forms of online research – for instance, highlighting online qualitative research, where there are many examples of companies specialising in online focus groups, in-depth interviews and ethnography. (These examples will be discussed in Chapters 6 to 9.) One long-term trend that can be observed is that the use of qualitative techniques and secondary data sources (captured in ‘other’) has steadily increased over time while quantitative research has declined. Despite these trends in terms of expenditure, quantitative methods remain dominant. The leading research firms on a global basis are highlighted in Table 1.5. Some names you may be familiar with while others may operate through a sub-brand in your market. What is key to note here is the extent to which a relatively small group of firms count for a large share of the market.

Chapter 1 Introduction to marketing research

Table 1.4

Spend by research method for 2014

Quantitative research Online Automated digital/electronic Telephone Face-to-face Other quantitative (e.g. syndicated services) Mobile/smartphone Postal Online traffic/audience

23% 21% 9% 8% 5% 3% 2% 2%

Qualitative research Group discussions Online qualitative In-depth interviews Other qualitative Other

Table 1.5

Market share of top six companies (2014)

The Nielson Company Kantar IMS Health Inc. Ipsos Gartner GfK Rest of the market

External suppliers Outside marketing research companies hired to supply marketing research services.

Full-service suppliers Companies that offer the entire range of marketing research services.

11% 3% 2% 1% 11%

14% 8% 6% 5% 5% 4% 58%

The bases for the estimates in Tables 1.2 to 1.5 are derived from external marketing research suppliers or agencies. External suppliers are outside firms hired to supply research data. These external suppliers collectively comprise the ‘marketing research industry’. They range from small (one or a few persons) operations to very large global corporations. We now examine the nature of services that may be supplied by external suppliers. As illustrated in Figure 1.5, external suppliers can be classified as full-service or limitedservice suppliers. Full-service suppliers offer the entire range of marketing research services: for example, defining a problem, developing a research design, conducting focus group interviews, designing questionnaires, sampling, collecting, analysing and interpreting data and presenting reports. They may also address the marketing implications of the information they present, i.e. have the management skills to interpret and communicate the impact of their research findings at the highest levels. They may also manage customer database analyses, being able to integrate the management and analyses databases with the management and analyses of conventional marketing research techniques. The services provided by these suppliers can be further broken down into syndicated services, standardised services and customised services (see Figure 1.5). Examples of these companies include Kantar (www.kantar.com) and Ipsos (www.ipsos.com).

Marketing Research

Figure 1.5

Marketing research suppliers

Research suppliers

Internal

External

Full-service

Syndicated services

Field services

Customised services

Analytical services

Coding and dataentry services

Syndicated services Companies that collect information of known commercial value that they provide to multiple clients on a subscription basis.

Customised services Companies that offer a variety of marketingresearch services specifically designed to suit a client’s particular needs. Each marketing-research project is treated uniquely.

Online services Companies that offer a combination or variety of secondary data and intelligence gathering, survey or qualitative interviewing, social media engagement and the analysis and publication of research findings, exclusively online.

Market research reports and advisory service

Online services

Panel providers

Brandedproducts services

Limited-service

Online community providers

Software providers

Online focus groups and streaming

Reporting

Syndicated services collect information of known commercial value that they provide to multiple clients on a subscription basis. Surveys, diary panels, scanners and audits are the main means by which these data are collected. Examples of these companies include Nielsen (www.nielsen.com) and GfK (www.gfk.com). Customised services offer a variety of marketing research services specifically designed to suit a client’s particular needs. Each marketing research project is treated uniquely. An example of such companies is TNS (www.tnsglobal.com). Online services offer a combination or variety of secondary data and intelligence gathering, survey or qualitative interviewing, social media engagement and the analysis and publication of research findings, exclusively online. Examples of these companies include YouGov (www.yougov.com) and OnePoll (www.onepoll.com). Market research reports and advisory services provide off-the-shelf reports as well as data and briefs on a range of markets, consumer types and issues; as such, they are thought of as part of the broader information market and not necessarily part of the traditional marketing research industry. Examples include Euromonitor (www.euromonitor. com) and Mintel (www.mintel.com). Limited-service suppliers specialise in one or a few phases of a marketing research project. Services offered by such suppliers are classified as field services, coding and data entry, analytical services, branded products, viewing facilities, panel providers, software providers, web analytics, online community providers, online focus groups and streaming and reporting.

Chapter 1 Introduction to marketing research Market research reports and advisory services Companies that provide off-the-shelf reports as well as data and briefs on a range of markets, consumer types and issues.

Limited-service suppliers Companies that specialise in one or a few phases of a marketing-research project.

Field services Companies that collect data through postal surveys, face-to-face interviews, telephone interviews and the internet.

Coding and dataentry services Companies that offer such services as editing completed questionnaires, developing a coding scheme and transcribing the data for input into a computer.

Analytical services Companies that provide such services as designing and pre-testing questionnaires, determining the best means of collecting data and designing sampling plans.

Branded marketingresearch products and services Companies that offer specialised data collection and analysis procedures developed to address specific types of marketingresearch problems. These procedures can be patented, given brand names and marketed like any other branded product.

Field services collect data through postal surveys, face-to-face interviews, telephone interviews and the internet. Firms that specialise in interviewing are called field-service organisations. These organisations may range from small proprietary companies that operate locally to large multinationals. Some organisations maintain extensive interviewing facilities across the country for interviewing shoppers. Many offer qualitative data collection services, such as focus group interviewing (discussed in detail in Chapter 7). Examples of these companies include LightspeedGMI (part of WPP) (www.lightspeedgmi.com) and Indiefield (www.indiefield.co.uk). Coding and data-entry services include editing completed questionnaires, developing a coding scheme and transcribing the data for input into a computer. Analytical services include designing and pre-testing questionnaires, determining the best means of collecting data and designing sampling plans, as well as other aspects of the research design. Some complex marketing research projects require knowledge of sophisticated procedures, including specialised experimental designs (discussed in Chapter 10) and analytical techniques such as conjoint analysis and multidimensional scaling (discussed in Chapter 26). This kind of expertise can be obtained from firms and consultants specialising in analytical services. Examples of these companies include Cobalt Sky Ltd (www.cobaltsky.com) and Digitab (www.digitab.uk.com). Branded marketing-research products and services are specialised data collection and analysis procedures developed to address specific types of marketing research problems. These procedures may be patented, given brand names and marketed like any other branded product. An example of such a company is Millward Brown’s Vermeer (mbvermeer.com). Panel providers offer researchers the opportunity to access consumer, b2b and specialist panels of participants, alongside scripting and hosting surveys. Examples of these companies include e-Rewards (www.e-rewards.com) and Toluna (www.toluna.com). Software providers offer software packages that create platforms to script, host and analyse surveys, or software as a service (SaaS) options. Examples of these companies include Qualtrics (www.qualtrics.com) and Surveymonkey (www.surveymonkey.com). Online community providers build online research communities where researchers can employ a wide variety of quantitative and qualitative techniques to connect to consumers. Examples of these companies include Cspace (www.cspace.com) and FreshMinds (www. freshminds.net). Online focus groups and streaming provide platforms for running online focus groups and streaming the results. An example is FocusVision (www.focusvision.com). Reporting offers research companies reporting solutions that seek to engage clients in oral and electronic presentations beyond conventional reporting methods such as hard-copy reports and PowerPoint. They utilise specialist art and graphic-design services to create static data presentation formats and data dashboards that can be interrogated.

Justifying the investment in marketing research Panel providers Companies that offer researchers the opportunity to access consumer, b2b and specialist panels of participants, alongside scripting and hosting surveys.

Software providers Companies that provide software packages that create platforms to script, host and analyse surveys, or software as a service (SaaS) options.

The 2015 ‘ESOMAR Global Market Research’ report highlights many of the pressures that the marketing research industry is facing. One of the key weaknesses the report highlights is the need to raise the perceived value of research among decision makers outside the research sector.16 This is not a recent phenomenon; it is a challenge that the marketing research industry has faced from its inception and that has become more prevalent in recent times: the price of consumer data is trending downwards and parts of market research are becoming commoditised. This is in part driven by aggressive procurement pro cesses, growing expectations for demonstrable return on investment and increas ing macro-economic pressure. ‘Consumer data’ is now more abundant and automated.17

Marketing Research

Online community providers Companies that build online research communities where researchers can employ a wide variety of quantitative and qualitative techniques to connect to consumers.

Online focus groups and streaming Companies that provide platforms for running online focus groups and streaming the results.

Reporting Companies that offer research companies reporting solutions that seek to engage clients in oral and electronic presentations beyond conventional reporting methods such as hard-copy reports and PowerPoint.

Return on investment in marketing research spend will continue to be a factor that all practising researchers will need to address. It must be recognised that if decision makers make use of marketing researchers, even if the best theories and practice of the marketing research process are followed ‘to the letter’, there is no guarantee that a marketing decision supported by research will be successful. The act of decision making and conducting marketing research are distinctive activities and there are examples where the vital link between these activities has resulted in failure. If decision makers have gaps in their knowledge, if they perceive risk and uncertainty in their decision making and cannot find support at hand within their organisation, they can gain support from marketing research. However, many decision makers can recount cases where the use of marketing research has resulted in failure or where decisions based upon gut feeling or intuition have proved to be successful. Such cases present a challenge to researchers, especially in light of the competition faced by the industry from alternative data sources.18 Reflecting upon such cases should remind researchers to maintain a focus of offering real and valuable support to decision makers. Understanding what real and valuable support means should underpin the whole array of creative data collection and analysis procedures available to the researcher. Another view to reflect upon is the damning comment from the late Anita Roddick, founder of The Body Shop, who said that ‘market research is like looking in the rear view mirror of a speeding car’.19 This may be a valid point if one sees the relationship of marketing and marketing research from the perspective illustrated by the respected research practitioner, Wendy Gordon: Traditional marketers delegate responsibility to the processes of marketing research. They believe that you can ask people what they want and need in the future and then deliver it to them. It is a fallacy. Marketing research removes peo ple from experiencing reality, where the signs of change bubble up in unexpected places. Sitting in comfort behind a one-way mirror, listening to a debrief from researchers describing the world ‘out there’ or reading statistical reports on mar kets and the ‘aggregate consumer’ is not real, it is sanitised and second-hand.20 Given the above criticisms, it is a fair point to acknowledge that there are cases where the use of marketing research has resulted in poor decision making, or even failure. Ultimately, this examination should lead to a stronger justification of what ensures strong and valuable marketing research support. It may be a painful path to tread, but this journey has to be made! There are two areas of misconception of the role of marketing research that are still relevant today:21 Marketing research does not make decisions. The role of marketing research is not to make decisions. Rather, research replaces hunches, impressions or a total lack of knowledge with information that can be trusted. Marketing research does not guarantee success. Research, at best, can improve the odds of making a correct decision. Anyone who expects to eliminate the possi bility of failure by doing research is both unrealistic and likely to be disappointed. The real value of research can be seen over a long period where increasing the percentage of good decisions should be manifested in improved bottom-line perfor mance and in the occasional revelation that arises from research. The last point shows the long-term benefits of conducting marketing research, i.e. that the results of a study may help decision makers with an immediate problem, but by building their knowledge they can also have long-term benefits. The following example illustrates how marketing research could be used in new-product development. In an echo of some of the sentiments shared by Steve Jobs earlier in this chapter, the designer and entrepreneur chose to ignore the findings, and ultimately achieved immense levels of success. This is not always the case, as many different designers embrace marketing-research techniques to support their design thinking and practice to great effect.

Chapter 1 Introduction to marketing research

Real research

Doing a Dyson22 Just 23 months after its launch in the UK, the Dyson bagless vacuum cleaner became the country’s best seller, overtaking sales of Hoover, Electrolux, Panasonic, Miele and all other vacuum cleaners. The Dyson’s clear bin was given a resounding thumbs-down in marketing research. People said they did not like the dirt being visible in the bin in case their neighbours saw how much dirt had been picked up in their homes. Some retailers said they would not want to have dust on display in demonstration machines. Yet, the dust was there because they began using Dyson display machines to clean their shops. Dyson felt compelled to launch its vacuum cleaner with a clear bin, believing that it was important to see when it was full. Moreover, what better way was there to show stockists, sales staff and customers proof of its increased efficiency than to see the dirt being collected? How would consumers react to a new vacuum cleaner with totally radical styling, revolutionary internal engineering and a price tag almost twice that of the current brand leader? The response proved immediately that innovative products do sell, even at a premium price. However, marketing research did not point to this product having the potential to be a success. James Dyson argued that ‘marketing research will only tell you what has happened. No research can tell you what is going to happen’. This is a theme that James Dyson has reiterated over the years. In an interview in 2006, giving tips to would-be inventors and entrepreneurs, he said: You can’t go out and do marketing research to try and solve these problems about what to do next because usually, or very often, you’re doing the opposite of what marketing research would tell you. You can’t base a new project two years ahead on current market trends and what users are thinking at the moment. That sounds very arrogant. But it isn’t arrogance. You can’t go and ask your customers to be your inventors. That’s your job.

Out of the array of research and information-support approaches, there is no one, guaranteed approach, research design or technique that can create the perfect means to support decision makers. If decision makers complain that research is misleading or is only telling them what they already know, the researcher may argue that the fault lies with managers who pose the wrong questions or problem in the first place. If one takes the narrow view that the decision maker poses the questions and the researcher finds the answers, there may be some validity in such an argument. It does not hold if one considers that the decision maker and the researcher have a joint commitment to solve problems. In this joint commitment they have quite distinct but complementary creative skills that they can bring together to understand what problem they should be researching, how they conduct the research and how they interpret their findings. Can researchers survive in an age of increasing competition from other information providers? Can they cope with the threats of growth of in-house research and new entrants to the industry that adopt new technologies and techniques, especially in the use of social media? Can the industry fend off the challenge from the armies of consultants, and avoid research being seen as a commodity?23 To achieve this, the industry has to offer marketers’ insights that have integrity and can be trusted, rather than just ‘robust’ data collection and analysis. Such insights should lead to fresh perspectives to business problems and/or a competitively advantaged solution.24 The researcher’s input must be seen to benefit the bottom line. Initiatives that bring marketers and researchers closer together are needed, initiatives that educate buyers that marketing research has as much, if not more, to offer than far more expensive consultancy firms.25

Marketing Research

The future – addressing the marketing research skills gap A key theme of this book relates to the emergence of new technologies and their impact upon marketing research. Billions of people now engage regularly in online discussions, giving their opinions, meeting new people, showing their activities, preferences, uses and attitudes, talking about brands, services, music and films. An idea of the scale of the potential impact of this does not come from Facebook’s announcement that it passed 1 billion regular users26, but from its internal target of having 5 billion users by 2030.27 Despite these numbers, the marketing research industry has been criticised for being slow to recognise that engagement with these new technologies is having a significant impact upon the nature, value and integrity of the work they undertake. That is not to say that marketing research has not responded to the growth in technology, and in later chapters we will look at the importance of mobile and social media research, together with the increasing use of online data collection tools. In marketing research, the early period of the internet – from the late 1990s onwards – was used as a digital extension of activities that could be done offline, taking the survey from face to face, then to telephone (with computer-assisted telephone interviewing, CATI) and then online with web surveys. It has been argued that ‘the survey’ has not really embraced the breadth and richness of digital developments, with many surveys conducted online being essentially online versions of surveys that were previously administered by interviewers face to face.28 Although there are some opportunities to include multimedia, such as video, audio or pictures, in essence it is still a survey. These attempts to engage participants are in response to evidence that shows completion rates of surveys are dropping as participants grow tired of overly long surveys.29 However, the continuing use of surveys may ignore a revolution in online behaviour where people are now expressing their opinions and feelings in far more sophisticated and complex ways. The following example of audio company Bose highlights how such online channels can be used in research.

Real research

Bose’s online community30 Bose (www.bose.com) is a high-end audio manufacturer, famous for its speakers and headphones. As a privately held company, worried about competitors finding out new product plans, it could only draw upon existing employees for insights. The company realised that gathering feedback from employees – most of whom got the product for free – was not giving it an understanding of how its actual customers fel. Working with C Space, a specialist in building online communities, Bose built an online community of around 400 people, including a mix of people who were existing customers and fans of the Bose brand and those who weren’t. Members of the community completed a number of activities each week, ranging from surveys to mobile ethnographies. The membership of the online community was frequently refreshed to ensure that it was representative of the most important customer segments. After running for 18 months, Bose identified a number of benefits that were created by the use of online communities. These included new product opportunities, improving its marketing messaging and a deeper understanding of how its customers view competitors.

Chapter 1 Introduction to marketing research

Within the marketing research community there has been some attempt to align the broader changes resulting from the growth of the internet. For example, in 2004 the term ‘Web 2.0’ entered common use to describe the growth in user-generated content being uploaded to websites and the increasingly participative nature of the Web. For example, the growth in social networks has happened through interaction between individuals rather than top-down control of content by the companies running websites. As the term Web 2.0 became increasingly established, people began to apply the 2.0 label to a wider range of activities, including law, architecture and even government. In the world of marketing research, the term ‘Research 2.0’ came into being in 2006, to reflect a shift away from the old ‘command and control’ paradigm of marketing research towards a more collaborative approach. The core of Research 2.0 was to move away from an assumption that the brand decision makers and the researcher knew everything, towards a three-way discussion between the brand, the researcher and the customer. Although early techniques tended to be passive techniques based around blogs, more active techniques are now the most significant area of interest in the area of online research communities, such as that used in the example of Bose.31 Traditional research techniques, such as focus groups and one-to-one interviews, while they still relate to younger audiences do not apply as readily as collaborative techniques, which are aligned more to conversation and empowering participants than to seeking specific responses. In isolation, face-to-face research with young people can deliver patchy results.32 The combination of Web and electronic media use and proficiency by youth audiences has forced marketing research to evolve and embrace mixed methodologies. By engaging with younger audiences in ‘youth-friendly’ media, the quality and range of insight returned has risen. In contexts that are familiar, interactive, but not physically engaging, younger audiences come alive. Over time, the usage of the term Web 2.0 has declined sharply, and with it the term Research 2.0 has faded.33 This is not because the underlying concepts were unimportant, but it reflects that the development of internet technology is an ongoing process with impacts that differ depending on the time, place and context. The Web 2.0/Research 2.0 model implied an alternative world where everything had changed. Yet, in the case of research, new technology has often been used alongside existing techniques. Additionally, as the use and impact of technology has grown to near ubiquitous levels, the need to distinguish between ‘new’ and ‘old’ research has dissipated. That is not to say that there aren’t important issues raised by the growth in technology. Some key issues are:34 1 Trust. Ensuring that research buyers understand the basis of the advice they are given. Decision makers have been assured for over 70 years that the research is ‘true’ because it is based on a scientific approach to knowledge development, thus it will take a while for the new messages to be widely understood. 2 Theoretical base. At the moment, many new techniques are being used in a theoretical vacuum; thus researchers need to address this and rebuild a body of knowledge and theory that supports the techniques being used. 3 Ethical base. There are new privacy, security and safety issues. Social media has changed the rules on how ‘findable’ somebody is. This has enormous implications for privacy and safety. For example, including a literal quote from an online forum in a report is essentially the same thing as naming the individual, since a search on the quote will usually return information about the person making it. The discussion about ‘what is in the public domain’ and what can be used when, where and how has barely started, and will develop rapidly over the next few years. A newer issue that has emerged recently is the question of whether the marketing research industry is facing a skills gap.35 It has been suggested that one of the reasons that marketing research has found it difficult to adapt to change brought about by technology

Marketing Research

is the lack of appropriate technical skills among researchers. A worrying trend for marketing research is the identification that marketing researchers lack sufficient analytical skills to draw insights from the increasing volumes of data being generated through ‘big data’ technologies.36 These issues will be described, illustrated and debated throughout this text. While marketing research faces uncertainty and challenges, these challenges can be found across many industries. The corollary of these events can also be seen, in that the future of the marketing research industry is laden with great opportunities, and it is in this spirit that we also wish to portray the subject. There are many commercial and scholarly opportunities, but these will demand a different set of skills, thinking and outlook compared with the researcher of the past. The marketing research industry has great opportunities to add value to research. Researchers can move up the value chain to offer more advice and insight, thus improving their stature and ultimately their profitability. They can help decision makers to make sense of a variety of data sources rather than walking away from a project when the research is complete.37 Moving towards a business model that is driven by researchers offering actionable consumer insight means that researchers and the marketing research industry of the future will be required to:38 •

•

Think conceptually – by developing ‘conceptual’ thinkers, i.e. researchers who feel comfortable working with higher-order business concepts and talking the language of senior decision makers. These individuals must understand the relationship between information and key business concepts. They must go beyond their technical and skill-based knowledge and offer strategic and tactical advice for business advantage based on detailed consumer and market knowledge. Communicate in the way that those who commission research think – by knowing how to communicate in the way senior people think, i.e. researchers presenting findings as a compelling narrative, not as disparate blocks of information. Interpret findings in terms of the whole picture – by thinking holistically about ‘evidence’, i.e. researchers with the skills to work in a ‘holistic’ way with all available customer evidence, recognising the need to interpret often imperfect marketing information. They must draw knowledge from a host of different sources including qualitative and quantitative techniques, a variety of forms of observation, customer relationship management systems and financial and customer-profile information. These individuals will have to draw heavily upon the use of analytical models that represent the way customers think and behave. Integrate findings with others that support marketing decision makers – by working in a multidisciplinary way with related marketing-services companies, with researchers working alongside branding and design and other marketing specialisms to gain a wider market understanding. This makes sure that everything is tailored to business solutions and is not just the result of rigid prescriptive research designs. This bottom-up, multidisciplinary approach provides flexibility and differentiates ‘strategic marketing intelligence’ from the ‘top-down’ approach of full-blown management consultants. This will also mean the cultivating of a more creative environment, with a more ‘hands-off’ management style rather than a prescriptive techniques-driven approach.

Finally, in a note of optimism, it is worth reflecting upon the views of three new graduates arguing what makes marketing research a great career choice. They worked for the research company Ipsos (www.ipsos.com) and were presenting their views to professional researchers at the Annual Conference of the Market Research Society:39 1 Variety. This can apply to the kind of work and the projects one experiences, the sectors one can specialise in, the people and the teams one will work with depending on the project. Then, the actual day-to-day work is varied (be it data analysis one day, fieldwork the

Chapter 1 Introduction to marketing research

next, charting, etc.). Ad hoc research also has the benefit of offering a variety of projects that can last from a few weeks up to a year or more. 2 Career progression. Marketing research has many clearly defined roles across the industry. Not only is there clear career progression within a company, but there is also the option to move client side (or vice versa), do international research, relocate to another country (a key selling point for a global business), specialise in a particular sector or even move to other roles such as brand consulting. 3 Responsibility. Compared with other industries, marketing research can offer a large amount of responsibility from an early stage of a person’s career. Where graduates in some industries may still be doing photocopying and other mundane administrative tasks, those working in marketing research may be at a stage where they are managing large international projects. 4 Intellectual eclecticism. Marketing research is open to graduates from all disciplines; all subject disciplines are applicable as there are a variety of roles and the nature of work can demand skills from all subject areas. 5 Working environment. Marketing research has some of the most intelligent, interesting, fun and inspiring people, and that makes it a great place in which to work and develop. The culture (particularly agency side) is relaxed and friendly with a mix of personalities and characters. It is not until you actually work in marketing research that you realise this.

Summary

Marketing research provides support to marketing decision makers by helping to describe the nature and scope of customer groups, understand the nature of forces that shape the needs of customer groups and the marketer’s ability to satisfy those groups, test individual and interactive controllable marketing variables and monitor and reflect upon past successes and failures in marketing decisions. The overall purpose of marketing research is to assess information needs and provide the relevant information in a systematic and objective manner to improve marketing decision making. The marketing research process consists of six broad steps that must be followed creatively and systematically. The process involves problem definition, research approach development, research design formulation, fieldwork or data collection, data integrity and analysis and report preparation and presentation. Within these six broad steps are many iterations and routes that can be taken, reflecting the reality of marketing research in practice. Marketing research may be classified into problem-identification research and problem-solving research. In general terms, problem identification uncovers the potential that may be exploited in markets, problem solving uncovers the means to realise that potential. The major developed economies, especially in Europe and the USA, are the biggest users of marketing research on a per capita and total expenditure basis. However, in recent years growth of the sector has slowed – and in some years fallen. Commentators have debated whether this fall can be attributed solely to the global economic factors or trends within market research itself. Alternative explanations have focused upon the development in technology, such as social media usage and the growth of big data. New ways of engaging and collaborating with consumers are being generated that challenge many of the principles upon which ‘traditional marketing research’ has been built. Marketing research may be conducted internally (by internal suppliers) or may be purchased from external suppliers. Full-service suppliers provide the entire range of marketing research services, from problem definition to report preparation and presentation. They may also manage customer database analyses and social media research, being able to integrate the management and analyses databases with the

Marketing Research

management and analyses of conventional marketing-research techniques. Limitedservice suppliers specialise in one or a few phases of the marketing-research project. Marketing research is not a panacea for all marketing problems. There are examples where marketing research has not adequately supported decision makers. The Steve Jobs quote used at the beginning of this chapter has become popular because many managers have experienced disappointment at the performance of marketing research. However, many of the problems that arise from poor marketing research derive from poor communications between decision makers and researchers. In order to resolve these problems, there are growing demands upon the marketing research industry to produce research findings that are more actionable and relevant to marketing decision makers. As well as having the technical skills to conduct research in a professional and ethical manner, researchers are increasingly expected to have the ability to interpret their findings in a manner that is relevant to decision makers.

Questions

Exercises

1 Describe the purpose of marketing research. 2 What kinds of decisions are made by marketing managers? How does marketing research help in supporting these decisions? 3 What do you see as the major challenges for researchers that emerge from the ESOMAR definition of marketing research? 4 How may the effective problem-identification research enhance the practice of problem-solving research? 5 What challenges exist in trying to quantify the size and growth of the marketing research industry on a global basis? 6 Explain one way to classify marketing research suppliers and services. 7 Describe the steps in the marketing-research process. 8 Explain why there may be the need for iterations between stages of the marketing-research process. 9 What arguments can be used by sceptics of marketing research? 10 What kinds of new skills are increasingly being demanded from researchers? 11 What arguments would you use to make the case for greater investment in marketing research? 12 Summarise the nature of threats and opportunities that social media offer the researcher.

1 Visit the website of TNS (www.tnsglobal.com). Examine the nature of the research services the firm offers and consider how you see them fitting together. 2 Visit the website of the Market Research Society (www.mrs.org.uk). Work through the range of publications and support it gives to its members. Specifically visit the published code of conduct. Compare the MRS code of conduct with that available on the ESOMAR website (www.esomar.org). Are there any differences in their respective approaches to maintaining professional standards in the marketing research industry?

Chapter 1 Introduction to marketing research

3 From national or international newspapers, track down stories of successful entrepreneurial ventures. Evaluate the extent to which marketing research is attributed to their success and/or an awareness of their market(s). 4 In a small group discuss the following issue: ‘What is the ideal educational background for someone seeking a career in marketing research?’. 5 Re-read the quote from Steve Jobs earlier in this chapter. Using the internet, identify other business leaders who have made comments around the effectiveness of market research, positive or negative. Examine their statements and consider the extent to which you agree with them.

Notes 1. ‘TfL – Next stop, cultural change’, MRS Awards: Winner, December 2015 2. Isaacson, W., Steve Jobs (London: Little Brown 2011), 72. 3. ‘Turns out Apple conducts market research after all’, http://blogs.wsj.com/digits/2012/07/26/turns-out-appleconducts-market-research-after-all/, accessed 4 May 2016. 4. Dekkers, S. and Lawrence, G., ‘easyJet community – using online communities to co-create the future’, ESOMAR Panel Research, Dublin (October 2008). 5. ‘Europe by easyJet’, Marketing Society UK: Excellence Awards, Grand Prix, 2014. 6. ‘How easyJet used data to cut spend and boost its brand: A view from Thinkbox’s Blind Data event’, Event Reports: Thinkbox: Blind Data, November 2013. 7. Macer, T., ‘Technology futures: perspectives on how technology will transform the market research of tomorrow’, Market Research Society Conference (2009). 8. Bank, P.F., The Roman Bazaar. A Comparative Study of Trade and Markets in a Tributary Empire’ (Cambridge: Cambridge University Press, 2008). 9. Lockley, L., ‘Notes on the history of marketing research’, Journal of Marketing, 14 (1950) (5), 733–6. 10. Blankenship, A., ‘Needed: A broader concept of marketing research’ Journal of Marketing, 13 (1949) (3) 305. 11. ESOMAR, ‘Market Research Explained’, https://www. esomar.org/knowledge-and-standards/market-researchexplained.php, accessed 4 May 2016. 12. ‘AMA Definition of Marketing’, https://www.ama.org/ AboutAMA/Pages/Definition-of-Marketing.aspx, accessed 4 May 2016. 13. Renkema, R. and Zwikker, C., ‘Development of a new brand concept’, ESOMAR Consumer Insights Conference (March 2003). 14. Boal, K., ‘Kellogg rolls out new cereal and snacking options’, Bakery & Snacks (12 February, 2007); Anon., ‘Kellogg’s Crunchy Nuts gets ready for adult breakfast’, The Grocer 224 (7524) (6 October, 2001), 53 and www.kelloggs.com. 15. ESOMAR, ‘Global Market Research’, ESOMAR Industry Report (2015). 16. ESOMAR, ‘Global Market Research’, ESOMAR Industry Report (2010), 44.

17. Woodnutt, T. and Owen, R., ‘The research industry needs to embrace radical change in order to thrive and survive in the digital era’, Market Research Society, Annual Conference (2010). 18. ESOMAR, ‘Global Market Research’, ESOMAR Industry Report (2015), 3. 19. Lury, G., ‘Market research cannot cover for the “vision thing”’, Marketing (9 November 2000), 34. 20. Gordon, W., ‘Be creative to innovate’, Research (January 2000), 23. 21. Lehmann, D.R., Market Research and Analysis, 3rd edn (Homewood, IL: Irwin, 1994), 14. 22. Muranka, T. and Rootes, N., Doing a Dyson (Dyson Appliances, 1996), 22; Mesure, S., ‘A day in the life of James Dyson’, Independent (27 May 2006), 55. 23. ESOMAR, ‘Global Market Research’, ESOMAR Industry Report (2015), 48. 24. Srivatsa, A., Puri, A. and Raj, S., ‘The case of the elusive insight: lessons from the greatest researcher of them all’, Consumer Insights Conference, Milan (May 2005). 25. Chelliah, J. and Davis, D., ‘But do you like your (expensive management) consultant?’, Journal of Business Strategy 31 (2) (2010), 34–42. 26. BBC News, ‘Facebook has a billion users in a single day, says Mark Zuckerberg’, http://www.bbc.co.uk/news/ world-us-canada-34082393, accessed 28 August 2015. 27. USA Today, ‘Facebook in 2030? 5 billion users, says Zuck’, http://www.usatoday.com/story/tech/ news/2016/02/04/facebook-2030-5-billion-users-sayszuck/79786688/, accessed 4 February 2016. 28. ESOMAR, ‘Global Market Research’, ESOMAR Industry Report (2015). 29. ESOMAR, ‘Global Market Research’, ESOMAR Industry Report (2015). 30. Whiteside, S., ‘Bose learns to listen to customers’, Event Reports: The Market Research Event (November 2015). 31. Poynter, R., Cierpicki, S., Cape, P., Lewis, A. and Vieira, S., ‘What does research 2.0 mean to consumers in Asia Pacific?’, ESOMAR, Asia Pacific, Beijing (April 2009). 32. Antilli, L. and Vishney, A., ‘Digital media and technology in youth audience research’, Admap Magazine, Issue 498 (October 2008).

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33. Discover, ‘The Decline of Web 2.0’ (March 2011), http:// blogs.discovermagazine.com/gnxp/2011/03/the-declineof-web-2-0/, accessed 4 May 2016. 34. Poynter, R., ‘A taxonomy of new MR’, Market Research Society, Annual Conference (2010). 35. Nunan, D., ‘Addressing the market research skills gap’, International Journal of Market Research 57 (2) (2015) 177–8. 36. Lund, S., Manyika, J., Nyquist, S., Mendonca, S. and Ramaswamy, S., ‘Game changers: Five opportunities for US growth and renewal’, McKinsey Global Institute Report (2013). 37. Chelliah, J. and Davis, D., ‘But do you like your (expensive management) consultant?’, Journal of Business Strategy 31 (2) (2010), 34–42; Keegan, S.,

‘“Emergent inquiry”: a practitioner’s reflections on the development of qualitative research’, Qualitative Market Research: An International Journal 12 (2) (2009), 234–48; Florin, D., Callen, B., Pratzel, M. and Kropp, J., ‘Harnessing the power of consumer insight’, Journal of Product & Brand Management 16 (2) (2007), 76–81. 38. Gordon, W., Ratcliff, M., Wynberg, R., Edwards, P., Helyar, R., Simmons, S., Fryer, S., Taylor, R. and O’Brien, Y., ‘The future of research’, Admap, July/August (2010), 18–23; Van Hamersveld, M. and Smith, D., ‘From data collection to decision support (3)’, Research World (December 2003), 20. 39. Radbourne, V., Boneham, D. and Muttiallu, J., ‘“When I grow up I want to be…”: attracting, developing and retaining graduate talent’, Market Research Society, Annual Conference (2008).

2 Stage 1

Problem definition

Stage 2 Research approach developed

Stage 3 Research design developed

Stage 4 Fieldwork or data collection

Stage 5 Data integrity and analysis

Stage 6 Communicating research findings

Defining the marketing research problem and developing a research approach The accurate identification of research problems cannot be compromised. Regardless of how well subsequent stages are conducted, the whole process may be worthless if problem identification is incorrect.

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Objectives After reading this chapter, you should be able to: 1 understand the importance of, and the process used in, defining marketing research problems; 2 describe the tasks involved in problem definition; 3 discuss in detail the nature and various components of a research brief and a research proposal; 4 discuss the environmental factors affecting the definition of the research problem; 5 clarify the distinction between the marketing decision problem and the marketing research problem; 6 explain the structure of a well-defined marketing research problem, including the broad statement and the specific components; 7 understand the role of theory in the development and execution of applied marketing research; 8 acquire an appreciation of the complexity involved in defining the problem and developing a research approach in international marketing research.

Overview This chapter covers the first two of the six steps of the marketing research process (described in Chapter 1): defining the marketing research problem and developing a research approach to tackle the problem. Defining the problem is the most important step, since only when a problem has been clearly and accurately identified can a research project be properly conducted. Regardless of how well a research plan is designed and subsequent stages are carried out, if the problem is not correctly diagnosed, research findings could be misleading or even dangerous. In this chapter, we allow the reader to appreciate the complexities involved in defining a problem, by identifying the factors to be considered and the tasks involved. In practical terms, the means to communicate and facilitate the diagnosis of research problems is achieved through the preparation of a research brief and research proposal. The rationale and components of the research brief and research proposal are presented. We provide guidelines for appropriately defining the marketing research problem and avoiding common types of errors. The client–researcher relationship is described with seven Cs (communication, cooperation, confidence, candour, closeness, continuity and creativity), presented to nurture a trusting and effective relationship. We also discuss in detail the characteristics or factors influencing the research design and components of an approach to the problem: objective/theoretical framework, analytical models, research questions and hypotheses. We introduce our discussion with an example of how Walmart’s UK subsidiary, Asda, structured a market research project to successfully address the problem of ensuring that research insights made their way across the organisation.

Real research

Breaking down silos at Asda1 Asda is the UK brand of American retail giant Walmart, known for its large-format stores. It operates in one of the world’s most competitive grocery markets. Additionally, it faces the challenges of consumers shifting to online purchasing, the growth in ‘click and collect’ services and the growth of smaller-format stores. Working with full-service market research agency Trinity McQueen (www.trinitymcqueen.com), Asda sought to address the following marketing research problem:

Chapter 2 Defining the marketing research problem and developing a research approach

How can organisation silos be broken down to ensure that research insights reach across the organisation? This is important because the behaviour of individual categories, on their own, can cause wider problems if they are not joined up with the corporate views of ‘head office’. For example, a reduction in prices in one category might damage a message of quality in an adjacent category. This research problem was addressed via a range of approaches, including both primary and secondary research in a process labelled ‘Category Deep Dive’. Primary research included shopper interviewers (in-home, accompanied during the shopping process and when exiting store), observational in-store research, surveys and eye-tracking interviews during shopping. Secondary data included both internal data (e.g. sales data) and data from external marketing research providers. The findings were effective not because of the range of methods used, but by the focus on ensuring that insights were actionable within the realities of organisational life. For example, this research approach ensured that: 1 Actionable insights are simple and clear. For example, they are often presented in a visual format. 2 Research is matched to the planning cycle and done at a point where research insights can be effectively actioned. 3 To break through silos a cross-functional group is involved from different departments, and the project can not get underway without sponsorship from senior management.

Importance of defining the problem

Problem definition A broad statement of the general problem and identification of the specific components of the marketing research problem.

Although each step in a marketing research project is important, problem definition is the most important step. For the purpose of marketing research, problems and opportunities are treated interchangeably (as mentioned in Chapter 1). Problem definition involves stating the general problem and identifying the specific components of the marketing research problem. Only when the marketing research problem has been clearly defined can research be designed and conducted properly: Of all the tasks in a marketing research project, none is more vital to the ultimate fulfilment of a client’s needs than an accurate and adequate definition of the research problem. All the effort, time, and money spent from this point on will be wasted if the problem is misunderstood and ill-defined.2 An analogy to this is the medical doctor prescribing treatment after a cursory examination of a patient – the medicine may be even more dangerous than the condition it is supposed to cure! The truly serious mistakes are made not as a result of wrong answers but because of asking the wrong questions. This point is worth remembering, because inadequate problem definition is a leading cause of failure of marketing research projects. Further, better communication and more involvement in problem definition are the most frequently mentioned ways of improving the usefulness of research. The importance of clearly identifying and defining the research problem cannot be overstated. The foundation of defining a research problem is the communication that develops between marketing decision makers and researchers. In some form or another, marketing decision makers must communicate what they see as being the problems they face and what

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research support they need. This communication usually comes in the form of a research brief. The researcher responds to the research brief with a research proposal, which encapsulates the researcher’s vision of a practical solution to the set research problem. The following example illustrates that a research brief may not always be particularly well thought out. The researcher is expected to develop the brief into a research proposal and, in doing so, has a vital role to play in the diagnosis of research problems.

How to bait the interview hook for those top 1,000 big fish3

Real research

The groans from researchers when another brief arrives asking for 100 or 200 interviews with chief executive officers (CEOs) or equivalents within large companies typifies the attitude generated by business-to-business marketers’ constant demand to reach this audience. When the research brief arrives, it is certainly worth examining whether, practically, what is requested can actually be done. The research proposal developed must reflect the practicalities of questioning managers who are constantly bombarded with requests to respond to research questions. The number of interviews, the timescale, the nature of questions and the structure of the sample all need to be taken into account. For example, is it really worth undertaking just 200 interviews within any single E uropean country? If we were limited to one per organisation, we would be interviewing to strike rates of between 1 in 2.5 and 1 in 5. If the research targets companies throughout Europe, individual countries such as the UK and France may have few large companies compared with the USA, while Italy has a small number of very large companies and a great many smaller ones. In actually reaching the target audience, a number of issues need to be taken into account. International business-to-business research with senior business audiences brings with it not only the particular difficulties of reaching them, but also the need to understand both country and cultural issues that impact on the research. Telephone interviews (even if possible) are considered inappropriate in many Far East and Middle East markets, especially South Korea and Japan. In Singapore and Hong Kong, the telephone is fine, provided the interviews are not too long (over 15 minutes).

The marketing research brief Research brief A document produced by the users of research findings or the buyers of a piece of marketing research. The brief is used to communicate the perceived requirements of a marketing research project.

The marketing research brief is a document produced by the users of research findings or the buyers of a piece of marketing research. The brief may be used to communicate the perceived requirements of a marketing research project to external agencies or internally within an organisation to marketing research professionals. It should act as the first step for decision makers to express the nature of a marketing and research problem, as they see it. This first step is vital in developing an agreement of an appropriate research approach. As a first step of problem diagnosis and negotiation, the marketing research brief should not be carved in tablets of stone! It has been argued that the greatest source of potential error in marketing research lies in the initial relationship between marketing decision makers and researchers.4 In developing a sound initial relationship, the research brief plays a vital role. Without some formal method of communicating the nature of a marketing problem, there is great potential for ambiguities, illogical actions (by both parties), misunderstandings and even forgetfulness. The purpose of a written marketing research brief may be summarised as follows: •

•

It makes the initiator of the brief more certain of how the information to be collected will support decision making. It ensures an amount of agreement or cohesion among all parties who may benefit from the research findings.

Chapter 2 Defining the marketing research problem and developing a research approach

• •

•

It helps both the marketer and the researcher to plan and implement the research design. It helps to reduce disputes that can occur when the gaps in decision makers’ knowledge are not ‘filled’ as intended. It can form the basis for negotiation with a variety of research organisations.

In all, the research brief saves resources in time and money by helping to ensure that the nature of the problem or opportunity under investigation has been thought through.

Components of the marketing research brief The rationale for a marketing research brief may seem logical, but actually generating a brief from marketing decision makers can be extremely difficult. These difficulties will be tackled later in this chapter. If a decision maker has a very clear idea of the nature of decision support needed and can define the research objectives that will create such support and define the research design that will fulfil the research objectives, then the decision maker can write a research brief that is highly structured. A structured brief created in these conditions would basically be a tender document, allowing a number of research suppliers to pitch for business on a like-for-like basis. Not all marketing decision makers have such clarity of the marketing research support they need. Even if they do, by sticking to highly structured and prescriptive marketing research briefs, they can underutilise the experience and creativity of researchers. This is illustrated by the following quote, based upon the experiences of a researcher who has seen many research problems misdiagnosed: When a client calls for a meeting on a research brief, quite often the tendency is for a methodology meeting: ‘I’d like to have a product test done on three new flavours that we have developed’. Off goes the researcher, conducts the test, identifies the winning flavour, the client launches it and finds to their dismay that it fails dismally. Why? It turns out the flavours were developed to try and revitalise an ageing product category and brand. In the product test, the familiar flavours orange and lemon won over the more exotic flavour to boost the category image. Had the researcher been allowed to look beyond the brief and ask one simple question on why the flavours were being made it may have led to a clearer brief, which in turn would have led to a research design which was more appropriately designed to cull out the real insight, which was that the consumers were bored and something rather more than flavour extensions were needed to revitalise the category.5 The following format for a research brief helps to make the most of the experience and creativity of both the marketing decision maker and the researcher, and has clear advantages for both parties. First, it does not demand that decision makers have a great deal of technical knowledge about research. Their focus can remain upon the gaps in their knowledge, the nature of support they need, not the technicalities of how data are to be collected and analysed. Second, it allows the researchers the opportunity to demonstrate their creative abilities and awareness of the latest research and analysis techniques. Using their experiences from problems faced by other decision makers, perhaps from a great variety of contexts and industries, researchers have the possibility of examining the marketing and research problem from many different perspectives. They can create, develop and adapt a research design to the research problem that supports the marketing decision maker within clear time and cost parameters (See Figure 2.1): 1 Background information. The background serves to put research objectives into context, helping the researcher to understand why certain research objectives are being pursued. Decision makers would detail what they see as being the main events that have caused or contributed to the problem under study. Such a background gives a framework for the researcher to investigate other potential events, contributory factors or causes.

Marketing Research

Figure 2.1 Background information

Components of the marketing research brief

Objectives (a) marketing (b) research

Target to research

Who is to use findings (a) analysis (b) format

Constraints

Administration

2 Objectives. The first part of this section would detail which marketing decisions are to be completed once the research has been undertaken. This requires decision makers toexplain what they see as the focus of the decisions they plan to make. They then go on to explain what gap(s) they see in their knowledge. Those gaps create the focus for planned research activities and set the research objectives. The formulation of the marketing objectives can encompass two areas: organisational objectives and personal objectives of the decision maker. For a research project to be successful, it must serve the objectives of the organisation and of the decision maker. For the researcher, this may not be explicit or obvious to discern. It may take some time working with a decision maker or a particular organisation to see potential conflicts in organisational and personal objectives. The problem faced by researchers is that decision makers may not formulate marketing objectives clearly. Rather, it is likely that objectives tend to be stated in terms that have no operational significance, such as ‘to improve corporate image’. Ultimately this does not matter, as this ‘first-step’ brief offers the opportunity for the researcher to draw out and develop a much clearer vision of marketing and research objectives. Drawing out and developing decision makers’ perspectives of objectives, even if they have no operational significance, helps the process of developing a common understanding of what the decision maker is trying to achieve. 3 Target to research. Any marketing research project will measure, understand or observe a target group of individuals. These may be distinct groups of consumers, channel members such as retailers or competitors, or company employees. In this section, details of the characteristics of the target group(s) can help in many research design decisions. These cover areas of identification, gaining access to conduct research, understanding which techniques are appropriate to measure or understand these individuals and the best environment or context in which to conduct research. 4 Who is to use the findings? This section would outline brief details of the decision makers who will use the research findings. For example, certain decision makers may be entrepreneurial and introspective, looking for short-term tactical advantages. Presenting research findings that make tactical advantages apparent would be the best way to communicate to such managers. Managers with a background and training in statistics may expect results to be analysed and presented in a particular manner to have any credibility.

Chapter 2 Defining the marketing research problem and developing a research approach

Other managers, e.g. those responsible for many product and/or communications design decisions, may not have such training or may even be distrustful of statistical analyses and seek a more qualitative interpretation. These issues have an impact upon the nature and extent of analysis conducted, upon the data collected and the style and format in which research findings will be presented. 5 Constraints. The main limitation to researchers carrying out what they may perceive as being the correct way to research a problem is the time and money that decision makers can afford. Proposing a large-scale project that would cost €200,000 when only €50,000 has been budgeted obviously will not meet management approval. In many instances, the scope of the marketing research problem may have to be reduced to accommodate budget constraints. With knowledge of time and cost constraints, the researcher can develop a research design to suit these needs. The researcher may also demonstrate other courses of action that could demand greater amounts of money or time, but could have clear benefits that the marketer may be unaware of. Other constraints, such as those imposed by the client firm’s personnel, organisational structure and culture or decision-making styles, should be identified to determine the scope of the research project. Yet, constraints should not be allowed to diminish the value of the research to the decision maker or to compromise the integrity of the research process. In instances where the resources are too limited to allow a project of sufficient quality, the firm should be advised not to undertake formal marketing research. In the following example, research undertaken by Nestlé in Poland shows how a research brief was developed that facilitated creative input from researchers, marketers and their communications agency. 6 Administrative considerations. These would lay out administrative details in completing the research project. Examples could be the expected delivery of interim reports, contacts in an organisation that may be able to help supply further information, or reference to sources of materials and individuals that are needed to complete the research successfully.

Real research

Can marketing research support effective communication ideas for children?6 The marketing team of the Ice Cream Division of Nestlé in Poland wished to brief its creative agency. It turned to the marketing research team to see what support it could give to develop strong communications with the target market of children. The researchers seized the opportunity to be part of the process of advertising development, rather than simply delivering data or consumer test results. They decided to try a new way of cross-functional team cooperation to the challenge, which started with the preparation of a research brief. Their short brief described: 1 Clear and straightforward project objectives, including details of the target group they would be addressing. In this particular case, the research objective was to reconstruct consumer insights, which help to build the most relevant and effective communication for children in the ice cream category in Poland. The core target group was children aged 6 to 11 years old. 2 Details of participant characteristics.

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3 A detailed plan of the project: What?

Who is responsible?

a Short brief with the objective b Prepare and conduct the training from Consumer Insight Process at Nestlé and how to talk with consumers c Prepare and conduct of the training for ‘consumer connection’ – what this is, how to talk toyour consumer and how to obtain knowledge inthe connection process d Meeting with consumers at their homes e Preparation of guide (how to talk to the consumers) f Affinity groups – just before their workshop – to put everyone in the ‘mood of consumers’ g Final workshop h Analyses: information about the product and consumer habits i Analyses: communications for children j Knowledge from the meetings with the consumers (pictures, toys, verbatims) k Reports; required at distinct stages throughout the whole project

Marketing team Marketing research team

Marketing research team and agency

Marketing research agency and everyone Marketing research team and marketing research agency Everyone Marketing research team and agency Marketing team Creative team Everyone Marketing research team

Three of the best ideas were tested in the research study; one was chosen, filmed and aired. The outcome was a success for the new business in Poland (Nestlé was a relatively new brand that did not really exist in consumers’ minds as it had taken over the Scholler brand). The marketing team increased awareness of the Nestlé brand and the BluMis brand (hero of the Nestlé children’s ice creams in Poland); the team sold much more than the operational plan and began building the image of the brands. This is an example of an action research approach (which will be discussed in more detail in Chapter 6).

With a formal marketing research brief and perhaps preliminary discussion with the organisation that is to commission the research, the researcher has the necessary material to develop a research proposal. In many instances, however, the researcher does not enjoy the luxury of a written research brief.7 The marketing decision maker may outline ideas in an oral manner, perhaps on an informal basis. This can happen if the decision maker is not aware of the personal benefits of producing a written research brief as detailed above. Decision makers may see the brief as a time-consuming process that really is the job of the researcher. If researchers are faced with an oral brief, they can use the proposed brief outline above as a guideline to the issues they should elicit in informal discussions in order to develop an effective proposal.

The marketing research proposal Research proposal The official layout of the planned marketing research activity.

In response to a research brief, the researcher will develop a research plan (covered in detail in Chapter 3) and will develop a research proposal to communicate this plan. The marketing research proposal contains the essence of the project and, in its final format, can serve as a contract between the researcher and decision makers.8 The research proposal covers all phases of the marketing research process. It allows the researcher to present an interpretation of the problems faced by management and to be creative in developing a research solution

Chapter 2 Defining the marketing research problem and developing a research approach

Figure 2.2 Executive summary

Components of the marketing research proposal

Background Problem definition Research objectives Research design Fieldwork/data collection Data analysis Reporting Cost and timetable Research organisation and researchers Appendices Agreement

that will effectively support decision makers. Although the format of a research proposal may vary considerably, most proposals address all the steps of the marketing research process and contain the elements shown in Figure 2.2: 1 Executive summary. The proposal should begin with a summary of the major points from each of the other sections, presenting an overview of the entire proposal. 2 Background. The researcher would be expected to have researched and developed ideas beyond those presented in the brief ‘background’. Other potential causes of the problems faced, or alternative interpretations of the factors that shape the background in an environmental context, should be presented. The extent of developmental work on the background to a research project will depend mostly upon how much past work researchers have done for the decision makers. In projects where researchers and decision makers are working together for the first time, much exploratory work may be undertaken by the researcher to understand an industry, organisation, decision makers, planned campaigns, etc. After a number of projects, much of this may be understood and not need restating. 3 Problem definition. Again, if necessary, the researcher may go beyond the problem definition presented in the brief. If the researcher sees potential to add value for the marketer through alternative diagnoses of the problem presented in the brief, then these should be shown. If the researcher sees a problem in the brief that is ambiguous or unattainable, other alternative diagnoses should be presented. From this section, the marketer’s gaps in knowledge should be apparent. 4 Research objectives. These may be presented in the form of clear hypotheses that may be tested. They may also cover broader areas in terms of ‘research questions’ that are to be explored rather than formally measured in a conclusive manner.

Marketing Research

5 Research design. The research design to be adopted, classified in broad terms as exploratory, descriptive or causal, should be specified. Beyond such a broad classification should be details of the individual techniques that will be adopted and how they will unfold and connect to each other. This means that the reader will clearly see methods of collecting the desired data, justification for these methods and a sampling plan to include details of sample size(s). This applies to both quantitative and qualitative approaches. 6 Fieldwork/data collection. The proposal should discuss how the data will be collected and who will collect them. If the fieldwork is to be subcontracted to another supplier, this should be stated. Control mechanisms to ensure the quality of data collected should be described. 7 Data analysis. This should describe the kind of data analysis that will be conducted, e.g. content analysis, simple cross-tabulations, univariate analysis or multivariate analysis. If software packages are to be used in these analyses, they should be specified, as they will be indicative of the potential analyses that can be conducted. There should be further description of the extent to which the results will be interpreted in light of the set marketing objectives, beyond the specified analysis techniques. 8 Reporting. The proposal should specify the nature of any intermediate reports to be presented, what will be the form of the final report and whether an oral presentation of the results will be made. 9 Cost and timetable. The cost of the project and a time schedule, broken down by phases, should be presented. A critical-path method chart might be included. In large projects, a payment schedule is also worked out in advance. 10 Research organisation and key researchers working on the project. When an organisation is working with researchers for the first time, some idea of past research projects and clients should be displayed. This can help the marketer to trust the researchers in problem diagnosis, research design and implementation (e.g. how credible the researchers may be seen to be by the individuals they are to research and how this may affect participant openness and honesty) and interpretation of the findings. 11 Appendices. Any statistical or other information of interest to only a few people should be contained in appendices. 12 Agreement. All parties concerned with fulfilling the research plan should sign and date their agreement to the proposal. Preparing a research proposal has several advantages. It ensures that the researcher and management agree about the nature of the project, and it helps sell the project to a wider array of decision makers, who may contribute to and benefit from the research findings. As preparation of the proposal entails planning, it helps the researcher conceptualise and execute the marketing research project. The following example illustrates a Coca-Cola European brand tracking study that required a major overhaul. This situation resulted in 400 research proposals being generated by marketing research agencies in 32 countries. Imagine the research, quality and creativity that went into the proposal that won the contract, not offering the cheapest option to Coca-Cola.

Real research

Coca-Cola’s Beverage Brand Barometer9 Coca-Cola’s Knowledge & Insights (K&I) marketing research team established a multicountry task force to consolidate its disparate brand trackers into a common framework to better understand consumers across the globe. The K&I task force launched the Beverage Brand Barometer (B3), feeling that having a consistent format would quickly pay its way. Coca-Cola’s K&I team reduced its global yearly research spend by 10%, while

Chapter 2 Defining the marketing research problem and developing a research approach

improving the quality of its insights. Two years after the launch, in the midst of a global economic and financial crisis, another Coca-Cola research task force was established, this time in Europe. Its aim was to review the brand tracker’s performance, and to validate consumer feedback on the experience of completing the B3 study in different European markets. The results of the review were conclusive: the B3 survey was too complex, extremely long and repetitive. This generated serious concerns over the quality of the data. In addition, structural changes within Coca-Cola Europe resulted in an increased need to benchmark, consolidate and cluster data across markets. With budget pressures and a tracking tool not delivering on business needs because of quality issues, the need for a shakeup was clear. In order to allow Coca-Cola Europe to improve its study, the B3 Global Council revisited the B3 core structure and significantly reduced all global mandatory sections, giving the Europe team the flexibility it needed. Because the study stretched across 32 European markets, consolidating all European B3 services with one marketing research supplier was identified as the best strategic and most feasible option. Working with a single partner on the revamped B3 across Europe would provide a new perspective, while allowing for productivity gains. The new study would improve quality by shortening the questionnaire, but it had also to generate savings for each individual market, while increasing the research supplier’s share of business. Five global agencies were briefed to put forward proposals for each individual market, as well as a potential pan-European package. However, the Coca-Cola project team also reviewed the local agency route to ensure fair local pricing, thus resulting in more than 400 proposals to be reviewed (i.e. five to seven agencies per market providing up to two proposals across 32 markets). Finally, Kantar (www.kantar.com) was chosen as the single strategic partner for Europe. Within Kantar, Millward Brown (www.millwardbrown.com) took the lead, with TNS (www.tnsglobal.com) playing a supporting role. Kantar was already well integrated into the Coca-Cola Company business via advertising testing and other tracking initiatives, and it presented a viable business case not only for the European central team but also for each individual market.

The process of defining the problem and developing a research approach By formally developing and exchanging a marketing research brief and research proposal, the marketing decision maker and the researcher utilise their distinctive skills. They ensure that the marketing problem and research problems have been correctly defined and an appropriate research approach is developed. The research brief and the research proposal are the formal documents that ensure each party is clear about the nature and scope of the research task. These documents allow decision makers and researchers formally to present their perspective of the task in hand. The nature of negotiations between decision makers and researchers may occur between a sponsoring client organisation, e.g. Coca-Cola, and a research agency, e.g. Kantar. It could also happen within an organisation, i.e. there may be an in-house marketing research team. In successfully diagnosing a marketing decision and marketing research problem, the access to, and the understanding of, decision makers by researchers can make a major difference. There are many positive reasons for using marketing research agencies, but it is worth noting that there has been a growth in the use of in-house marketing research, sometimes described in a derogatory manner as DIY (Do-It-Yourself) research.10 Where marketing research is practised without a full appreciation of the skills and creativity needed, or the limitations of particular techniques, much damage can be done. The growth in relatively cheap proprietary software to support DIY research has exacerbated concerns about the quality of some in-house marketing research. However, much in-house research is conducted by

Marketing Research

ell-qualified researchers, many of whom have worked at the best marketing research agenw cies. Such researchers can help diagnose research problems well and then outsource specific elements of data gathering and analysis to the many different types of research organisation that were detailed in Chapter 1. The following two examples illustrate how two major organisations have adopted ‘DIY research’.

Real research

Do-it-yourself research in Finland11 Like the country’s high-tech industries, research in Finland is expected to be increasingly driven by internet and software developments. One consequence, warns Research International’s (www.research-int.fi) managing director, Jukka Tolvanen, is that ‘many customers gather information themselves’. Juha Aalto, managing director of Taloustutkimus (www.taloustutkimus.fi/in_english/), goes further: ‘the increase in do-it-yourself research has been fast and furious’. At MTV, Research Manager, Taina Mecklin, has changing needs in an increasingly diffuse media industry. Although generally satisfied with services, she warns: ‘We already have the tools to conduct many projects ourselves. Agencies should think about how they can help us instead of wanting to keep the whole process to themselves.’ Public broadcaster YLE (www.yle.fi/fbc) also boasts its own research expertise. However, Head of Audience Research, Erja Ruohomaa, explains that she buys fieldwork to gain a ‘better understanding of the significance of our programming for all Finns’.

Real research

DIY research at Readers Digest12 Spurred on by technological, mostly web-based IT advancements, ‘do-it-yourself’ or DIY market research is growing. Not only does the online marketing of global brands cross international borders, but, most of all, web-based marketing research can be cost effective and fast. Additionally, as part of the growing importance of business intelligence departments and improved data management, it offers companies the bonus of keeping their information as close to the source as possible. One company where the DIY approach has played an integral role for a number of years is Readers Digest (www. readersdigest.co.uk). Apart from being a worldwide publisher of books, music and the magazine of the same name, Readers Digest also offers financial services. It supports all these products with a substantial amount of in-house research. This covers all the international markets in which Reader’s Digest operates. Additionally, the company executes an annual ‘European Trusted Brands’ survey in 14 European countries for its advertisers. Gavin Murray, strategy director, explains: Rather than being approached by a third party, our readership appreciates direct contact. We are in the unique position of being able to communicate directly with our customers and most of these customers are happy to participate in surveys sent out by us.

Whether marketing research is conducted by research agencies, in-house or a combination of these, the diagnosis and articulation of what should be researched is vital. The following section details the process that needs to be undertaken in order to produce research proposal documents. The detail of defining the nature of problems and developing an appropriate research approach to the point of creating a research design is shown in Figure 2.3.

Chapter 2 Defining the marketing research problem and developing a research approach

Figure 2.3 Environmental context of the problem – the tasks involved

The process of defining the problem and developing an approach

Discussions with decision makers

Secondary data evaluation

Interviews with experts

Marketing-decision problem to marketing-research problem Marketingdecision problem

Marketingresearch problem

Approach to the problem Objective theoretical framework

Analytical model

Research questions

Hypotheses

Research design Characteristics/factors influencing research design (Chapter 3)

Bear in mind, at this point, the challenges of gaining access to and understanding the demands of decision makers in this process. The tasks involved in problem definition consist of discussions with decision makers, qualitative interviews with industry experts and other knowledgeable individuals and analysis of readily available secondary data. These tasks help the researcher to understand the background of the problem by analysing the environmental context. Certain essential environmental factors bearing on the problem should be evaluated. An understanding of the environmental context facilitates the identification of the marketing decision problem. Then, the marketing decision problem is translated into a marketing research problem. Based on the definition of the marketing research problem, an approach to the problem is established and an appropriate research design is developed. The components of the approach may consist of an objective/theoretical framework, analytical models, research questions and hypotheses. Further explanation of the problem-definition process begins with a discussion of the tasks involved.

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Environmental context of the problem The tasks involved in understanding the environmental context of the marketing and research problem can include discussions with decision makers, qualitative interviews with industry experts, and secondary data collection and analysis. The purposes of these tasks are to develop an understanding of forces that may affect the nature of decision makers’ problems and related research problems.

Discussions with decision makers

Problem audit A comprehensive examination of a marketing problem to understand its origin and nature.

Discussions with the decision makers beyond the formal presentation of a research brief and research proposal are usually vital. The decision maker needs to understand the capabilities and limitations of research.13 Research provides information relevant to management decisions, but it cannot provide solutions, because solutions require managerial creativity and judgement. Conversely, the researcher needs to understand the nature of the decision that managers face – the marketing problem and what they hope to learn from the research. To identify the marketing problem, the researcher must possess considerable skill in interacting with the decision maker. Several factors may complicate this interaction. Access to decision makers may be difficult, and some organisations have complicated protocols for access to top executives. The organisational status of the researcher or the research department may make it difficult to reach the key decision maker in the early stages of the project. Finally, there may be more than one key decision maker, and meeting collectively or individually may be difficult. All of these problems make it difficult to develop a research brief. Despite these problems, though, it is necessary that the researcher attempts to interact directly with the key decision makers.14 A problem audit provides a useful framework to develop ideas from a brief, allowing the researcher to interact with the decision maker and identify the underlying causes of the problem. Like any other type of audit, it is a comprehensive examination of a marketing problem with the purpose of understanding its origin and nature.15 A problem audit involves discussions with the decision maker on the following issues: 1 The events that led to the decision that action is needed, or a brief history of the problem. 2 The corporate culture as it relates to decision making.16 For example, in some firms, the decision-making process is dominant; in others, the personality of the decision maker is more important. 3 The alternative courses of action available to the decision maker. The set of alternatives may be incomplete at this stage, and exploratory research may be needed to identify more innovative courses of action. 4 The criteria that will be used to evaluate the alternative courses of action. For example, new product offerings might be evaluated based on sales, market share, profitability, or return on investment. 5 What the decision maker perceives to be gaps in their knowledge. 6 The manner in which the decision maker will use each item of information in making the decision. It may be necessary to perform a problem audit, because the decision maker may have only a vague idea of what the problem is. For example, the decision maker may know that the firm is

Chapter 2 Defining the marketing research problem and developing a research approach

losing market share but may not know why; decision makers may tend to focus on symptoms rather than on causes. An inability to meet sales forecasts, a loss of market share and a decline in profits are all symptoms. The researcher should treat the underlying causes, not merely address the symptoms. For example, loss of market share may be caused by much better advertising campaigns by the competition, inadequate distribution of the company’s products, or any number of other factors. Only when the underlying causes are identified can the problem be successfully addressed. A problem audit, which involves extensive interaction between the decision maker and the researcher, can greatly facilitate problem definition by determining the underlying causes. The interaction between the researcher and the decision maker is facilitated when one or more people in the client organisation serve to liaise and form a team with the researcher. To be fruitful, the interaction between the decision maker and the researcher can be characterised by the following: 1 Communication. A free exchange of ideas between the decision maker and the researcher is essential. 2 Cooperation. Marketing research is a team project in which both parties (decision maker and researcher) must cooperate, from problem diagnosis through to the interpretation and presentation of findings. 3 Confidence. Mutual trust of each other’s distinct skills and contribution should underlie the interaction between the decision maker and the researcher. 4 Candour. There should not be any hidden agendas, and an attitude of openness should prevail. 5 Closeness. An understanding of each other’s problems should result in a closeness that should characterise the relationship between the decision maker and the researcher. 6 Continuity. The decision maker and the researcher must interact continually rather than sporadically. 7 Creativity. The interaction between the decision maker and the researcher should be creative rather than formulaic. Though the research process may be laid out in ‘easy-to-follow’ steps, in reality great amounts of creativity are needed at every stage.

Real research

Surf Superconcentrate faces a super washout in Japan Unilever attempted to break into the Japanese detergent market with Surf Superconcentrate. It initially achieved a 14.5% market share during test marketing but fell to a shocking 2.8% when the product was introduced nationally. Where did Unilever go wrong? Surf was designed to have a distinctive pre-measured packet, resembling teabaglike sachets, joined in pairs because convenience was an important attribute to Japanese consumers. It also had a ‘fresh smell’ appeal. Japanese consumers, however, noticed that the detergent did not dissolve in the wash, partly because of weather conditions and because of the popularity of low-agitation washing machines. Surf was not designed to work in the new washing machines. Unilever also found that the ‘fresh smell’ positioning of new Surf had little relevance since many consumers hang their washing out in the fresh air. The research approach was certainly not without flaw, as Unilever failed to identify critical attributes that are relevant in the Japanese detergent market. Furthermore, it identified factors such as ‘fresh smell’ that had no relevance in the Japanese context. Appropriate secondary data and business intelligence gathering

Marketing Research

and analysis, and even some exploratory qualitative research from the target market, could have revealed the correct characteristics or factors leading to a suitable research design. Despite having to withdraw from the Japanese market, Surf continued to perform well in several markets including India. By 2009 it was the third-biggest-selling product in the Indian washing detergent market behind Unilever’s Persil and Procter & Gamble’s Ariel.

Interviews with industry experts In addition to discussions with decision makers, qualitative interviews with industry experts who are individuals knowledgeable about the firm and the industry can help in diagnosing the nature of the marketing and research problem. 17 These experts may be found both inside and outside an organisation commissioning the research. Typically, expert information is obtained by unstructured interviews. It is helpful, however, to prepare a list of topics to be covered during the interview. The order in which these topics are covered and the questions to ask should not be predetermined. Instead, they should be decided as the interview progresses, which allows greater flexibility in capturing the insights of the experts (see C hapter8 for full details of in-depth interviewing techniques). The list of topics to cover and the type of expert sought should evolve as the researcher becomes more attuned to the nature of the marketing problem. The purpose of interviewing experts is to explore ideas make new connections between ideas and create new perspectives in defining the marketing research problem. If the technique works well by identifying an appropriate individual with the qualities to give insight into a particular topic, and an amount of trust and rapport is developed, the potential to generate and test ideas can be immense. Experts may have other contacts that the researcher may not be aware of or may not be able to get access to. They may also have secondary data, which, again, the researcher may not be aware of or have access to. Unfortunately, two potential difficulties may arise when seeking advice from experts: 1 Some individuals who claim to be knowledgeable and are eager to participate may not really possess expertise. 2 It may be difficult to locate and obtain help from experts who are outside the commissioning organisation, i.e. access to these individuals may be problematic. For these reasons, interviews with experts are more useful in conducting marketing research for industrial firms and for products of a technical nature, where it is relatively easy to identify and approach the experts. This method is also helpful in situations where little information is available from other sources, as in the case of radically new products and markets. For example, in a marketing research study of Indian high-net-worth consumers, much work went into the environmental context of the problem. Understanding the characteristics of such a complex and fragmented group of wealthy consumers demanded an understanding of significant cultural changes in India. As well a critical evaluation of relevant theories and secondary data, interviews with experts helped enormously with the challenge of developing a research approach and research design. Identifying credible experts on India came from an immersion in good theories and secondary data. Identifying them was just the first challenge, gaining access to them and/or their network of contacts was the major test.

Chapter 2 Defining the marketing research problem and developing a research approach

Real research

The changing Indian consumer18 Modernisation theories propose that the central challenge for developing economies is to manage the transition from traditional to modern societies. Since liberalisation of the Indian economy started in 1991, urban Indian society has become consumerist in its orientation. As a result of the political, social and economic changes of the past six decades, urban India today can be described as a modern society with strong traditional roots. The modern values and ideas that have made inroads into Indian society and culture include money, power, equality, democracy, individuality, pleasure and indulgence, celebrity and glamour, enterprise, experimentation and technology. Many of these represent ‘rational’ and ‘self-expressive’ values, as defined in modernisation theories. At the same time, there are several core values that retain their imprint on Indian society. These include hierarchy, primacy of family, importance of religion, belief in the supernatural, importance of relationships, mutual duty, alignment to the group, male superiority and scarcity consciousness. These core values have founded the Indian cultural unconscious for thousands of years. Today, it results in a constant churn and intersection of traditional and modern to create new blends, amalgams and trends that are uniquely Indian. Culture experts have commented about this fundamental aspect of Indian society in different ways. Professor Rapaille, a French–American culture guru, author of the recent bestseller, The Culture Code,19 has studied the cultures of India, China and America. He says: India has a different cultural code to China. The collective unconscious of India has a way to integrate the outside world without losing their soul. A culture which was able to get rid of the British, the Moguls, the Persians, the Arabs, and so on, could survive anything. We will not have, in India, a phase of self-destruction like the Chinese Cultural Revolution, but more of a slow practical way of using the incredible commerce ability of the Indians to their advantage without destroying their culture. Professor Sudhir Kakar, India’s foremost psychoanalyst and social commentator, writing in The Inner World,20 says: ‘its aim dramatizes a cultural ideal of the whole society, namely, a receptive absorption rather than an active alteration and opposition’. He also talks of the Elastic Indian – the eclectic Hindu who absorbs all manner of new religious practices such as reiki, pranic healing, Buddhist meditation, alongside traditional Hindu practices. These expert views point to the ‘and-ness’ of the Indian worldview, where the aim of the cultural unconscious is to find the ‘and’ answer to potentially conflicting values and ideas. Indians employ a variety of strategies to achieve ‘and-ness’: blend, balance, manipulate, conceal or negotiate and, when all other options fail, coexist.

Initial secondary data analyses Secondary data Data collected for some purpose other than the problem at hand.

Secondary data collection and analysis will be addressed in detail in Chapters 4 and 5. Here it can be seen in a broad context to include data generated within organisations, externally generated data and business intelligence. A brief introduction here will demonstrate the worth of secondary data at the stage of problem diagnosis. Secondary data are data collected for some

Marketing Research

Primary data Data originated by the researcher specifically to address the research problem.

purpose other than the problem at hand. Primary data, on the other hand, are originated by the researcher for the specific purpose of addressing the research problem. Secondary data include data generated within an organisation, including customer databases, information made available by business and government sources, commercial marketing research firms and the vast resources available online. Secondary data are an economical and quick source of background information. Analysis of available secondary data is an essential step in the problem-definition process: primary data should not be collected until the available secondary data have been fully analysed. Past information, forecasts and commentary on trends with respect to sales, market share, profitability, technology, population, demographics and lifestyle can help the researcher to understand the underlying marketing research problem. Where appropriate, this kind of analysis should be carried out at the industry and organisation levels. For example, if an organisation’s sales have decreased but industry sales have increased, the problems will be very different than if the industry sales have also decreased. In the former case, the problems are likely to be specific to the firm. Past information and forecasts can be vital in uncovering potential opportunities and problems.

Marketing decision problem and marketing research problem Marketing decision problem The problem confronting the marketing decision maker, which asks what the decision maker needs to do.

Marketing research problem A problem that entails determining what information is needed and how it can be obtained in the most feasible way.

Real research

The marketing decision problem asks what the decision maker needs to do, whereas the marketing research problem asks what information is needed and how it can best be obtained.21 The marketing decision problem is action oriented. It is concerned with the possible actions the decision maker can take. How should the loss of market share be arrested? Should the market be segmented differently? Should a new product be introduced? Should the promotional budget be increased? In contrast, the marketing research problem is information oriented. It involves determining what information is needed and how that information can be obtained effectively and efficiently. Consider, for example, the loss of market share for a particular product line. The decision maker’s problem is how to recover this loss. Alternative courses of action can include modifying existing products, introducing new products, changing other elements in the marketing mix and segmenting the market. Suppose that the decision maker and the researcher believe that the problem is caused by inappropriate segmentation of the market and want research to provide information on this issue; the research problem would then become the identification and evaluation of an alternative basis for segmenting the market. Note that this process requires much interaction, in the sense that both parties critically evaluate, develop and defend each other’s ideas to clarify the nature of decision and research problems, and to ensure there is a clear and logical connection between them. The following example further illustrates the distinction between the marketing decision problem and the marketing research problem. It also illustrates the interactive nature of identifying the marketing decision problem and the research problem, each one unfolding and informing the understanding of the other. The following example, and Table 2.1, further distinguish between the marketing decision problem and the marketing research problem.

Defining the problem Bank X:

We are experiencing a loss of market share in France in corporate banking.

Researcher: Is it just France? Bank X: No, but as we conduct the majority of our business there, the loss is causing us the greatest amount of concern.

Chapter 2 Defining the marketing research problem and developing a research approach

Researcher: Why do you think you are losing market share? Bank X:

We wish we knew!

Researcher: How are your competitors coping? Bank X: We suspect that other French banks are also suffering, and the multinational banks are capturing market share. Researcher: How do your customers feel about the quality of services you deliver? Bank X: We recently attained our ISO 9000 for service quality, which we are proud of! Researcher: But how does your service delivery compare with your competitors? After a series of discussions with key decision makers, analysis of secondary data and business intelligence sources within the bank and from other sources, the problem was identified as follows: •

•

Marketing decision problem. To improve the the relationship experience with clients both in face-to-face and online relationships, in order to arrest the decline in market share of Bank X. Marketing research problem. To determine the relative strengths and weaknesses in terms of relationship experiences of Bank X, vis-à-vis other major domestic and international competitors in France. This would be done with respect to factors that influence a company in its choice of a bank to handle its transactions.

Table 2.1

Marketing decision problems versus the marketing research problem

Marketing decision problem

Marketing research problem

Evaluates what the decision maker needs to do

Evaluates what information is needed to support the identified marketing decision

Action oriented

Information oriented

Focuses upon symptoms

Focuses on the underlying causes

The following examples further distinguish between the marketing decision problem and the marketing research problem: Which product line extension should we invest in?

To determine consumer perceptions of the qualities and fit to existing products of a selection of product line extensions

Should we invest in celebrity X to endorse our brand To determine consumer perceptions of the in Europe? qualities and fit to a brand of a selection of celebrities Should we reposition our brand with an emphasis upon raising prices?

Conceptual map A way to link the broad statement of the marketing decision problem to the marketing research problem.

To determine the price elasticity of demand and impact on sales and profits of various levels of price changes

While distinct, the marketing decision problem has to be closely linked to the marketing research problem. A good way to link the broad statement of the marketing decision problem with the marketing research problem is through the use of a conceptual map (Figures 2.4 and 2.5). A conceptual map involves the following three components:

Marketing Research

Figure 2.4

A conceptual map for problem definition (DM = decision maker)

Problem identification consists of Marketing decision problem asks

consists of guides Marketing research problem focuses on

Symptoms

What does the DM need to do?

asks

focuses on

What information is needed?

Action oriented

Information oriented

consists of

Broad statement consists of Management want to (take an action) therefore

Underlying causes

is broken down to

Specific components such as

such as Component 1

Component n such as

Component 2

We should study (topic) so that We can explain (question)

Marketing decision maker wants to (take an action) Therefore we should study (topic) So that we can explain (question). The first line states the rationale for the question and the project; this is the marketing decision problem. The second line of the conceptual map sets out the nature of the broader topic being investigated. The third line implies the question being investigated – the who/ how/why that needs to be explained. Thus, the second and third lines define the broad marketing research problem. An example follows of the conceptual map for the study of highnet-worth individuals, assuming that the French luxury brand Hermès was developing marketing strategies to develop its brand in India: Marketing decision maker wants to (develop differentiated in-store customer experiences for particular types of high-net-worth individuals) Therefore we should study (ways to segment different types of high-net-worth individuals in India) So that we can explain (the essential demographic, geographic, psychographic, behavioural and psychological factors that could shape differentiated in-store consumer experiences for luxury goods and services). As can be seen, the preceding example provides valuable definitions of the marketing decision problem and the broad marketing research problems that are closely linked. The problem is now focused upon a research approach and research design that will generate understanding and measurements of different types of high-net-worth individuals in India.

Chapter 2 Defining the marketing research problem and developing a research approach

Figure 2.5

A conceptual map for approach to the problem

Specific components of the marketing research problem

guide Approach to the problem

consists of Theoretical framework and models models could be

guide guide models could be

Verbal models

Mathematical models models could be Graphical models

consists of

consists of Research questions and hypotheses broken down to

refined statements

Research questions possible answers Hypotheses

guide guide

guide

Specification of information needed for each component

Information needed for component 1 Information needed for component 2 Information needed for component n

The distinction and linkage between the marketing decision problem and the marketing research problem helps us in understanding how the marketing research problem should be defined.

Defining the marketing research problem The general rule to be followed in defining the research problem is that the definition should: •

•

allow the researcher to obtain all the information needed to address the marketing decision problem; guide the researcher in maintaining focus and proceeding with the project in a consistent manner.

Researchers make two common errors in problem definition. The first arises when the research problem is defined too broadly. A broad definition does not provide clear guidelines for the subsequent steps involved in the project. Some examples of excessively broad marketing research problem definitions are: developing a marketing strategy for a brand, improving the competitive position of the firm, or improving the company’s image. These are not specific enough to suggest an approach to the problem or a research design. The second type of error is just the opposite: the marketing research problem is defined too narrowly. A narrow focus may preclude consideration of some courses of action, particularly those that are innovative and not obvious. It may also prevent the researcher from

Marketing Research

Figure 2.6 Marketing research problem

Proper definition of the marketing research problem

Broad statement

Specific components

addressing important components of the marketing decision problem. For example, in a project conducted for a consumer products firm, the marketing problem was how to respond to a price cut initiated by a competitor. The alternative courses of action initially identified by the firm’s research staff were to: • • •

Broad statement of the problem The initial statement of the marketing research problem that provides an appropriate perspective on the problem.

Specific components of the problem The second part of the marketing research problem definition that focuses on the key aspect of the problem and provides clear guidelines on how to proceed further.

decrease the price of the firm’s brand to match the competitor’s price cut; maintain price but increase advertising heavily; or decrease the price somewhat, without matching the competitor’s price, and moderately increase advertising.

None of these alternatives seemed promising. When outside marketing research experts were brought in, the problem was redefined as improving the market share and profitability of the product line. Qualitative research indicated that in blind tests consumers could not differentiate products offered under different brand names. Furthermore, consumers relied on price as an indicator of product quality. These findings led to a creative alternative: increase the price of the existing brand and introduce two new brands – one priced to match the competitor and the other priced to undercut it. This strategy was implemented, leading to an increase in market share and profitability. The likelihood of committing either error of problem definition can be reduced by stating the marketing research problem in broad, general terms and identifying its specific components (see Figure 2.6). The broad statement of the problem provides perspective and acts as a safeguard against committing the second type of error. The specific components of the problem focus on the key aspects and provide clear guidelines on how to proceed further, and act as a safeguard against committing the first type of error. Decisions requiring research support linked to fitting marketing research problem definitions are provided in the following example.

Components of the research approach

Paradigm A set of assumptions consisting of agreed-upon knowledge, criteria of judgement, problem fields and ways to consider them.

Once the marketing decision maker and researcher have clarified the decision problem and established the research problem they face, it has to be decided how to approach the research problem. The research problem may be very clear in the sense that there are strong established theories of what should be measured and how to conduct the measurements. Conversely, the research problem may lack theoretical foundation, with the researcher trying to cope with a broad set of issues that have not been sufficiently researched beforehand and unable to trust existing theories. How the researcher perceives the research problem affects the paradigm they will adopt in either an implicit or explicit manner. The researcher’s adopted paradigm is built upon a set of assumptions. These assumptions consist of ‘agreedupon’ knowledge, criteria of judgement, problem fields and ways to consider them22 (these factors will be developed further in Chapter 6). What is ‘agreed-upon’ refers to how strong the theories are in defining and encapsulating the issues that make up a research problem.23 Bringing together the ‘agreed-upon’ knowledge, criteria of judgement, problem fields and

Chapter 2 Defining the marketing research problem and developing a research approach

ways to consider them can be undertaken by considering the objective/theoretical framework, analytical models, research questions and hypotheses. Each of these components is discussed in the following sections. Collectively they may be considered to be the ‘approach’ that a researcher will take.

Objective/theoretical framework Theory A conceptual scheme based on foundational statements, or axioms, that are assumed to be true.

Objective evidence Perceived to be unbiased evidence, supported by empirical findings.

Real research

In general, researchers should aim to base their investigations upon objective evidence, supported by theory. A theory is a conceptual scheme based on foundational statements called axioms that are assumed to be true. Objective evidence is gathered by compiling relevant findings from secondary sources. Likewise, an appropriate theory to guide the research might be identified by reviewing academic literature contained in books, journals and monographs. The researchers should rely on theory to help them to measure or understand the variables they are investigating. Academic sources of new developments to measure, understand and analyse consumers should be constantly evaluated; the following example illustrates why.

Using faces: measuring emotional engagement: FaceTrace™24 The research company BrainJuicer (www. brainjuicer.com) tested a number of adverts that had won awards from the Institute of Practitioners in Advertising, and had therefore been shown to deliver against their business objectives. Alongside these, BrainJuicer tested a set of adverts from each of the same categories, with what might commonly be termed as having the same kind of advertising objective (i.e. direct message, relaunch, brand building). An experiment was conducted online, and each advert was tested with 150 participants. The emotional scale BrainJuicer developed stated how many viewers felt each emotion, having viewed the adverts, and also the intensity with which they felt any emotion. A review of methods used to measure emotion led the company to the conclusion that it needed to develop a self-report technique (it needed to be easy to administer and user-friendly) that overcame some of the criticisms of self-report, one that identified the emotion felt without the need for a great deal of cognitive processing on the part of the participant. The company turned to the work of Paul Ekman,25 a respected psychologist, who puts a case for a set of seven basic emotions, happiness, surprise, sadness, fear, anger, contempt and disgust, all of which are universally conveyed by and recognisable in the face. Ekman’s research on reading emotion in people’s faces had two important implications: 1 It gave BrainJuicer a framework for understanding which emotions they should be looking to capture. 2 It provided a means of accessing what participants feel, with minimal cognitive processing on their part. 3 Ekman’s research findings served as BrainJuicer’s theoretical framework for measuring emotional response. They were fundamental in helping to set out important new findings for the measurement of emotion in advertising.

Marketing Research

Table 2.2

The role of theory in applied marketing research Research task

Role of theory

Conceptualising and identifying key variables

Provides a conceptual foundation and understanding of the basic processes underlying the problem situation; these processes will suggest key dependent and independent variables

Operationalising key variables

Provides guidance for the practical means to measure or encapsulate the concepts or key variables identified

Selecting a research design

Causal or associative relationships suggested by the theory may indicate whether a causal, descriptive or exploratory research design should be adopted (see Chapter 3)

Selecting a sample

Helps in defining the nature of a population, characteristics that may be used to stratify populations or to validate samples (see Chapter 14)

Analysing and interpreting data

The theoretical framework and the models, research questions and hypotheses based on it guide the selection of a data analysis strategy and the interpretation of results (see Chapter 19)

Integrating findings

The findings obtained in the research project can be interpreted in the light of previous research and integrated with the existing body of knowledge

Researchers should also rely on theory to determine which variables should be investigated. Past research on theory development and testing can provide important guidelines on determining dependent variables (variables that depend on the values of other variables) and independent variables (variables whose values affect the values of other variables). Furthermore, theoretical considerations provide information on how the variables should be operationalised and measured, as well as how the research design and sample should be selected. A theory also serves as a foundation on which the researcher can organise and interpret the findings: ‘nothing is so practical as a good theory’.26 Conversely, by neglecting theory researchers increase the likelihood that they will fail to understand the data obtained or be unable to interpret and integrate the findings of the project with findings obtained by others. The role of theory in the various phases of an applied marketing research project is summarised in Table 2.2. Applying a theory to a marketing research problem requires creativity on the part of the researcher. A theory may not specify adequately how its abstract constructs (variables) can be embodied in a real-world phenomenon. Researchers must therefore take the best of what they believe to be the most novel theories to represent and encapsulate consumer thinking and behaviour. It is also vital for researchers to recognise that theories are incomplete; they deal with only a subset of variables that exist in the real world. Hence, the researcher must also identify and examine other variables that have yet to be published as theories. This may involve the researcher developing ‘grounded theory’,27 (which will be explained and developed in Chapter 6).

Analytical model Analytical model An explicit specification of a set of variables and their interrelationships designed to represent some real system or process in whole or in part.

An analytical model is a set of variables and their interrelationships, designed to represent, in whole or in part, some real system or process. Models can have many different forms. The most common are verbal, graphical and mathematical structures. In verbal models, the variables and their relationships are stated in prose form. Such models may be mere restatements of the main tenets of a theory. Graphical models are visual. They are used to isolate variables

Chapter 2 Defining the marketing research problem and developing a research approach Verbal models Analytical models that provide a written representation of the relationships between variables.

Graphical models Analytical models that provide a visual picture of the relationships between variables.

Mathematical models Analytical models that explicitly describe the relationships between variables, usually in equation form.

Real research

and to suggest directions of relationships but are not designed to provide numerical results. They are logical, preliminary steps to developing mathematical models.28 Mathematical models explicitly specify the relationships among variables, usually in equation form.29 These models can be used as guides for formulating the research design and have the advantage of being amenable to manipulation.30 As can be seen from this example, the verbal, graphical and mathematical models depict the same phenomenon or theoretical framework in different ways. The phenomenon of ‘sponsorship impact’, stated verbally, is represented for clarity through a figure (graphical model) and is put in equation form (mathematical model) for ease of statistical estimation and testing. Graphical models are particularly helpful in clarifying the concept or approach to the problem. The verbal, graphical and mathematical models complement each other and help the researcher identify relevant research questions and hypotheses.

Model building with ESP Properties The three approaches to model building can be understood through an example. ESP Properties (www.espglobal.com), part of WPP, is a leading sports and entertainment rights management company. Firms working with ESP Properties are seeking to use sponsorship as a marketing tool. However, for sponsorship to be effective it is vital to ensure that the most appropriate sponsorship is selected. This requires a high level of planning before any sponsorship is agreed, as outlined in the following.

Verbal model The marketing department wish to include an investment in sponsorship as part of an integrated marketing communications strategy. They need to understand the potential impact of their sponsorship investment. They start by deciding what key objectives should be fulfilled through a sponsorship relationship. They then select a sector (sports, arts, culture, environment, broadcast) and the type of property (event, team, performance, individual, programme). Once the sector and property have been selected, they set specific objectives that can be developed to help to set realistic targets and a set of metrics as a means to measure success.

Mathematical model n

y = a0 +

∑a x i =1

where y = sponsorship impact a0, ai = model parameters to be estimated statistically xi = sponsorship requirement factors.

Research questions Research questions Refined statements of the specific components of the problem.

Research questions are refined statements of the components of the problem. Although the components of the problem define the problem in specific terms, further detail may be needed to develop an approach. Each component of the problem may have to be broken down into subcomponents or research questions. Research questions ask what specific information is required with respect to the problem components. If the research questions are answered by the research, then the information obtained should aid the decision maker. The

Marketing Research

formulation of the research questions should be guided not only by the problem definition, but also by the theoretical framework and the analytical model adopted. For a given problem component, there are likely to be several research questions.

Hypothesis Hypothesis An unproven statement or proposition about a factor or phenomenon that is of interest to a researcher.

A hypothesis is an unproven statement or proposition about a factor or phenomenon that is of interest to the researcher. For example, it may be a tentative statement about relationships between two or more variables, as stipulated by the theoretical framework or the analytical model. Often, a hypothesis is a possible answer to the research question.31 Hypotheses go beyond research questions because they are statements of relationships or propositions rather than merely questions to which answers are sought. Research questions are interrogative; hypotheses are declarative and can be tested empirically (see Chapter 20). An important role of a hypothesis is to suggest variables to be included in the research design.32 The relationship between the marketing research problem, research questions and hypotheses, along with the influence of the objective/theoretical framework and analytical models, are described in Figure 2.7.33 Hypotheses are an important part of the approach to a research problem. When stated in operational terms, such as H1 and H2, they provide guidelines on what, and how, data are to be collected and analysed. When operational hypotheses are stated using symbolic notation, they are commonly referred to as statistical hypotheses. It is important to note that not all research questions can be developed into hypotheses that can be tested. Certain research questions may be exploratory in nature, with the researcher having no preconceived notions of possible answers to the research questions, nor the ability to produce statements of relationships or propositions. If the researcher is faced with such a situation, it does not mean that the investigation will not be as valid as one where hypotheses are clearly established. It means that the researcher may have to adopt a different approach or paradigm to establish its validity.

Figure 2.7 Development of research questions and hypotheses

Components of the marketing research problem Objective/ theoretical framework Research questions Analytical model Hypotheses

Summary

Defining the marketing research problem is the most important step in a research project. Problem definition is a difficult step, because, frequently, decision makers have not determined the actual problem or only have a vague notion about it. The researcher’s role is to help decision makers identify and define their marketing research problem.

Chapter 2 Defining the marketing research problem and developing a research approach

The formal ways in which decision makers and researchers communicate their perspectives on a research problem and how to solve it are through the development of a research brief and a research proposal. To develop these documents fully, researchers should be proactive in arranging discussions with key decision makers, which should include a problem audit whenever possible. They should also conduct, where necessary, interviews with relevant experts, and secondary data collection and analyses. These tasks should lead to an understanding of the environmental context of the problem. Analysis of the environmental context should assist in the identification of the marketing decision problem, which should then be translated into a marketing research problem. The marketing decision asks what the decision maker needs to do, whereas the marketing research problem asks what information is needed and how it can be obtained effectively and efficiently. The researcher should avoid defining the marketing research problem either too broadly or too narrowly. An appropriate way of defining the marketing research problem is to make a broad statement of the problem and then identify its specific components. Developing an approach to the problem is the second step in the marketing research process. The components of an approach may consist of an objective/theoretical framework, analytical models, research questions and hypotheses. It is necessary that the approach developed be based upon objective evidence or empirical evidence and be grounded in theory as far as it is appropriate. The relevant variables and their interrelationships may be neatly summarised in an analytical model. The most common kinds of model structures are verbal, graphical and mathematical. The research questions are refined statements of the specific components of the problem that ask what specific information is required with respect to the problem components. Research questions may be further refined into hypotheses. Finally, given the problem definition, research questions and hypotheses should be used to create a method either to measure or elicit an understanding of target participants.

Questions

1 2 3 4 5 6 7 8 9 10 11

What is the nature of the first step in conducting a marketing research project? Why is it vital to define the marketing research problem correctly? What is the role of the researcher in the problem definition process? What are the components of a marketing research brief? What are the components of a marketing research proposal? How may a researcher be creative in interpreting a research brief and developing a research proposal? What is the significance of the ‘background’ section of a research brief and research proposal? Describe some of the reasons why management are often not clear about the ‘real’ research problem that needs to be addressed. What interrelated events occur in the environmental context of a research problem? What are some differences between a marketing decision problem and a marketing research problem? Describe the factors that may affect the approach to a research problem.

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12 13 14 15

Exercises

What is the role of theory in the development of a research approach? What are the most common forms of analytical models? What are the differences between research questions and hypotheses? Is it necessary for every research project to have a set of hypotheses? Why or why not?

1 Imagine that you are the Marketing Director of Lufthansa. a Make a list of potential marketing objectives whose fulfilment could improve the performance of Lufthansa. b

Select what you feel would be the most important marketing objective. Develop a set of marketing research objectives that you consider would support the decisions needed to fulfil that marketing objective. 2 You are a consultant to Audi AG, working on a project for their Lamborghini subsidiary. a Use online databases to compile a list of articles related to the Lamborghini and the global high-performance luxury car market in the past year. b c

Visit the Lamborghini and Ferrari websites and evaluate the extent of competitive information available at each.

Based upon the information collected from 2a and 2b, write a report on the environmental context surrounding Lamborghini. 3 In a small group discuss the following issues: ‘Is it feasible that marketing decision makers may not conceive of or be able to express the nature of decision support they need? What are the implications of such a possibility in the development of research proposals?’ And ‘From where may theory emerge to ground applied marketing research and what may be the relative worth of the source of theories used by researchers?’ 4 Visit www.innocentdrinks.co.uk and other relevant sources of business news and gather relevant information about the marketing challenges of Innocent Smoothies. As a brand manager for Innocent Smoothies you are concerned about improving the performance of your brand. Identify possible factors that you feel may shape the future performance of the brand. Write a brief report of 1,000 words that sets out Innocent’s marketing challenges and concludes with your views of factors that could shape its future performance. 5 Visit www.fabindia.com. In particular, look at the sections that describe the vision and philosophy behind this business. Gather online secondary data and business intelligence from online sources, especially your library’s online databases. If Fabindia were to develop its brand further in selected European countries, what would the key challenges be? Write a brief report of 1,000 words that sets out Fabindia’s challenges, identify five experts who may have a view of capitalising upon these challenges, and give brief details of why these individuals may be seen as experts.

Chapter 2 Defining the marketing research problem and developing a research approach

Notes 1. Cliffe, A., McCauley, B. and Briscoe, R. ‘Asda: Diving deeper, thinking broader, working closer’, MRS Awards (December 2013). 2. ‘Marketing profs knowledge exchange: money spent, marketing research, decision-making’, www. marketingprofs.com/ea/qst_question.asp?qstID=11527, accessed 4 November 2010; Sheth, J.N. and Sisodia, R.S., ‘Marketing productivity: issues and analysis’, Journal of Business Research 55 (5) (May 2002), A9; Butler, P., ‘Marketing problem: from analysis to decision’, Marketing Intelligence & Planning 12 (2) (1994), 4–12. 3. Ingledew, S., ‘How to bait the interview hook for those Top 1000 big fish’, ResearchPlus (October 1996), 4. 4. John, C.F., ‘From Iliad to Odyssey: the Odyssey of our profession’, ESOMAR Congress Odyssey, Athens (September 2010); Greenhalgh, C., ‘How should we initiate effective research?’, The Market Research Society Conference (1983). 5. Srivatsa, A., Puri, A. and Raj, S., ‘The case of the elusive insight: lessons from the greatest researcher of them all’, ESOMAR Consumer Insights Conference, Milan (May 2007). 6. Blachowska, M., ‘From consumer connection to consumer insight: a Nestlé case study’, ESOMAR Consumer Insights Conference, Milan (May 2007). 7. Methner, T. and Frank, D., ‘Welcome to the house of research: achieving new insights and better brand knowledge through courageous ways of collaboration in what is usually a competitive environment’, ESOMAR Congress Odyssey, Athens (September 2010). 8. Pagani, P., Raubik, P. and May, J., ‘Coca-Cola Europe and the philosopher’s stone: crafting a rare win-win-win situation’, ESOMAR Congress Odyssey, Athens (September 2010). 9. Pagani, P., Raubik, P. and May, J., ‘Coca-Cola Europe and the philosopher’s stone: crafting a rare win-win-win situation’, ESOMAR Congress Odyssey, Athens (September 2010). 10. ESOMAR, ‘Global Market Research’, ESOMAR Industry Report (2010), 48. 11. Heeg, R., ‘Do-it-yourself’, Research World (December 2005), 25. 12. Heeg, R., ‘DIY’, Research World (February 2006), 15. 13. Cooke, M. and Buckley, N., ‘Web 2.0, social networks and the future of market research’, International Journal of Market Research 50 (2) (2008), 267–92; Marshall, G.W., ‘Selection decision making by sales managers and human resource managers: decision impact, decision frame and time of valuation’, Journal of Personal Selling and Sales Management (Winter 2001), 19–28. 14. Anon., ‘How to decide who should get what data’, HR Focus (May 2001), 7; Cronin, M.J., ‘Using the web to push key data to decision makers’, Fortune 36 (6) (29 September 1997), 254. 15. Copernicus Marketing Consulting, ‘Auditing a marketing program’, www.copernicusmarketing.com/univers/audit. shtml, accessed 10 November 2010; Reid, M., ‘IMCperformance relationship’, International Journal of

Advertising 22 (2) (2003), 227–48; Morgan, N.A., ‘Marketing productivity, marketing audits, and systems for marketing performance assessment: integrating multiple perspectives’, Journal of Business Research 55 (5) (May 2002), 363; Merrilyn, A.T., ‘Quick marketing audit’, Law Practice Management 23 (6) (September 1997), 18, 63; Berry, L.L., Conant, J.S. and Parasuraman, A., ‘A framework for conducting a services marketing audit’, Journal of the Academy of Marketing Science 19 (Summer 1991), 255–8; Ackoff, R.L., Scientific Method (New York: Wiley, 1961), 71; Ackoff, R.L., The Art of Problem Solving (New York: Wiley, 1978). 16. Balmer, J.M.T., ‘Corporate marketing: apocalypse, advent and epiphany’, Management Decision 47 (4), (2009), 544–72; Charan, R., ‘Conquering a culture of indecision’, Harvard Business Review (April 2001), 74; Nwachukwu, S.L.S. and Vitell, S.J. Jr, ‘The influence of corporate culture on managerial ethical judgments’, Journal of Business Ethics 16 (8) (June 1997), 757–76. 17. Grisham, T., ‘The Delphi technique: a method for testing complex and multifaceted topics’, International Journal of Managing Projects in Business 2 (1) (2009), 112–30; Malo, K., ‘Corporate strategy requires market research’, Marketing News 36 (2) (21 January 2001), 14; Winett, R., ‘Guerilla marketing research outsmarts the competition’, Marketing News 29 (1) (January 1995), 33. 18. Shivakumar , H., ‘“And-ness”: the key to the changing Indian consumer’, Admap 479 (January 2007), 38–40. 19. Rapaille, C., The Culture Code: An Ingenious Way to Understand Why People Around the World Buy and Live as They Do (Portland, OR: Broadway Books, 2007). 20. Kakar, S., The Inner World: A Psycho-analytical Study of Hindu Childhood and Society (Oxford: Oxford University Press, 2008). 21. Ganeshasundaram, R. and Henley, N., ‘The prevalence and usefulness of market research: an empirical investigation into “background” versus “decision” research’, International Journal of Market Research 48 (5) (2006), 525–50; Roe, M. and Vervoot, J., ‘A market research training simulation – bringing market research closer to decision-makers’, ESOMAR Innovate! Conference, Paris (February 2005); Gordon, A., ‘Linking marketing decisions with consumer decision making: closing the gap between feelings and behaviour’, ESOMAR Annual Congress, Lisbon (September 2004). 22. Potter, G., The Philosophy of Social Science: New Perspectives (Harlow: Pearson, 2000), 242. 23. Saren, M. and Pels, J., ‘A comment on paradox and middle-range theory: universality, synthesis and supplement’, Journal of Business & Industrial Marketing 23 (2) (2008), 105–7. 24. Wood, O., ‘Using faces: measuring emotional engagement for early stage creative’, ESOMAR Annual Congress, Berlin (September 2007). 25. Ekman, P., Emotions Revealed, Understanding Faces and Feelings (London: Phoenix, 2003). 26. Nyilasy, G. and Reid, L.N., ‘The academicianpractitioner gap in advertising’, International Journal of Advertising 26 (4) (2007), 425–45; Lilien, G.L., ‘Bridging the marketing theory’, Journal of Business

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Research 55 (2) (February 2002), 111; Hunt, S.D., ‘For reason and realism in marketing’, Journal of Marketing 56 (April 1992), 89–102. 27. Goulding, C. and Saren, M., ‘Immersion, emergence and reflexivity: grounded theory and aesthetic consumption’, International Journal of Culture, Tourism and Hospitality Research 4 (1) (2010), 70–82. 28. For an illustration of a graphical model, see Nauckhoff, F., Asberg, P. and Hemmingsson, C., ‘Managing media planning and brand positioning across media platforms’, ESOMAR Worldwide Media Measurement, Stockholm (May 2009). 29. For an illustration of a mathematical model based on it, see Suher, J. and Sorenson, H., ‘The power of Atlas: why in-store shopping behavior matters’, Journal of Advertising Research 50 (1) (2010), 21–9. 30. Patwardhan, P. and Ramaprasad, J., ‘Rational integrative model of online consumer decision-making’, Journal of Interactive Advertising 6 (1) (Fall 2005), 2–13; Malhotra, N.K. and Wu, L., ‘Decision models and descriptive

models: complementary roles’, Marketing Research 13 (4) (December 2001), 43–4. 31. For an example of hypothesis formulation, see Bian, X. and Moutinho, L., ‘The role of brand image, product involvement, and knowledge in explaining consumer purchase behaviour of counterfeits: direct and indirect effects’, European Journal of Marketing 45 (1/2) (2010), 191–216. 32. For an example of model development and hypothesis formulation, see Heath, R.G., Nairn, A.C. and Bottomley, P.A., ‘How effective is creativity? Emotive content in TV advertising does not increase attention’, Journal of Advertising Research 49 (4) (December 2009), 450–63. 33. The integrated role of theory, models, research questions and hypotheses in marketing research can be seen in Nygaard, A. and Dahlstrom, R., ‘Role stress and effectiveness in horizontal alliances’, Journal of Marketing 66 (April 2002), 61–82; Nunes, J.C., ‘A cognitive model of people’s usage estimations’, Journal of Marketing Research 37 (4) (November 2000), 397–409.

3 Stage 1

Problem definition

Stage 2 Research approach developed

Stage 3 Research design developed

Stage 4 Fieldwork or data collection

Stage 5 Data integrity and analysis

Stage 6 Communicating research findings

Research design

There is a wide choice of alternative research designs that can meet research objectives. The key is to create a design that enhances the value of the information obtained, while reducing the cost of obtaining it.

Marketing Research

Objectives After reading this chapter, you should be able to: 1 define research design, classify various research designs and explain the differences between exploratory and conclusive research designs; 2 compare the basic research designs: exploratory, descriptive and causal; 3 understand how participants or the subjects of research design affect research design choices; 4 understand the strengths and weaknesses of key research designs; 5 describe the major sources of errors in a research design, including random sampling error and the various sources of non-sampling error.

Overview Chapter 2 discussed how to define a marketing research problem and develop a suitable approach. These first two steps are critical to the success of the whole marketing research project. Once they have been completed, attention should be devoted to designing the formal research project by formulating a detailed research design (as a reminder, see Figure 2.3). This chapter defines and classifies research designs. We examine the nature of research design from the perspectives of decision makers and participants. Two major types of research design are then discussed: exploratory and conclusive. We further classify conclusive research designs as descriptive or causal and discuss both types in detail. The differences between the two types of descriptive designs are then considered (crosssectional and longitudinal) and sources of errors are identified. The special considerations involved in formulating research designs in international marketing research are discussed. A better appreciation of the concepts presented in this chapter can be gained by first considering the following example, which illustrates the use of a number of interrelated techniques to build a research design.

Real research

Getting to know you1 Building a relationship with consumers is a challenge facing all organisations, but particularly so in the case of ‘emergent drinkers’, those of legal drinking age up to 25. Allied Domecq Spirits and Wines (www.allieddomecq.com) recognised the danger of being distanced from this crucial group, particularly across geographical markets. Allied Domecq worked with Pegram Walters International (www.aegisplc.com) on a project that went far beyond an exploration of the current usage and attitudes towards spirits. The objectives of the project encompassed an exploration of the target groups’ personal values, their feelings about their lives, their universe, their hopes and dreams. There were three stages to the research design. In the first stage the researchers conducted one-hour in-depth interviews. There were three clear objectives for this stage: to understand personal viewpoints on marketing and lifestyle issues; to clarify and/or narrow down topics for subsequent exploration; and to recruit appropriate ‘information gatherers’. From this stage, hypotheses were formulated on issues such as how participants saw themselves and their future, their relationships, self-discovery and opting in or out of the

Chapter 3 Research design

system. In the second stage, from 20 in-depth interviews, 10 participants were retained as ‘information gatherers’. ‘Leading-edge’ bars were rented out and 50 adult emergent drinkers were invited to participate in workshops. Given a task guideline, the i nformation gatherers led discussions. As an additional record, the workshops were video recorded. The participants felt comfortable within their peer group and, in the more natural bar environment, fed back real, relevant and honest information. The third stage occurred on the night following the workshops. Focus groups were used, made up of the ‘information gatherers’. They discussed what happened in the workshops and their interpretation of what it actually meant. In order to ensure that the information remained topical, useful and easily accessible, it was felt important to create a vehicle for an ongoing communication and dialogue with the target market. To achieve this, a highimpact ‘magazine’ was created to bring the research to life after the presentation of findings. This was referred to as a magazine and not a research report to reflect the lifestyle of the consumer group in question: it contained images, layouts and fonts typically associated with the generation.

The above example illustrates a very creative and useful exploratory research design. As a research design it worked well in that it achieved a balance of the needs and expectations of marketing decision makers and participants. Decision makers helped to set clear research objectives based upon the gaps in their knowledge of the target market. Participants related well to the questions and issues posed to them, in a context and environment in which they felt comfortable. An understanding of the fundamentals of research design, its components and the trade-offs between the parties involved in crafting an effective research design enabled the researchers to formulate the most appropriate design for the problem at hand.

Research design definition Research design A framework or plan for conducting the marketing research project. It specifies the details of the procedures necessary for obtaining the information needed to structure or solve marketing research problems.

A research design is a framework or plan for conducting a marketing research project. It details the procedures necessary for obtaining the information needed to structure or solve marketing research problems. Although a broad approach to the problem has already been developed, the research design specifies the details, the practical aspects of implementing that approach. A research design lays the foundation for conducting the project. A good research design will ensure that the marketing research project is conducted effectively and efficiently. Typically, a research design involves the following components or tasks, is discussed in detail in various chapters: 1 Define the information needed (Chapter 2). 2 Decide whether the overall design is to be exploratory, descriptive or causal (Chapter 3). 3 Design the sequence of techniques of understanding and/or measurement (Chapters 4 to 12). 4 Construct and pre-test an appropriate form for data collection or questionnaire (Chapters 7, 8 and 13). 5 Specify the qualitative and/or quantitative sampling process and sample size (Chapters 6, 14 and 15). 6 Develop a plan of qualitative and/or quantitative data analysis (Chapters 9 and 19).

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In formulating a research design, the researcher has to balance the perspectives of marketing decision makers and target participants. From their education and experience, marketing decision makers may have certain techniques that they believe to be the most effective and in which they subsequently have more confidence. There is no problem with this, providing the technique is the best means to measure or understand the issue under investigation, from the perspective of participants. In the example at the start of this chapter, decision makers had confidence in the qualitative techniques and the data generated. The techniques worked well with the participants, drawing out a rich picture of participant behaviour, lifestyle and aspirations. However, should the decision makers feel that survey techniques were the most effective, giving them the most confidence to support their decisions, the researchers may face a dilemma. If they use survey techniques they might find that participants may have a different relationship with interviewers, do not reflect in the same manner and ultimately do not reveal so much. Thus, research design involves the researchers developing an understanding of the type of data decision makers have confidence in, plus an understanding of how participants may respond to different techniques. The first part of this balancing act involves understanding research design from the decision makers’ perspective; the second part involves understanding the participants’ perspective.

Research design from the decision makers’ perspective Marketing decision makers seek support from researchers that is of practical relevance to the decisions they face. To give practical support, decision makers expect information that is: •

•

Accurate, i.e. the most valid representation of the phenomena under investigation, that has come from the most reliable or consistent form of measurement or understanding, that is sufficiently sensitive to the important differences in individuals being measured or understood. Combining these three criteria refers to the degree to which information may be deemed as ‘accurate’. Current, i.e. as up to date as possible. This is particularly important where consumer attitudes, lifestyle or behaviour change quickly, perhaps due to rapid technological changes or new product offerings in a highly competitive market. Sufficient, i.e. the completeness or clarity of a ‘picture’ that reflects the characteristics of the marketing problem the decision makers face. Available, i.e. that access to the relevant information can be made when a decision is imminent. This is particularly important where competitive activity forces the decision makers into making a rapid response. Relevant, i.e. that the support given ‘makes sense’ to decision makers. In a very general sense, decision makers may criticise qualitative research approaches and techniques for being biased and unrepresentative and, conversely, quantitative approaches and techniques for lacking depth and a contextual perspective. Whichever approach or techniques are adopted, decision makers should be aware of their benefits, limitations and even alternatives. With this awareness they can use the findings with confidence to build upon their existing experiences and knowledge.

Generating information that fulfils all the above characteristics is extremely difficult, if not impossible, to achieve in marketing research. The evaluation of sources of error, presented later in this chapter, and the restrictions of budget and timescales mean that this list represents ‘ideals’. Realistically, trade-offs must be made among the above characteristics. Within the first characteristic of accuracy there are further trade-offs, which are primarily caused by what the researcher is attempting to measure or understand:2

Chapter 3 Research design

1 The subject of investigation is usually human. 2 The process of measuring or observing humans may cause them to change. 3 It is difficult to assess the effect of extraneous variables in marketing experiments and thus their applications are limited. Given the complexity of the subjects under study, the context or environment in which measurements are taken and the skills required to perform and interpret measurements, it is difficult (if not impossible) to gain completely objective and accurate measurements.3 Of all the potential trade-offs, if one were to remove relevance, then the whole rationale of supporting the marketing decision maker would be removed. Therefore this characteristic can never be compromised. Relevance embraces, among other things, the ability to plan and forecast from research findings, to be able to distinguish real differences in consumer traits and to know that characteristics are representative of groups of individuals. With relevant information such as this, the decision maker can build up a stronger understanding or awareness of markets and the forces that shape them. In building up this understanding, the decision maker cannot turn to a single technique or even body of techniques that may be deemed ‘ideal’ in ensuring that information is relevant.4 In different types of decision-making scenarios, different techniques will offer the best support for that decision maker. Establishing the best form of support is the essence of research design. A fundamental starting point in deciding an appropriate design is viewing the process from the point of view of the potential subject or participant of a marketing research study.

Research design from the participants’ perspective The potential participants in any marketing research investigation play a vital role in deciding which research design will actually work in practice. A subject of study may be complex and need time for participants to reflect upon and put words to the questions posed. Certain methods are more likely to build up a rapport and trust – in these circumstances putting the participants in the right frame of mind and getting them to respond in a full and honest manner. Figure 3.1 is a framework that serves to remind how participants may be accessed, and what kinds of response may be generated.5 In Figure 3.1 the box under the heading ‘Layers of response from participants’ represents how participants may react to questions posed to them. In the first layer of ‘Spontaneous, Reasoned, Conventional’ are questions that participants can express a view about quickly, and that are simple for them to reflect upon, relating to common, everyday occurrences that are at the forefront of their minds. In such circumstances, simple structured questioning (or self-reporting) in a standardised manner is possible. Further, the same procedure can be conducted in a consistent manner to a whole array of ‘types’ of participant, such as age groups, social class and intellectual levels. For example, if questions were posed on which news papers someone reads, it is a reasonable assumption that participants would be aware of the newspaper title(s), these title(s) can be communicated and the topic of newspaper readership is not a sensitive issue. In these circumstances, where answers to questions on reading habits are relatively easy to access and respond to, highly structured questionnaires are appropriate. Clearly, in such situations, quantitative techniques are applicable that allow very detailed descriptions or experiments to be conducted. The following example illustrates the use of a structured online survey that allowed detailed descriptions and attitudinal measurements of visitors to an exclusive event.

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Figure 3.1 Access to participant

Layers of response from participants • Spontaneous • Reasoned • Conventional

Examples of techniques

Tends to be conclusive

Highly structured questionnaires e.g. telephone surveys

Aware

Communicable

Public

Responses to interviewing

• Concealed • Personal

Questionnaires with a proportion of openended questions to allow probing e.g. face-to-face surveys Semi-structured to unstructured interviews on an individual or group basis e.g. focus group discussions

Unaware

Non-communicable

Private

• Intuitive • Imaginative

• Unconscious • Repressed

Unstructured interviews and observations e.g. naturalistic approaches on a one-to-one basis Tends to be exploratory

Real research

The Moving Motor Show at Goodwood Held within the spectacular grounds of Goodwood Park, the exclusive Moving Motor Show (https://www.goodwood.com/ grrc/event-coverage/festival-of-speed/) was an important addition to the Festival of Speed. The show enabled a limited number of motoring enthusiasts and new-car buyers to see the very latest models up close for the first time in the UK, and, in some cases, also to climb aboard and experience the vehicles firsthand, strictly at the invitation of the attending vehicle manufacturers. Following the show, IFM Sports Marketing

Chapter 3 Research design

Surveys (now part of Repucom: http://repucom.net) contacted visitors using its ticketing database as a sampling frame. Event attendees were invited to complete an online questionnaire. The nature of questions posed in this survey addressed attitudinal, behavioural and demographic questions. These questions did not demand in-depth reflection on the part of participants; their responses could be articulated with ease in a concise survey that took five minutes to complete. As most attendees to the event were passionate about Goodwood and cars, their engagement with the subject was high, resulting in 777 completed questionnaires. The show succeeded in attracting new visitors to Goodwood: 26% of visitors had never been to any event prior to this visit. Encouragingly, 37% of visitors had nothing negative to say about their visit to Goodwood; however, 27% disliked the walk from the car park to the event.

Progressing down Figure 3.1, at the second level are questions that are more personal and more sensitive. There are two characteristics that can turn otherwise mundane topics into sensitive ones.6 The first involves any private, sacred or stressful aspect of a participant’s life. The second is the real or perceived stigma associated with specific thoughts or actions. A great amount of business-to-business research can be added to these in terms of commercially sensitive information. Again, structured questionnaires can measure the relevant issues, but an amount of rapport may be needed to induce participants to trust the interviewer and reveal their ‘more personal’ attitudes and behaviour. Where the presence of the interviewer causes discomfort or bias, the method of audio/computer-assisted self-interviewing may be used7 or, far more frequently, the anonymity of online research methods can facilitate more honest and open responses.8 Such techniques combine the higher response rates of personal interviews with the privacy of self-administered questionnaires. The following example illustrates how the condom manufacturer Durex managed to research a sensitive topic.

Real research

Minimising unease, embarrassment or reluctance in disclosing intimate personal information9 Durex (www.durex.com) wishes to support each individual’s right to enjoy a healthy and rewarding sex life. The challenge for Durex, in this vision, is to develop a brand platform that encompasses sexual well-being (and, through this, the promise of an enhanced and better sex experience), without eroding its safe sex and barrier protection. To fulfil its overall business objective of providing insights to support the commercial vision for the brand, marketing research was needed to address a number of discrete research objectives. These ranged from understanding sexual well-being and how it fits into people’s lives, through exploring the sexual activities they take part in, to future trends. It was also critical to ensure that within the overarching aim, the needs of individual stakeholder audiences were met through a robust and reliable research design. The stakeholder audiences included internal business teams and divisions, sexual well-being and health experts, clinicians, politicians, opinion formers and teachers. Openness to talking about sex can vary greatly, not only from individual to individual, but from one culture to another. So a key challenge for the research was to ensure that unease, embarrassment or reluctance in disclosing intimate personal information was minimised. For those who would choose to participate in the survey, their concerns were in participant willingness

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to answer more specific, detailed and sensitive questions (e.g. on sexual activities or dysfunctions). In designing the survey, these issues needed to be front of mind, and every effort made to minimise their potential impact on response rates, data quality and, ultimately, on costs and feasibility. The duty of care to participants in the survey was at the centre of the thinking throughout questionnaire design, and the respective codes of conduct in each of the 26 countries covered in the research were rigorously followed. The focus of the approach was the idea of ‘treating others as we expect to be treated’. So, it was extremely important to be open and honest about the nature of the survey from the very beginning. The introduction advised participants of the sensitive nature of the questions and it also stressed that researchers were not in any way intending to cause any offence. Participants were consequently able to make an informed choice as to their participation. A funnel approach to questionnaire design was adopted, with the less sensitive questions placed at the beginning of the questionnaire to build trust, so that participants felt comfortable being asked the more sensitive questions later on. Throughout the survey, participants were given the option to decline to answer, or suspend, to ensure they did not feel pressured into answering questions they did not feel comfortable with. After careful consideration of the strengths and limitations associated with each mode of data collection available in a researcher’s toolkit, an online approach was singled out as the best one for this survey. This approach presented a number of key advantages over other methods for the following reasons: •

The sensitive topic area required an approach that allowed for honesty and openness.

•

Removing any interviewer influence or bias was also considered key to data quality.

•

The need for global coverage.

•

Reach/cost ratio: an online approach was the most cost-effective way of obtaining global reach.

However, an online approach was not feasible in Nigeria, principally due to low penetration levels of the telephone and internet. Instead, a face-to-face self-completion approach was adopted in this country.

At the third level are questions that require participants to be creative. For example, if participants were to be asked about their attitudes and behaviour towards eating yogurt, this could be done in a very structured manner. Questions could be set to determine when it was eaten, favourite flavours and brands, where it was bought, how much was spent, etc. The same can be said of alcohol consumption, though this could well be a sensitive issue for many participants. Now imagine a new product idea that mixes yogurt and alcohol. What combinations of alcohol and yogurt would work, and what types of consumer would be attracted to them? Would it be a dessert liqueur such as Baileys Irish Cream, or frozen yogurt to compete with the Häagen-Dazs luxury ice creams? Would champagne, advocaat, whisky or beer be the best alcoholic ingredient? Should any fruits be added? Individually? Forest fruits? Tropical fruits? How would the product be packaged? What name would best suit it? What price level would it sell at? On what occasions would it be consumed? Answering these questions demands a great amount of creativity and imagination. It demands that participants reflect upon ideas, play with ideas and words and dig deep to draw out ideas in a relaxed manner. Structured questionnaires cannot do this; such a scenario would work best with the use of focus groups. One of the major participant-access challenges faced at this level relates to how participants articulate their views and feelings,

Chapter 3 Research design

especially their emotional states related to brands. The following example illustrates how research participants can be helped to articulate what they may feel about sensations and brands.

Real research

What the nose knows10 Thomas Inglesant works in the Global Consumer Insights team of the fragrances and flavours company Givaudan (www.givaudan.com). The task of his team is to help brands match household products, such as floor cleaners, with scents that appeal to consumers. One of the main activities of his team is the broad pursuit of an understanding of consumers, covering their attitudes and usage habits as they relate to different products. This work is growing, with group discussions, one-to-one interviews and in-home ethnography as commonly used tools. Inglesant notes: ‘the negative side is there are no numbers so you cannot do statistics with the results, but the positive is that it is more to do with the “why”, rather than the “what” and the “how much”’. One of the problems with asking consumers about different scents is that they tend not to have many words to be able to describe either a smell or why they do or don’t like it. Words such as ‘clean’ and ‘fresh’ are used almost universally by people describing a whole range of scents they like. In case words fail them, consumers can be shown pictures to help them associate scents with certain moods, colours or scenes. Researchers draw on a bank of about 100 pictures – everything from food and flowers to mountain views and people pulling different facial expressions – to help discussions along. In some instances, consumers are given a bank of descriptive words and asked to choose which best describe the fragrance they are given.

At the fourth level may be questions that participants may not be able to conceptualise, never mind be able and willing to express what they feel about particular views and feelings. Consumers may absorb masses of marketing-related stimuli, react to them and ‘intend’ to behave without really knowing why or even being aware of the true drivers of their intentions or behaviour.11 An example may be trying to understand the childhood influences of family and friends on an individual’s perception and loyalty to brands that the individual may purchase, perhaps on a habitual basis – an example being washing-up liquid. Another example may be understanding the image consumers have of themselves and an image they wish to portray by spending €20,000 on a Rolex wristwatch. Participants do not normally have to think through such issues or articulate reasons for buying expensive luxury or fashion brands, until a researcher comes along! There is an implicit assumption in research that people carry attitudes around in their head that determine their buying behaviour. Most of the time, we don’t give much thought to the burger we’ve eaten or even the flight we’ve made. Our natural inclination is to be polite and cooperative. If a researcher asks us to give an opinion we will do our best to formulate one on the spot.12 In circumstances where the researcher is digging deep into topics that participants do not normally think about or articulate, polite responses to questions may be very misleading. The characteristics of the individual participant may determine what is the best way to probe and elicit appropriate responses. Nothing is standardised or consistent in these circumstances, the researchers having to shape the questions, probes and observations as they see fit in each interview or observation situation. The following example illustrates the challenges faced by researchers and research participants in thinking and articulating their emotional relationships to brands.

Marketing Research

Real research

Winning people’s hearts13 There are plenty of brands that give consumers satisfaction, and then there are brands such as Apple (www.apple.com) and Netflix (www.netflix.com) that have something extra. This intangible something is what Marc Gobé, CEO of Desgrippes Gobé Group (www.dga.com), calls ‘emotional branding’, and he says it is what makes consumers fall in love with a brand: This magnetism can be manufactured and there's a big role for research in coming up with the right chemistry to create it. Nike is a good example of an emotional brand. It made sportswear accessible to non-sports people with a brand story that inspired not just success but energy and determination. Marc says that it is important to evaluate visual codes and emotional stimuli associated with brands and their competitors, to determine how consumers experience brands on a sensory level. What he does not do is ask consumers to describe their own feelings about brands and visual stimuli, recalling famous brands like Absolut and Red Bull that have flopped in focus groups: It is very difficult to ask consumers, particularly in that kind of environment that is not conducive to imagination, about what they feel. I think consumers are not honest all the time and we are limited by the words that we use to express the emotions we have. It is very difficult to truly understand what it is that consumers really will accept in their lives, particularly when it comes to innovation.

As well as understanding how participants may react to particular issues, researchers should also understand how the context or environment may affect participants. The following examples illustrate why ‘context’ is so important when thinking about where participants are questioned and/or observed. The first example sets out ideas of how to experiment with different contexts in which to conduct qualitative interviews. The second example questions the context in which focus groups are conducted and the possible impact of context upon participant engagement, reflection and honesty.

Real research

Taxis, vans and subways: capturing insights while commuting14 The Mexican research company Insitum (www.insitum.com) has been experimenting with new ways to conduct qualitative research by reaching consumers in their own context instead of making them move to a local facility and participate in a study. The company tried three approaches: 1 Designing and implementing a research taxi in which participants are taken to their destination while they participate in an interview conducted by the researcher–driver. 2 Moderating focus group sessions inside a private van in which passengers participate while they travel from a suburb to the city centre. 3 Conducting shadowings (observations and interviews) with subway passengers during their home–work commute. The three approaches had mixed results and opportunities for improvement, with clear logistical challenges. However, they all successfully developed new insights of consumers who were happy to discuss issues and be observed in contexts that they felt ‘comfortable’ in.

Chapter 3 Research design

As a further example, return to the first level of Figure 3.1, where participants may be more relaxed and feel in control if they can answer the set questions about their newspaperreading habits online rather than on the street. In the example at the start of this chapter, which explored the hopes and dreams of ‘emergent drinkers’, techniques were used at the third and fourth levels of Figure 3.1. The context of the interviews was in ‘leading-edge bars’. This context could have helped the target participants to relax, to develop a better rapport with interviewers and other participants and to think more about the issues and express their feelings more clearly. If the interviews were conducted online, the same levels of relaxation and rapport might not work so well. If the interviews were targeted at older participants, they would have felt very self-conscious in ‘leading-edge bars’, which might restrict their responses. Researchers therefore must understand the characteristics of participants, how they react to particular issues and how they react in different contexts or environments. These factors are illustrated in Figure 3.2, which acts as a reminder of the understanding of participants that researchers must develop in order to choose and apply the best research technique. Figure 3.2 Context or environment where participant is questioned

Understanding participants – to help choose optimum research techniques

Nature of issue under investigation, as perceived by participant

Nature of participant

Research design classification Exploratory research A research design characterised by a flexible and evolving approach to understanding marketing phenomena that are inherently difficult to measure.

Conclusive research A research design characterised by the measurement of clearly defined marketing phenomena.

Research designs may be broadly classified as exploratory or conclusive (see Figure 3.3). The differences between exploratory research and conclusive research are summarised in Table 3.1. The primary objective of exploratory research is to provide insights into and an understanding of marketing phenomena.15 It is used in instances where the subject of the study cannot be measured in a quantitative manner, or where the process of measurement cannot realistically represent particular qualities. For example, if a researcher was trying to understand what ‘atmosphere’ meant in a restaurant, exploratory research may help to establish all the appropriate variables and how they connect together. What role did music play? What type of music? How loud? What types of furniture? What colours and textures? What types of lighting? What architectural features? This list could go on to consider what ‘atmosphere’ may mean in the context of a restaurant experience for particular types of consumer. ‘Atmosphere’ may not be measurable from the participant’s perspective. From the perspective of the creative director in an advertising agency, quantitative measurements of the individual components of ‘atmosphere’ may not create the holistic feel of a restaurant in a manner the creative director can relate to. Exploratory research may also be used in cases where the problem must be defined more precisely, relevant courses of action identified, or additional insights gained before going on to confirm findings using a conclusive design. The following example of researching the psychology of voting illustrates how the different approaches to research can be combined within a single study.

Marketing Research

Figure 3.3

Research design

A classification of marketing research designs

Conclusive design

Exploratory design

Qualitative exploration

Quantitative exploration

Descriptive research

Cross-sectional design

Single cross-sectional

Table 3.1

Longitudinal design

Multiple cross-sectional

Differences between exploratory and conclusive research Exploratory

Objectives

Characteristics

Conclusive

To provide insights and understanding To test specific hypotheses and examine of the nature of marketing phenomena relationships To understand

To measure

Information needed may be loosely defined

Information needed is clearly defined

Research process is flexible, unstructured and may evolve Samples are small Data analysis can be qualitative or quantitative Findings/results Can be used in their own right

Methods

Causal research

Research process is formal and structured Sample is large and aims to be representative Data analysis is quantitative

Can be used in their own right

May feed into conclusive research

May feed into exploratory research

May illuminate specific conclusive findings

May set a context to exploratory findings

Expert surveys

Surveys

Pilot surveys

Secondary data

Databases

Qualitative interviews

Panels

Unstructured observations

Structured observations

Quantitative exploratory multivariate methods

Experiments

Chapter 3 Research design

Real research

Getting inside the minds of European voters16 Around the world, countries face a challenge with falling participation in elections and a sense of alienation felt by citizens in response to the actions of their governments. Researchers at Opinium Research (www.opinium.co.uk) and The London School of Economics (www. lse.ac.uk) have been undertaking a multi-year study to get inside the mind of voters across 12 European countries. The goal of this research, ‘entitled’ Inside the mind of the vote’, is to build a better understanding of the psychology of the voting process itself. In order to address this challenging research problem project, a very broad range of data collection techniques were built into the research design. The research design involved both qualitative and quantitative data collection approaches, including: •

Multi-wave quantitative surveys

•

In-depth interviews

•

Experiments

•

Diary techniques

•

Observational techniques in polling stations.

The complexity of the research design generated a number of challenges in analysing the research, which had to be overcome. One approach to dealing with combining qualitative and quantitative data sources is to ensure that there is a ‘bridge’ between the different methods. For example, including open-ended questions in surveys that link to the themes used in interviews, or using questionnaire items in diary entries. This helped to triangulate the data and identify potential sources of bias. The study generated a number of insights about the voting process itself. For example, the high levels of voters who change their mind in the week before an election and the role of emotions in the voting process. This unique research design has resulted in a number of important impacts upon public policy, both within the European Commission and in individual European governments.

In an example of a flexible, loosely structured and evolutionary approach, consider conducting personal interviews with industry experts. The sample, selected to generate maximum insight, is small and non-representative. However, the emphasis in the sampling procedure is focused upon ‘quality’ individuals who are willing to open up, use their imagination, be creative and reveal perhaps sensitive thoughts and behaviour. ‘Quality’ also may emerge from their level of expertise; for example, there may only be a small population of chief executives of airline companies in Europe. If a small sample of, say, six chief executives from the largest and fastest-developing airlines allowed access to a researcher and revealed their attitudes and behaviour, insights might be gained that no conclusive study could achieve. By being flexible in the issues to discuss, loosely structured in how probes and additional issues emerge and evolutionary in the nature of who to talk to and the best context in which to gain their confidence and get them to express what they really feel, an exploratory design can be very beneficial.

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There is an exception to exploratory designs being built around qualitative techniques. There are examples of quantitative findings being used for exploratory purposes. For example, within a survey that examines specific research questions and hypotheses lies the opportunity to examine additional connections between questions that had not been initially considered. Simple correlations through to multivariate techniques that explore potential connections between questions may be conducted; this process is known as data mining. In essence, data mining searches for significant connections or patterns in a dataset that a researcher or decision maker may be unaware of. To summarise, exploratory research is meaningful in any situation where the researcher does not have enough understanding to proceed with the research project. Exploratory research is characterised by flexibility and versatility with respect to the methods, because formal research protocols and procedures are not employed. It rarely involves structured questionnaires, large samples and probability sampling plans. Rather, researchers are alert to new ideas and insights as they proceed. Once a new idea or insight is discovered, they may redirect their exploration in that direction. That new direction is pursued until its possibilities are exhausted or another direction is found. For this reason, the focus of the investigation may shift constantly as new insights are discovered. Thus, the creativity and ingenuity of the researcher play a major role in exploratory research. Exploratory research can be used for any of the purposes listed in Table 3.2.

Table 3.2

A summary of the uses of exploratory research designsa

1 To obtain some background information where absolutely nothing is known about the problem area 2 To define problem areas fully and to formulate hypotheses for further investigation and/or quantification 3 To identify and explore concepts in the development of new products or forms of marketing communications 4 During a preliminary screening process, such as in new-product development, in order to reduce a large number of possible projects to a smaller number of probable ones 5 To identify relevant or salient behaviour patterns, beliefs, opinions, attitudes, motivations, etc., and to develop structures of these constructs 6 To develop an understanding of the structure of beliefs and attitudes in order to aid the interpretation of data structures in multivariate data analyses 7 To explore the reasons that lie behind the statistical differences between groups that may emerge from secondary data or surveys 8 To explore sensitive or personally embarrassing issues from the participants’ and/or the interviewer’s perspective 9 To explore issues that participants may feel deeply about, that are difficult for them to rationalise and that they may find difficult to articulate 10 To ‘data-mine’ or explore quantitative data to reveal hitherto unknown connections between different measured variables

The objective of conclusive research is to describe specific phenomena, to test specific hypotheses and to examine specific relationships. This requires that the information needed is clearly specified.17 Conclusive research is typically more formal and structured than exploratory research. It is based on large, representative samples, and the data obtained are subjected to quantitative analysis. Conclusive research can be used for any of the purposes listed in Table 3.3.

Chapter 3 Research design

As shown in Figure 3.3, conclusive research designs may be either descriptive or causal, and descriptive research designs may be either cross-sectional or longitudinal. Each of these classifications is discussed further, beginning with descriptive research. Table 3.3

A summary of the uses of conclusive research designs

1 To describe the characteristics of relevant groups, such as consumers, salespeople, organisations, or target market 2 To estimate the percentage in a specified population exhibiting a certain form of behaviour 3 To count the frequency of events, especially in the patterns of consumer behaviour 4 To measure marketing phenomena to represent larger populations or target markets 5 To be able to integrate findings from different sources in a consistent manner, especially in the use of marketing information systems and decision support systems 6 To determine the perceptions of product or service characteristics 7 To compare findings over time that allow changes in the phenomena to be measured 8 To measure marketing phenomena in a consistent and universal manner 9 To determine the degree to which marketing variables are associated 10 To make specific predictions

Descriptive research Descriptive research A type of conclusive research that has as its major objective the description of something, usually market characteristics or functions.

As the name implies, the major objective of descriptive research is to describe something – usually market characteristics or functions.18 A major difference between exploratory and descriptive research is that descriptive research is characterised by the prior formulation of specific research questions and hypotheses. Thus, the information needed is clearly defined. As a result, descriptive research is preplanned and structured. It is typically based on large representative samples. A descriptive research design specifies the methods for selecting the sources of information and for collecting data from those sources. Examples of descriptive studies in marketing research are as follows: •

•

• • •

•

Market studies describing the size of the market, buying power of the consumers, availability of distributors and consumer profiles. Market-share studies determining the proportion of total sales received by a company and its competitors. Sales analysis studies describing sales by geographic region, product line, type of account and size of account. Image studies determining consumer perceptions of the firm and its products. Product usage studies describing consumption patterns. Distribution studies determining traffic-flow patterns and the number and location of distributors. Pricing studies describing the range and frequency of price changes and probable consumer response to proposed price changes. Advertising studies describing media consumption habits and audience profiles for specific TV programmes and magazines.

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Cross-sectional design A type of research design involving the collection of information only once from any given sample of population elements.

Single cross-sectional design A cross-sectional design in which one sample of participants is drawn from the target population and information is obtained from this sample only once.

Multiple crosssectional design A cross-sectional design in which there are two or more samples of participants, and information from each sample is obtained only once.

Real research

These examples demonstrate the range and diversity of descriptive research studies. Descriptive research can be further classified into cross-sectional and longitudinal research (Figure 3.3).

Cross-sectional designs The cross-sectional study is the most frequently used descriptive design in marketing research. Cross-sectional designs involve the collection of information only once from any given sample of population elements. They may be either single cross-sectional or multiple cross-sectional (Figure 3.3). In single cross-sectional designs, only one sample of participants is drawn from the target population, and information is obtained from this sample only once. These designs are also called sample survey research designs. In multiple cross- sectional designs, there are two or more samples of participants, and information from each sample is obtained only once. Often, information from different samples is obtained at different times. The following examples illustrate single and multiple cross-sectional designs respectively.

Television motivations19 Much marketing research is directed at understanding the ‘drivers’ of consumer behaviour. Corning is a leading specialist manufacturer of glass products, perhaps best known for its role in providing screens for the iPhone, iPad and other mobile devices. In a study commissioned by Corning Display Technologies (www.corning.com), the motivations for choosing a new TV were measured. An online survey of 2,500 respondents in China, France, Germany, Japan, the UK and USA was administered. Qualitative research grounded in motivational theory underpinned the survey. The qualitative research suggested a number of consumer concerns and interests that might have an impact on TV preferences, especially across the countries being studied. This knowledge was used to develop a list of concerns and interests that could encompass selection and use of a TV set. The survey included a discrete choice exercise to measure preferences for different types of TV sets. The survey also contained a list of TV viewing occasions and activities, and participants were asked to indicate the frequency of each occasion for their households. Participants selected three viewing activities or occasions that would be most important to their choice of a TV set. To be part of the survey, participants had to indicate a likelihood of purchasing an LCD TV in the next four years.

Real research

Life cycle, objective and subjective living standards and life satisfaction – multiple cross-sectional design20 Centrum Badania Opinii Spotecznej (CBOS) (www.cbos.pl) is a major Polish polling centre, a non-governmental foundation, whose main goal is to conduct a monthly survey of public opinion on all important current problems and events. The centre wished to build a composite measure of living conditions, based upon household material wealth and life satisfaction. In order to do this it conducted seven surveys in Poland between 1992 and 2004. Through 2003 the surveys were conducted on stratified probability random samples of Polish addresses. The data from all surveys were weighted to assure their representativeness in respect of the main socio-demographic characteristics of the

Chapter 3 Research design

opulation. Satisfaction with various aspects of life was also investigated many times p during the 1992–2004 period. However, only once, in September 1999, was it included in the same survey together with the questions on household possessions. Effective sample sizes were 1,788 in 1992, 1,222 in 1994, 1,177 in 1996, 1,167 in 1998, 1,092 in 1999, 1,060 in 2002, 1,057 in 2003 and 1,022 in 2004.

Cohort analysis A multiple cross-sectional design consisting of surveys conducted at appropriate time intervals. The cohort refers to the group of participants who experience the same event within the same time interval.

Table 3.4

The survey devoted to measuring motivations of TV purchases, a single cross-sectional design, involved only one group of participants who provided information only once. On the other hand, the Polish study involved eight different samples, each measured only once, with the measures generally obtained two years apart. Hence, the latter study illustrates a multiple crosssectional design. A type of multiple cross-sectional design of special interest is cohort analysis. Cohort analysis consists of a series of surveys conducted at appropriate time intervals, where the cohort serves as the basic unit of analysis. A cohort is a group of participants who experience the same event within the same time interval.21 For example, a birth (or age) cohort is a group of people who were born during the same time interval, such as 1951–1960. The term ‘cohort analysis’ refers to any study in which there are measures of some characteristics of one or more cohorts at two or more points in time. It is unlikely that any of the individuals studied at time 1 will also be in the sample at time 2. For example, the age cohort of people between 8 and 19 years was selected, and their softdrink consumption was examined every 10 years for 30 years. In other words, every 10 years a different sample of participants was drawn from the population of those who were then between 8 and 19 years old. This sample was drawn independently of any previous sample drawn in this study from the population of people aged 8 to 19 years. Obviously, people who were selected once were unlikely to be included again in the same age cohort (8 to 19 years), as these people would be much older at the time of subsequent sampling. This study showed that this cohort had increased consumption of soft drinks over time. Similar findings were obtained for other age cohorts (20–29, 30–39, 40–49 and 50+). Further, the consumption of each cohort did not decrease as the cohort aged. These results are presented in Table 3.4, in which the consumption of the various age cohorts over time can be determined by reading down the diagonal. These findings contradict the common belief that the consumption of soft drinks will decline with the greying of Western economies. This common but erroneous belief has been based on single cross-sectional studies. Note that if any column of Table 3.4 is viewed in isolation (as a single cross-sectional study) the consumption of soft drinks declines with age, thus fostering the erroneous belief.22

Consumption of soft drinks by various age cohorts (percentage consuming on a typical day)

Age

1950

1960

1970

8–19 20–29 30–39 40–49 50+

53 45 34 23 18

63 61 47 41 29 C1

73 76 68 59 50 C2

C1: cohort born prior to 1900 C2: cohort born 1901–1910 C3: cohort born 1911–1920

C4: cohort born 1921–1930 C5: cohort born 1931–1940 C6: cohort born 1941–1950

1980 81R 76R 71R 68R 52R C3 C7: cohort born 1951–1960 C8: cohort born 1961–1970

C8 C7 C6 C5 C4

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Cohort analysis can also be used to predict changes in voter opinions during a political campaign. Well-known researchers such as YouGov (www.yougov.com) or Ipsos MORI (www.ipsos-mori.com), who specialise in political opinion research, periodically question cohorts of voters (people with similar voting patterns during a given interval) about their voting preferences in order to predict election results. Thus, cohort analysis is an important cross-sectional design, as illustrated in the following example, which builds on the previous example of the Polish polling centre CBOS.

Real research

Longitudinal design A type of research design involving a fixed sample of population elements measured repeatedly. The sample remains the same over time, thus providing a series of pictures that, when viewed together, vividly illustrate the situation and the changes that are taking place.

Real research

Life cycle, objective and subjective living standards and life satisfaction – cohort analysis23 Cohort analysis of the household material wealth and life satisfaction in Poland allowed joint examination of the impacts of age, time and period of being born. It can be said that, though age-related differences were similar in each survey, between-survey differences suggested that material wealth was rapidly growing in time. This growth was evidently faster in young groups than in older ones, so the youth benefited the most from the changes. In addition, accumulated wealth was evidently much smaller in older age groups. That may bring an inexperienced researcher to a completely false conclusion that after a short period of acquiring wealth, people get rid of it rather than accumulate it in time. Thus, cohort analysis can be indispensable in properly examining the changes in wealth during the span of life.

Longitudinal designs The other type of descriptive design is longitudinal design. In a longitudinal design, a fixed sample (or samples) of population elements is measured repeatedly, as in the following example at Philips.

True Loyalty24 True Loyalty is a large-scale joint research project developed by Philips (www.philips. com) and Interview NSS (www.interview-nss.com). The project aims to measure the actual sales effect of consumers’ experiences with Philips Consumer Lifestyle. The project was influenced by the work of Frederick Reichheld,25 who developed the concept of ‘Net Promotor Score’ (NPS), which has become a widely used loyalty metric in many leading companies. Unlike most studies using the NPS, True Loyalty decided to set up a single-source longitudinal survey. Customers from whom it had obtained satisfaction and recommendation scores via ongoing research projects were recontacted 9 to 18 months later and both their purchases and those of friends and colleagues were assessed. The database consisted of over 25,000 recontacted customers.

A longitudinal design differs from a cross-sectional design in that the sample or samples remain the same over time. In other words, the same people are studied over time. In contrast to the typical cross-sectional design, which gives a snapshot of the variables of interest at a single point in time, a longitudinal study provides a series of ‘pictures’. These ‘pictures’ give an in-depth view of the situation and the changes that take place over time. For example, the

Chapter 3 Research design

Panel A sample of participants who have agreed to provide information at specified intervals over an extended period.

Access panel A general ‘pool’ of individuals or households who have agreed to be available for surveys of widely varying types and topics.

question ‘How did the German people rate the performance of German Chancellor Angela Merkel in 2016?’ would be addressed using a cross-sectional design. A longitudinal design, however, would be used to address the question ‘How did the German people change their view of Merkel’s performance during her term of office?’. Often, the term ‘panel’ is used in conjunction with the term ‘longitudinal design’. A panel consists of a sample of participants, generally households, who have agreed to provide general or specific information at set intervals over an extended period. The emphasis of the panel is on measuring facts, e.g. who in the household bought what, where they bought it, when, and other aspects of their behaviour. Panels are really only established when observations or measurements over an extended period are meaningful. The observations are usually gathered through questionnaires, such as purchase diaries, or increasingly through social media methods. Panels are maintained by syndicated firms, such as TNS (www.tnsglobal. com) and panel members are compensated for their participation with gifts, coupons, information or cash.26 Access panels are made up of a ‘pool’ of individuals or households who have agreed to be available for surveys of widely varying types and topics.27 They are used to provide information for ad hoc decisions rather than for longitudinal studies – a typical use being for newproduct testing. A pre-recruited panel that is willing to participate makes it easier to set up the test and conduct interviews after the test. Access panels are also used to test concepts, advertising and pricing decisions. Online consumer access panels are becoming increasingly prevalent in marketing research.28 The growth in use of access panels has partly been in response to the challenges of rising rates of non-response or refusal to take part in surveys. The growth of online surveys and the need for electronic addresses of willing participants have also favoured the use of access panels. (Given this growth and prevalence, we will further address access panels in Chapters 4, 10 and 14.) The industry moves forward at such a fast pace that samples can easily be left behind. Frequency of internet usage is a classic example; what people were doing 12 or even 6months ago will be different to what they are doing now. In a fast-moving research sector it is important to keep up to date with the latest gadgets, technologies and service offerings, and to keep the panel updated with these.

Relative advantages and disadvantages of longitudinal and cross-sectional designs The relative advantages and disadvantages of longitudinal versus cross-sectional designs are summarised in Table 3.5. A major advantage of longitudinal design over cross-sectional design is the ability to detect change as a result of repeated measurement of the same variables on the same sample. Tables 3.6 and 3.7 demonstrate how cross-sectional data can mislead researchers about changes over time. The cross-sectional data reported in Table 3.6 reveal that the purchases of Brands A, B and C remained the same in periods 1 and 2. In each survey, 20% of the participants purchased Brand A, 30% Brand B and 50% Brand C. The longitudinal data presented in Table 3.7 show that substantial change, in the form of brand switching, occurred in the study period. For example, only 50% (100/200) of the participants who purchased Brand A in period 1 also purchased it in period 2. The corresponding repeat-purchase figures for Brands B and C are, respectively, 33.3% (100/300) and 55% (275/500). Hence, during this interval Brand C experienced the greatest loyalty and Brand B the least. Table 3.7 provides valuable information on brand loyalty and brand switching (such a table is called a turnover table or a brand-switching matrix).29 Longitudinal data enable researchers to examine changes in the behaviour of individual units and to link behavioural changes to marketing variables, such as changes in advertising, packaging, pricing and distribution. Since the same units are measured repeatedly, variations caused by changes in the sample are eliminated, and even small variations become apparent.

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Another advantage of panels is that relatively large amounts of data can be collected. Because panel members are usually compensated for their participation, they are willing to participate in lengthy and demanding interviews. Yet another advantage is that panel data can be more accurate than cross-sectional data. A typical cross-sectional survey requires the participant to recall past purchases and behaviour; these data can be inaccurate because of memory lapses. Panel data, which might involve continuous recording of purchases in a diary, place less reliance on the participant’s memory. A comparison of panel and cross-sectional survey estimates of retail sales indicates that panel data give more accurate estimates.30

Table 3.5

Relative advantages and disadvantages of longitudinal and cross-sectional designs

Evaluation criteria

Cross-sectional design

Longitudinal design

− − − + +

+ + + − −

Detecting change Large amount of data collection Accuracy Representative sampling Response bias

Note: + indicates a relative advantage over the other design, whereas – indicates a relative disadvantage.

Table 3.6

Cross-sectional data may not show change Time period

Brand purchased

Period 1 survey

Period 2 survey

1,000 200 300 500

Total surveyed Brand A Brand B Brand C

Table 3.7

Longitudinal data may show substantial change Brand purchased in period 2

Brand purchased in period 1 Total surveyed Brand A Brand B Brand C

Brand A

Brand B

Brand C

Total

200 100 25 75

300 50 100 150

500 50 175 275

1,000 200 300 500

Chapter 3 Research design

The main disadvantage of panels is that they may not be representative. Non-representativeness may arise because of the following: 1 Refusal to cooperate. Many individuals or households do not wish to be bothered with the panel operation and refuse to participate. Consumer panels requiring members to keep a record of purchases have a cooperation rate of 60% or less. 2 Dropout. Panel members who agree to participate may subsequently drop out because they move away or lose interest. Dropout rates can be as high as 20% per year.31 3 Payment. Payment may cause certain types of people to be attracted, making the group unrepresentative of the population. 4 Professional participants. Most concerns about representativeness arise from the claim that research panels generate ‘professional’ participants. ‘Panel conditioning’ is the term used to describe the effect of participants who engage with a number of surveys over time and on a regular basis. Their self-reported attitudes and behaviours can be shaped by what they feel is the type of response expected of them.32 Another disadvantage of panels is response bias. New panel members are often biased in their initial responses. They tend to increase the behaviour being measured, such as food purchasing. This bias decreases as the participant overcomes the novelty of being on the panel, so it can be reduced by initially excluding the data of new members. Bias also results from boredom, fatigue and incomplete diary entries.33 The following example from the marketing research agency Taylor Nelson Sofres (TNS) illustrates how it copes with potential panel bias.

Rubbish in, rubbish out34

Real research

Research firms such as TNS (www.tnsglobal. com) spend a lot of money on recruiting participants to online panels – if the quality of participants is rubbish so will be the research! As part of the ESOMAR Project Team on online panels, TNS has been looking at how to define a well-recruited panel. For TNS, a panel is recruited from multiple sources with the panellist’s details verified. Care must be taken to account for the differences between the type of people who take part in online panels and those who do not, to ensure that the panel is truly representative. TNS deals with this issue by running parallel studies to make sure that online panellists are responding in the same way online as they would offline. If a bias is found, the results are calibrated to account for it. In this respect, online is no different from any other form of research.

Causal research Causal research A type of conclusive research where the major objective is to obtain evidence regarding cause-and-effect (causal) relationships.

Causal research is used to obtain evidence of cause-and-effect (causal) relationships. Marketing managers continually make decisions based on assumed causal relationships. These assumptions may not be justifiable, and the validity of the causal relationships should be examined via formal research.35 For example, the common assumption that a decrease in price will lead to increased sales and market share does not hold in certain competitive environments. Causal research is appropriate for the following purposes:

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1 To understand which variables are the cause (independent variables) and which variables are the effect (dependent variables) of marketing phenomena. 2 To determine the nature of the relationship between the causal variables and the effect to be predicted. 3 To test hypotheses. Like descriptive research, causal research requires a planned and structured design. Although descriptive research can determine the degree of association between variables, it is not appropriate for examining causal relationships. Such an examination requires a causal design, in which the causal or independent variables are manipulated in a relatively controlled environment. Such an environment is one in which the other variables that may affect the dependent variable are controlled or checked as much as possible. The effect of this manipulation on one or more dependent variables is then measured to infer causality. The main method of causal research is experimentation.36 (Due to the complexity and importance of this subject, Chapter 11 has been devoted to causal research designs.)

Relationships between exploratory, descriptive and causal research We have described exploratory, descriptive and causal research as major classifications of research designs, but the distinctions among these classifications are not absolute. A given marketing research project may involve more than one type of research design and thus serve several purposes as illustrated in the following example.

Real research

Italians and Americans face each other at dinner37 The ways in which we select, prepare and consume foods are tied to the habits and customs that define a people in their place and time. The foods that are valued and enjoyed are linked to circumstances of availability, tradition, self-image and cultural transference. In research commissioned by Barilla Alimentare (www.barillagroup.com), Hy Mariampolski and Sharon Wolf (www.qualidataresearch.com) studied ideas about the ‘Italianness’ influence on foods eaten in the USA, alongside a contrasting study of attitudes toward American foods eaten in Italy conducted by Luigi Toiati (www.focusresearch.it). Italian food in the USA, while being seen as an essential part of American cuisine, has been losing its previous cachet. Competing against other cuisines, particularly Asian and Mexican meals, Italian foods have been riddled with unhelpful ideas emanating from popular cultural steroetypes: that Italian meals consist of enormous quantities of pasta heavily sauced with cheese and meaty red tomato purée. These myths tend to reduce Italian foods as downscale and inappropriate for low-carbohydrate diets. Italy, too, has its own complex mythology regarding the USA and its cuisine: that it consists of heaping portions of food that are mediocre at best, over processed, lacking tradition, fattening and eaten too hastily. The general conclusion is that ‘America is a country worth visiting, but where it’s not worth eating’. In the Italian mind, overweight Americans stuff themselves with anonymous, monotonous food, simply eating for eating’s sake with no regard for taste! The researchers wanted to help reverse these disparaging stereotypes. Digging deeply into the meaning of ‘authenticity’ and seeking positive and constructive aspects of the national mythologies helped to secure consumer insights that promoted

Chapter 3 Research design

c onsumption of Italian brands in the USA and American foods in Italy. The methods used in this study of food culture were: semiotic analysis of media images to gain insights into the ideas communicated about Italy and the USA in popular culture; in-depth interviews with experts and influential consumers; ethnographic home visits to see how ideas about the foods of each culture were expressed in meal preparation; focus group discussions to explore emerging ideas; and descriptive, face-to-face street interviews.

Which combination of research designs to employ depends on the nature of the problem. We offer the following general guidelines for choosing research designs: 1 When little is known about the problem situation, it is desirable to begin with exploratory research. Exploratory research is appropriate for the following: a When the nature of the topic under study cannot be measured in a structured, quantifiable manner. b When the problem needs to be defined more precisely. c When alternative courses of action need to be identified. d When research questions or hypotheses need to be developed. e When key variables need to be isolated and classified as dependent or independent. 2 Exploratory research may be an initial step in a research design. It may be followed by descriptive or causal research. For example, hypotheses developed via exploratory research can be statistically tested using descriptive or causal research. 3 It is not necessary to begin every research design with exploratory research. It depends on the precision with which the problem has been defined and the researcher’s degree of certainty about the approach to the problem. A research design could well begin with descriptive or causal research. To illustrate, a consumer satisfaction survey that is conducted annually need not begin with or include an exploratory phase. 4 Although exploratory research is generally the initial step, it need not be. Exploratory research may follow descriptive or causal research. For example, descriptive or causal research can result in findings that are hard for managers to interpret. Exploratory research may provide more insights to help understand these findings. The relationships between exploratory, descriptive and causal research are further illustrated by the following example.

Real research

Using insight to improve telephone banking customer satisfaction at Natwest Financial services firms face increasing challenges to retain their customers. With many customers shifting their banking to digital channels, and pressure to manage costs, it is not surprising that telephone banking services could be seen as a declining channel. As a result, leading UK bank Natwest, like many other banks, developed processes to try and stop customers calling their online phone service and ensure any calls there were made kept short. For example, Natwest had a target that 90% of calls should be completed within 60 seconds.

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Working with leading research firm KPMG Nunwood38, Natwest ran a continuous tracking programme that interviewed 4,000 customers, alongside 2,000 customers of Natwest’s competitors each month. Researchers made use of a research method known as ‘critical incident technique’ (CIT), which involves research participants telling stories about specific experiences (‘incidents’) related to use of a product or service. This research generated insights in two important areas. Firstly, Natwest found it had some of the lowest customer satisfaction ratings for any bank telephone service. Secondly, far from being unimportant, telephone banking was often the point of contact where customers were most in need of help. To address these issues qualitative research was augmented with quantitative analysis of customer verbatim comments using textual analysis software. The output resulted in a new call model for delivering a high-quality customer experience over the telephone, and a dramatic increase in customer satisfaction.

Examples of multi-method research designs can be criticised for taking too long to undertake, being too expensive and perhaps applying too many techniques that do not offer sufficient additional understanding. Such criticism cannot really be addressed without knowing the value that decision makers may get from this decision support (not just at the end, but at the many stages of research as it unfolds), compared with how much they would have to pay for it. Decision makers can receive interim reports and feed back their ideas to give more focus to the issues and types of participant in subsequent stages. The example also illustrates that researchers can be very creative in their choice of techniques that combine to make up a research design.

Potential sources of error in research designs

Total error The variation between the true mean value in the population of the variable of interest and the observed mean value obtained in the marketing research project.

Random sampling error The error arising because the particular sample selected is an imperfect representation of the population of interest. It may be defined as the variation between the true mean value for the sample and the true mean value of the population.

Non-sampling error An error that can be attributed to sources other than sampling and that can be random or nonrandom.

Several potential sources of error can affect a research design. A good research design attempts to control the various sources of error. Although these errors are discussed in detail in subsequent chapters, it is pertinent at this stage to give brief descriptions. Where the focus of a study is a quantitative measurement, the total error is the variation between the true mean value in the population of the variable of interest and the observed mean value obtained in the marketing research project. For example, the annual average income of a target population may be 85,650, as determined from census information via tax returns, but a marketing research project estimates it at 62,580 based upon a sample survey. As shown in Figure 3.4, the total error (in the above case 23,070) is composed of random sampling error and non-sampling error.

Random sampling error Random sampling error occurs because the particular sample selected is an imperfect representation of the population of interest. Random sampling error is the variation between the true mean value for the population and the true mean value for the original sample. (Random sampling error is discussed further in Chapters 14 and 15.)

Non-sampling error Non-sampling errors can be attributed to sources other than sampling, and may be random or non-random. They result from a variety of reasons, including errors in problem definition, approach, scales, questionnaire design, interviewing methods and data preparation and analysis. Non-sampling errors consist of non-response errors and response errors.

Chapter 3 Research design

Figure 3.4

Total error

Potential sources of error in research designs Random sampling errors

Non-response error A type of non-sampling error that occurs when some of the participants included in the sample do not respond. This error may be defined as the variation between the true mean value of the variable in the original sample and the true mean value in the net sample.

Response error A type of non-sampling error arising from participants who do respond but who give inaccurate answers or whose answers are mis-recorded or mis-analysed. It may be defined as a variation between the true mean value of the variable in the net sample and the observed mean value obtained in the market research project.

Non-sampling errors

Response errors

Non-response errors

Researcher errors

Interviewer errors

Participant errors

• Surrogate information • Measurement • Population definition • Sampling frame • Data analysis

• Participant selection • Questioning • Recording • Cheating

• Inability • Unwillingness

A non-response error arises when some of the participants included in the sample simply do not respond. The primary causes of non-response are refusals and not-at-homes (see Chapter 15). Non-response will cause the net or resulting sample to be different in size or composition from the original sample. Non-response error is defined as the variation between the true mean value of the variable in the original sample and the true mean value in the net sample. Response error arises when participants give inaccurate answers, or their answers are misrecorded or mis-analysed. Response error is defined as the variation between the true mean value of the variable in the net sample and the observed mean value obtained in the marketing research project. Response error is determined not only by the non-response percentage, but also by the difference between participants and those who failed to cooperate, for whatever reason, as response errors can be made by researchers, interviewers or participants.39 A central question in evaluating response error is whether those who participated in a survey differ from those who did not take part, in characteristics relevant to the content of the survey.40 Response errors made by the researcher include surrogate information, measurement, population definition, sampling frame and data analysis errors: •

•

Surrogate information error may be defined as the variation between the information needed for the marketing research problem and the information sought by the researcher. For example, instead of obtaining information on consumer choice of a new brand (needed for the marketing research problem), the researcher obtains information on consumer preferences because the choice process cannot be easily observed. Measurement error may be defined as the variation between the information sought and information generated by the measurement process employed by the researcher. While seeking to measure consumer preferences, the researcher employs a scale that measures perceptions rather than preferences.

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•

Real research

Population definition error may be defined as the variation between the actual population relevant to the problem at hand and the population as defined by the researcher. The problem of appropriately defining the population may be far from trivial, as illustrated by the following example of affluent households. Their number and characteristics varied depending on the definition, underscoring the need to avoid population definition error. Depending upon the way the population of affluent households was defined, the results of this study would have varied markedly.

How affluent is affluent? The population of the affluent households was defined in four different ways in a study: 1 Households with an income of €80,000 or more. 2 The top 20% of households, as measured by income. 3 Households with net worth over €450,000. 4 Households with discretionary income to spend being 30% higher than that of comparable households.

•

Sampling frame error may be defined as the variation between the population defined by the researcher and the population as implied by the sampling frame (list) used. For example, the telephone directory used to generate a list of telephone numbers does not accurately represent the population of potential landline consumers due to unlisted, disconnected and new numbers in service. It also misses out the great number of consumers who choose not to have landlines, exclusively using mobile phones. Data analysis error encompasses errors that occur while raw data from questionnaires are transformed into research findings. For example, an inappropriate statistical procedure is used, resulting in incorrect interpretation and findings.

Response errors made by the interviewer include participant selection, questioning, recording and cheating errors: •

•

Participant selection error occurs when interviewers select participants other than those specified by the sampling design, or in a manner inconsistent with the sampling design. Questioning errors denotes errors made when asking questions of the participants, or in not probing when more information is needed. For example, while asking questions an interviewer does not use the exact wording or prompts as set out in the questionnaire. Recording error arises due to errors in hearing, interpreting and recording the answers given by the participants. For example, a participant indicates a neutral response (undecided) but the interviewer misinterprets that to mean a positive response (would buy the new brand). Cheating error arises when the interviewer fabricates answers to a part or the whole of the interview. For example, an interviewer does not ask the sensitive questions related to a participant’s debt but later fills in the answers based on personal assessment.

Response errors made by the participant comprise errors of inability and unwillingness: •

Inability error results from the participant’s inability to provide accurate answers. Participants may provide inaccurate answers because of unfamiliarity, fatigue, boredom, question format, question content or because the topic is buried deep in the participant’s mind. An example of inability error is where a participant cannot recall the brand of toothpaste he or she purchased four weeks ago.

Chapter 3 Research design

•

Unwillingness error arises from the participant’s unwillingness to provide accurate information. Participants may intentionally misreport their answers because of a desire to provide socially acceptable answers, because they cannot see the relevance of the survey and/or a question posed, to avoid embarrassment or to please the interviewer.41 For example, to impress the interviewer a participant intentionally says that he or she reads The Economist magazine.

These sources of error are discussed in more detail in subsequent chapters; what is important here is that there are many sources of error. In formulating a research design, the researcher should attempt to minimise the total error, not just a particular source. This admonition is warranted by the general tendency among naïve researchers to control sampling error by using large samples. Increasing the sample size does decrease sampling error, but it may also increase non-sampling error, e.g. by increasing interviewer errors. Non-sampling error is likely to be more problematic than sampling error. Sampling error can be calculated, whereas many forms of non-sampling error defy estimation. Moreover, non-sampling error has been found to be the major contributor to total error, whereas random sampling error is relatively small in magnitude. The point is that researchers must not lose sight of the impact of total error upon the integrity of their research design and the findings they present. A particular type of error is important only in that it contributes to total error. Sometimes, researchers deliberately increase a particular type of error to decrease the total error by reducing other errors. For example, suppose that a mail survey is being conducted to determine consumer preferences in purchasing shoes from a chain of specialist shoe shops. A large sample size has been selected to reduce sampling error. A response rate of 30% may be expected. Given the limited budget for the project, the selection of a large sample size does not allow for follow-up mailings. Past experience, however, indicates that the response rate could be increased to 45% with one follow-up mailing and to 55% with two follow-up mailings. Given the subject of the survey, non-participants are likely to differ from participants in many features. Therefore it may be wise to reduce the sample size to make money available for follow-up mailings. While decreasing the sample size will increase random sampling error, the two follow-up mailings will more than offset this loss by decreasing non-response error.42

Summary

A research design is a framework or plan for conducting a marketing research project. It specifies the details of how a project should be conducted in order to fulfil set research objectives. The challenge faced by researchers in developing a research design is that they need to balance an understanding of research design from the decision makers’ perspective with an understanding of potential participants’ reactions to issues researched using different techniques, applied in differing contexts. Research designs may be broadly classified as exploratory or conclusive. The primary purpose of exploratory research is to develop understanding and provide insights. Conclusive research is conducted to measure and describe phenomena, test specific hypotheses and examine specific relationships. Conclusive research may be either descriptive or causal. The findings from both exploratory and conclusive research can be used as input into marketing decision making. The major objective of descriptive research is to describe market characteristics or functions. Descriptive research can be classified into cross-sectional and longitudinal research. Cross-sectional designs involve the collection of information from a sample of population elements at a single point in time. These designs can be further classified as single cross-sectional or multiple cross-sectional designs. In contrast, in longitudinal designs repeated measurements are taken on a fixed sample. Causal research is designed for the primary purpose of obtaining evidence about cause-and-effect (causal) relationships. Many research designs combine techniques that can be classified as exploratory,

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descriptive and causal. In cases where there is an array of interrelating techniques, the researcher should examine the ultimate aim of an investigation, and decide what encapsulates the overall research design – i.e. a desire to explore, describe or experiment. A research design consists of six components, and errors can be associated with any of these components. The total error is composed of random sampling error and nonsampling error. Non-sampling error consists of non-response and response errors. Response error encompasses errors made by researchers, interviewers and participants. In formulating a research design when conducting international marketing research, considerable effort is required to ensure the equivalence and comparability of secondary and primary data obtained from different countries

Questions

Exercises

1 Define research design in your own words. 2 What expectations do marketing decision makers have of research designs? 3 How does the subject of a study, as seen by potential research participants, affect research design? 4 How does formulating a research design differ from developing an approach to a problem? 5 Differentiate between exploratory and conclusive research. 6 What are the major purposes for which exploratory research is conducted? 7 Describe how quantitative techniques may be used in exploratory research. 8 What are the major purposes for which descriptive research is conducted? 9 Discuss the advantages and disadvantages of access panels. 10 Compare and contrast cross-sectional and longitudinal designs. 11 Describe cohort analysis. Why is it of special interest? 12 What is a causal research design? What is its purpose? 13 What is the relationship between exploratory, descriptive and causal research? 14 What potential sources of error can affect a research design? 15 Why is it important to minimise total error rather than any particular source of error?

1 Imagine that you are the researcher appointed by BMW and that you have been hired to conduct a study of its corporate image. a Discuss the potential issues that may affect your choice of context in which to interview female executives who buy the 7-series cars. b

Discuss the potential issues that may affect your choice of context in which to interview teenagers whose parent(s) own a BMW. 2 Visit the website of the MRS. Browse through its Research Buyer’s Guide (www. theresearchbuyersguide.com) to get a feel for the nature of industries and marketing issues that may be supported by exploratory studies. Find the agency Brainjuicer and examine the work of this research company (www. brainjuicer.com). In what manner(s) does this agency link exploratory designs to conclusive designs?

Chapter 3 Research design

3 Visit www.netflix.com (look for the site in your home country) and search online using your library’s online databases to gather information of consumers’ attitudes towards TV and movie streaming services. Netflix would like to determine consumers’ attitudes towards entertainment streaming services and hope to repeat this project annually. What type of research design would you recommend and why? As the marketing director of Netflix in your country, how would you use information about consumers’ attitudes towards streaming services to increase consumer sign-ups and retention? 4 Visit the website of the research organisation JD Power and Associates (www. jdpower.com). Work through its corporate site and choose a study that it has conducted. What research design was used for this study and what potential error issues could emerge given the nature of what it was investigating? 5 In a small group, discuss the following issues: ‘There are many potential sources of error in a research project. It is impossible to control all of them. Hence, all marketing research contains errors and we cannot be confident of the findings.’ And ‘If a research budget is limited, small sample sizes through exploratory studies are the best solution.’

Notes 1. Perkins, H. and Carney, P., ‘In touch with the spirit world’, ESOMAR, Consumer Insights Conference, Madrid (April 2003); Acreman, S. and Pegram, B., ‘Getting to know you’, Research (November 1999), 36–41. 2. Branthwaite, A. and Patterson, S., ‘The vitality of qualitative research in the era of blogs and tweeting: an anatomy of contemporary research methods’, ESOMAR, Qualitative, Barcelona (November 2010); Tait, B., ‘How “marketing science” undermines brands’, Admap (October, 2004), 46–8. 3. Hunt, S., ‘Objectivity in marketing theory and research’, Journal of Marketing 57 (April 1993), 71–91. 4. Roberts, D. and Adams, R., ‘Agenda development for marketing research: the user’s voice’, International Journal of Market Research 52 (3) (2010), 329–52. 5. Cooper, P., ‘In search of excellence: the evolution and future of qualitative research’, ESOMAR, Annual Congress, Berlin (September 2007); figure adapted from Cooper, P. and Branthwaite, A., ‘Qualitative technology – new perspectives on measurement and meaning through qualitative research’, Market Research Society Conference, 2nd Pre-conference Workshop, 1979. 6. Examples of research conducted on sensitive topics include: Kouznetsov, A. and Dass, M., ‘Does size matter? A qualitative study into areas of corruption where a firm’s size influences prospects for distributors of foreign-made goods in Russia’, Baltic Journal of Management 5 (1) (2010), 51–67; Vasconcelos, A.F., ‘Intuition, prayer, and managerial decision-making processes: a religion-based framework’, Management Decision 47 (6), (2009), 930–49; Yap, M.H.T. and Ineson, E.M., ‘HIV-infected employees in the Asian hospitality industry’, Journal of Service Management 20 (5) (2009), 503–20.

7. Chambers, K., ‘Lies, damn lies and sensitive topics’, Imprints (July 2004), 6. 8. Brüggen, E. and Willems, P., ‘A critical comparison of offline focus groups, online focus groups and e-Delphi’, International Journal of Market Research 51 (3) (2009), 363–81. 9. Murray, D. and Manuel, L., ‘Coming together…’, Market Research Society, Annual Conference (2008). 10. Bowman, J. ‘What the nose knows’, Research News (May 2007), 32–3. 11. Heath, R. and Feldwick, P., ‘Fifty years using the wrong model of advertising’, International Journal of Market Research 50 (1) (2008), 29–59; Gordon, W., ‘Consumer decision making’, Admap (October 2004), 74. 12. Clegg, A. ‘What do you really think?’, Marketing Week (25 November 2004), 39. 13. Bowman, J., ‘Winning people’s hearts’, Research World (January 2008) 13–14. 14. Arnal, L. and Holquin, R., ‘Taxis, vans and subways: capturing insights while commuting’, ESOMAR Qualitative Research, Paris (November 2007). 15. Yaman, H.R. and Shaw, R.N., ‘Marketing research and small travel agents: an exploratory study’, Journal of Vacation Marketing 8 (2) (2002), 127–40; Halman, I.M., ‘Evaluating effectiveness of project start-ups: An exploratory study’, International Journal of Project Management 20 (January 2002), 81. 16. Opinium Research and The London School of Economics, ‘Inside the mind of the voter’, MRS Awards (December 2013). 17. Kover, A.J., Carlson, L. and Ford, J., ‘Comments – the quant-qual debate: Where are we in advertising?’,

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International Journal of Advertising 27 (4) (2008), 659–69; Creswell, J.W., Research Design: Qualitative, Quantitative, and Mixed Method Approaches, 2nd edn (Thousand Oaks, CA: Sage, 2002); Lee, H., Lindquist, J.D. and Acito, F., ‘Managers’ evaluation of research design and its impact on the use of research: An experimental approach’, Journal of Business Research 39 (3) (July 1997), 231–40; Wilson, R.D., ‘Research design: Qualitative and quantitative approaches’, Journal of Marketing Research 33 (2) (May 1996), 252–5. 18. For examples of descriptive research, see Lindstrand, A. and Lindbergh, J., ‘SMEs’ dependency on banks during international expansion’, International Journal of Bank Marketing 29 (1) (2010), 65–83; Robinson, W.Y., ‘Is the first to market the first to fail?’, Journal of Marketing Research 39 (1) (February 2002), 120–28; Song, S.M. and Perry, M.E., ‘The determinants of Japanese new product success’, Journal of Marketing Research 34 (February 1997), 64–76. 19. Bakken, D., ‘Renewing the original bonds – let’s put psychology back into market research (and marketing!)’, ESOMAR Annual Congress, London (September 2006). 20. Zagórski, K., ‘Life cycle, objective and subjective living standards and life satisfaction: New indexes building and applications, Poland, 1992–2004’, ESOMAR, Public Sector Research, Berlin (May 2004). 21. Yang, K. and Jolly, L.D., ‘Age cohort analysis in adoption of mobile data services: Gen Xers versus baby boomers’, Journal of Consumer Marketing 25 (5) (2008), 272–80; Creswell, J., Research Design: Qualitative, Quantitative, and Mixed Method Approaches, 2nd edn (Thousand Oaks, CA: Sage, 2002); Misra, R. and Panigrahi, B., ‘Changes in attitudes toward women: a cohort analysis’, International Journal of Sociology & Social Policy 15 (6) (1995), 1–20; Glenn, N.D., Cohort Analysis (Beverly Hills, CA: Sage, 1981). 22. Gayen, K., McQuaid, R. and Raeside, R., ‘Social networks, age cohorts and employment’, International Journal of Sociology and Social Policy 30 (5/6) (2010), 219–38; Rentz, J.O., Reynolds, F.D. and Stout, R.G., ‘Analyzing changing consumption patterns with cohort analysis’, Journal of Marketing Research 20 (February 1983), 12–20; see also Rentz, J.O. and Reynolds, F.D., ‘Forecasting the effects of an aging population on product consumption: An age-period-cohort framework’, Journal of Marketing Research (August 1991), 355–60. 23. Zagórski, K., ‘Life cycle, objective and subjective living standards and life satisfaction: New indexes building and applications, Poland, 1992–2004’, ESOMAR, Public Sector Research, Berlin (May 2004). 24. Otker, T. and van Leeuwen, H., ‘WOM’, Research World (September 2006), 36. 25. Reichheld, F.F., The Loyalty Effect: The Hidden Force Behind Growth, Profits, and Lasting Value (Boston, MA: Harvard Business School Press, 2001). 26. For example, see Tinson, J., Nancarrow, C. and Brace, I., ‘Purchase decision making and the increasing significance of family types’, Journal of Consumer Marketing 25 (1) (2008), 45–56; Elrod, T. and Keane, M.P., ‘A factor-analytic probit model for representing the market structure in panel data’, Journal of Marketing Research 32 (February 1995), 1–16.

27. De Wulf, K., Friedman, M. and Borggreve, B., ‘Pavlov revisited – comparing panel conditioning and quality between panel methods’, ESOMAR Panel Research, Dublin (October 2008); Michaelsen, F., ‘A quick ABC of panels’, Research World (February 2005), 27. 28. de Jong, K., ‘CSI Berlin: The strange case of the death of panels’, ESOMAR Online Research, Berlin (October 2010). 29. Table 3.7 can also be viewed as a transition matrix. It depicts the brand-buying changes from period to period. Knowing the proportion of consumers who switch allows for early prediction of the ultimate success of a new product or change in market strategy. 30. Rindfleisch, A., Malter, A.J., Ganesan, S. and Moorman, C., ‘Cross-sectional versus longitudinal survey research: concepts, findings and guidelines’, Journal of Marketing Research 45 (3) (June 2008), 261–79; de Vaus, D., Research Design, 4 vols (Thousand Oaks, CA: Sage, 2005); Brannas, K., ‘A new approach to modelling and forecasting monthly guest nights in hotels’, International Journal of Forecasting 18 (1) (January–March 2002), 19; Coupe, R.T. and Onudu, N.M., ‘Evaluating the impact of CASE: An empirical comparison of retrospective and cross-sectional survey approaches’, European Journal of Information Systems 6 (1) (March 1997), 15–24. 31. Brewer, J., Foundations of MultiMethod Research (Thousand Oaks, CA: Sage, 2005); Taris, T.W., A Primer in Longitudinal Data Analysis (Thousand Oaks, CA: Sage, 2001); Van Den Berg, D.G., Lindeboom, M. and Ridder, G., ‘Attribution in longitudinal panel data and the empirical analysis of dynamic labour market behaviour’, Journal of Applied Econometrics 9 (4) (October– December 1994), 421–35; Winer, R.S., ‘Attrition bias in econometric models estimated with panel data’, Journal of Marketing Research 20 (May 1983), 177–86. 32. De Wulf, K. and Berteloot, S., ‘Challenging conventional wisdom’, Research World (January 2008), 44. 33. Pearson, C. and Kateley, V., ‘Why are we trying to create new communities for market research purposes? A case study comparing learnings from an existing community vs. a research panel’, ESOMAR Online Research, Berlin (October 2010); Lee, J.K.H., Sudir, K. and Steckel, J.H., ‘A multiple ideal point model: Capturing multiple preference effects from within an ideal point framework’, Journal of Marketing Research 39 (1) (February 2002), 73–86; Maytas, L. and Sevestre, P. (eds), The Econometrics of Panel Data: A Handbook of the Theory with Applications (Norwell, MA: Kluwer Academic, 1996). 34. Murphy, D., ‘More efficiency and integration of data’, Research World (February 2005), 29. 35. Huertas-Garcia, R. and Consolación-Segura, C., ‘Using statistical design experiment methodologies to identify customers’ needs’, International Journal of Market Research 51 (1) (2009), 115–36; Hulland, J., Ho, Y. and Lam, S., ‘Use of causal models in marketing research: A review’, International Journal of Research in Marketing 13 (2) (April 1996), 181–97; see also Cox, K.K. and Enis, B.M., Experimentation for Marketing Decisions (Scranton, PA: International Textbook, 1969), 5. 36. Ryals, L. and Wilson, H., ‘Experimental methods in market research: from information to insight’,

Chapter 3 Research design

International Journal of Market Research 47 (4) (2005), 345–64; Winer, R.S., ‘Experimentation in the 21st century: the importance of external validity’, Journal of the Academy of Marketing Science (Summer 1999), 349–58. 37. Mariampolski, H., Wolf, S. and Luigi, T., ‘Americans and Italians face each other at dinner’, Research World (January 2006), 32–3. 38. KPMG Nunwood, ‘NatWest: A great call for financial services’, MRS Awards Finalist (December 2015). 39. Poynter, R., ‘A taxonomy of new MR’, Market Research Society, Annual Conference (2010); Lee, E., ‘Are consumer survey results distorted? Systematic impact of behavioural frequency and duration on survey response errors’, Journal of Marketing Research (February 2000), 125–33; Dutka, S. and Frankel, L.R., ‘Measuring response error’, Journal of Advertising Research 37 (1) (January/February 1997), 33–9. 40. van Meurs, L., van Ossenbruggen, R. and Nekkers, L., ‘Do rotten apples spoil the whole barrel? Exploring quality issues in panel data’, ESOMAR Panel Research,

Orlando (October 2007); Loosveldt, G., Carton, A. and Billiet, J., ‘Assessment of survey data quality: A pragmatic approach focused on interviewer tasks’, International Journal of Market Research 46 (1) (2004), 68. 41. Blyth, B., ‘Mixed mode: The only “fitness” regime?’, International Journal of Market Research 50 (2) (2008), 241–66; Brooks, D.V., ‘A hands on approach to response rates’, Imprints (October 2003), 24. 42. Manfreda, K.L., Bosnjak, M., Berzelak, J., Haas, I. and Vehovar, V., ‘Web surveys versus other survey modes: A meta-analysis comparing response rates’, International Journal of Market Research 50 (1) (2008), 79–104; Sinha, P., ‘Determination of reliability of estimations obtained with survey research: A method of simulation’, International Journal of Market Research 42 (3) (Summer 2000), 311–18; Rollere, M.R., ‘Control is elusive in research design’, Marketing News 31 (19) (15 September 1997), 17; Corlett, T., ‘Sampling errors in practice’, Journal of the Market Research Society 38 (4) (April 1997), 307–18.

4 Stage 1

Problem definition

Stage 2 Research approach developed

Stage 3 Research design developed

Stage 4 Fieldwork or data collection

Stage 5 Data integrity and analysis

Stage 6 Communicating research findings

Secondary data collection and analysis

The act of sourcing, evaluating and analysing secondary data can realise great insights for decision makers. It is also vital to successful problem diagnosis, sample planning and collection of primary data.

Chapter 4 Secondary data collection and analysis

Objectives After reading this chapter, you should be able to: 1 define the nature and scope of secondary data and distinguish secondary data from marketing intelligence and primary data; 2 analyse the advantages and disadvantages of secondary data and their uses in the various steps of the marketing research process; 3 evaluate secondary data using the criteria of specifications, error, currency, objectives, nature and dependability; 4 describe in detail the different sources of secondary data, focusing upon external sources in the form of published materials and syndicated services; 5 discuss in detail the syndicated sources of secondary data, including household and consumer data obtained via surveys, purchase and media panels and scanner services, as well as institutional data related to retailers and industrial or service firms; 6 explain the need to use multiple sources of secondary data and describe single-source data; 7 understand the researchers’ challenges in coping with the burgeoning amount of externally generated secondary data; 8 appreciate how social media research techniques are integrating with traditional forms of research, and the impact upon what may be defined as secondary data.

Overview The collection and analysis of secondary data helps to define the marketing research problem and develop an approach. In addition, before collecting primary data, the researcher should locate and analyse relevant secondary data. Thus, secondary data should be an essential component of a successful research design. Secondary data can help in sample designs and in the details of primary research methods. In some projects, research may be largely confined to the analysis of secondary data because some marketing problems may be resolved using only secondary data. This chapter discusses the distinction between primary data, secondary data and marketing intelligence. The advantages and disadvantages of secondary data are considered, and criteria for evaluating secondary data are presented, along with a classification of secondary data. Internal secondary data are described and major sources of external secondary data, such as published materials, online and offline databases and syndicated services, are also discussed. Using secondary data in international marketing research is covered. Several ethical issues that arise in the use of secondary data are identified. The impact of the growth and development of secondary data sources on the web will also be evaluated. To begin with, we present an example that illustrates how secondary data were used in a research design for the Virgin brand.

Real research

A 21st-century approach to brand development1 As a leading global brand, Virgin has created more than 200 companies in 29 different countries. Virgin brands are independent businesses, empowered to run themselves but united by Virgin’s brand values of being fun, innovative, challenging and offering great service and value for the customer. The lack of management layers and bureaucracy creates an optimum ‘start-up’ atmosphere, backed up by the support of a wider ‘family’ of

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brands operating as a community to support and challenge each other. As such, the Virgin brand can mean many things to many different people. Virgin had an intuitive feel for what this was but lacked any firm evidence of the Virgin brands supporting each other. Measuring the equity of the Virgin brand required a customised approach to assess the impact of the brand at both industry and Virgin-group level. Virgin needed a research solution that would move beyond a ‘recap’ of the brand health and provide a roadmap to increase consumer engagement, support new category entry and, ultimately, generate a tangible return for the business. With the opportunity of a new phase of research, Virgin wanted to throw away the rule book, creating a programme of brand evaluation that would help Virgin ‘join the dots’ across its family of brands and harness the voice of the consumer in a more intuitive way. The research had to balance the need for ongoing tracking and global benchmarking research, while delivering an increased understanding of the consumer. A new phase of research always generates debate, and in an organisation such as Virgin there was no shortage of ideas for moving things forward, shaking things up and challenging the status quo. A balance was required to ensure the great ideas and insights from previous work were not ignored. It was extremely important to move this phase of research forward without throwing away the ideas and insights that the brand team and wider research users had been using effectively. There were three key phases: (1) reviewing historical research (both in terms of past reports and in an engagement in the ‘stories’ that surround past research); (2) evaluating internal and external secondary data sources; and (3) in-depth interviews with Virgin executives and executives from supporting agencies. Searching for past research and secondary data beyond the Virgin brand team to agency partners presented further resources to explore. They worked through Mullen’s (a full-service integrated advertising agency, www.mullen.com) internal resources, which in turn provided access to Simmons’ (www.simmonssurvey.com) psychographic profiling and media databases. Utilising secondary data was a critical step in creating not simply a brand research review, but a dynamic brand research ‘resource’ that could provide more versatile elements of brand research, which could be used directly to target Virgin customers.

Defining primary data, secondary data and marketing intelligence Primary data Data originated by the researcher specifically to address the research problem.

Secondary data Data previously collected for some purpose other than the problem at hand.

Marketing intelligence Qualified observations of events and developments in the marketing environment.

Primary data are data originated by a researcher for the specific purpose of addressing the problem at hand. They are individually tailored for the decision makers of organisations that pay for well-focused and exclusive support. Compared with readily available data from a variety of sources, this exclusivity can mean higher costs and a longer time frame in collecting and analysing the data. Secondary data are data that have already been collected for purposes other than the problem at hand. At face value, this definition seems straightforward, especially when contrasted to the definition of primary data. However, many researchers confuse the term, or quite rightly see some overlap, with marketing intelligence. Marketing intelligence can be defined as ‘qualified observations of events and developments in the marketing environment’. The use of the word ‘observations’ is presented in a wide sense to include a variety of types of data, broadly concerned with ‘environmental scanning’.2 In essence, though, marketing intelligence is based upon data that in many instances have been collected for purposes other than the problem at hand. To clarify this overlap in definitions, Table 4.1 compares secondary data with marketing intelligence through a variety of characteristics.

Chapter 4 Secondary data collection and analysis

Table 4.1

A comparison of secondary data and marketing intelligence3

Characteristic

Secondary data

Marketing intelligence

Structure

Specifications and research design tend to be apparent

Can be poorly structured; no universal conventions of reporting

Availability

Tend to have regular updates

Irregular availability

Sources

Generated in-house and from organisations with research prowess

Generated in-house and from unofficial sources, especially through social media

Data type

Tend to be quantitative; many issues need qualitative interpretation

Tends to be qualitative; many issues difficult to validate and quantify

Source credibility

Tend to be from reputable and trustworthy research sources

Questionable credibility; can be generated from a broad spectrum of researchers and authors

Terms of reference

Tend to have clear definitions of what is being measured

Ambiguous definitions; difficult to compare over different studies

Analysis

Mostly conventional quantitative techniques

Opinion based, interpretative

Ethics

In-company data gathering may be covered byData Protection Acts; externally generated data may be covered by research codes of conduct, e.g. ESOMAR

Some techniques may be seen as industrial espionage – though there is an ethical code produced by the Society of Competitive Intelligence Professionals

Note in these comparisons the repeated use of the word ‘tend’. The boundaries between the two are not absolutely rigid. As will become apparent in this chapter, there are clear criteria for evaluating the accuracy of secondary data, which tend to be of a quantitative nature. Marketing intelligence is more difficult to evaluate but this does not mean that it has less value to decision makers or researchers. Certain marketing phenomena cannot be formally measured: researchers may not be able to gain access to conduct research, or the rapid unfolding of events means that it is impracticable to conduct timely research.

Real research

Gathering marketing intelligence in China4 The very nature of marketing intelligence gathering means that much of what researchers discover is often new and surprising. This is particularly true of intelligence gathering in China, where the rapid changes in the commercial landscape mean changes to commercial structures and processes, and projections, happen very quickly; an industry report can be out of date within six months. Some of the challenges that are faced in gathering marketing intelligence in China include the following: •

•

Access to Western internet services within China, including Facebook and Google, is restricted or blocked by China’s Golden Shield Project (often referred to by the media as the ‘Great Firewall’), which controls access to internet traffic in and out of China. Because of the scale and size of the Chinese marketplaces, China has now developed its own social media ecosystem and marketing researchers should be careful to understand the effective local sources of data (see Chapter 17 for more details). Protecting information is part of the culture, as is a reluctance to be the one blamed for losing information. There is little incentive for a typical purchasing or operations manager or government employee to provide information to an

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external party. There is potential risk associated in passing on information, and since marketing research is relatively new in China, interviewers have to be more reassuring about how ‘normal’ the process is in order to facilitate meetings, interviews and informative responses. •

•

Shadow team A small, cross-functional, boundary-spanning group that learns everything about a competitive unit.

Research participants can be from a wide variety of social and educational backgrounds, but all can be working in the same district. This phenomenon is particularly apparent in the ‘1st-tier cities’, as Beijing, Shanghai, Shenzhen and Guangzhou are collectively known. There is a complex convergence of those with money and international experience, those with money but no international experience and those with very little money and no experience outside one small area of the country. When this diverse combination occurs within one family, it causes specific challenges to researchers. In marketing intelligence gathering, the progression from very low knowledge and awareness of international influences on an industry to full awareness happens very fast. Fragmented industries and a vast country means hundreds of local marketplaces abound. Extracting comment on the nature of one industry across the country is unrealistic, and so it is for the researcher to merge the jigsaw pieces from across the country to build a national picture. A senior manager in a company in Zhejiang will often assume automatically that we are speaking only about the Zhejiang province when posed questions about the development of the industry in the coming five years.

Many major organisations invest huge amounts in the hardware and software needed for a systematic approach to gathering intelligence, some even engaging in the use of ‘shadow teams’. A shadow team is a small, cross-functional, boundary-spanning group that learns everything about a competitive unit. A competitive unit can be a competitor, product line, supply chain or prospective partner in a strategic alliance. The objective of a shadow team is to learn everything possible about its target through published data, personnel and network connection and organisation knowledge or hearsay. It brings together knowledge from across an organisation, so that it can think, reason and react like the competitive unit.5 (Competitive intelligence will be discussed in more detail in the context of business-to-business marketing research in Chapter 29.) Such widespread use of intelligence in major organisations means it has a role to play in supporting decision makers, but it has many limitations, which are apparent in Table 4.1. In the development of better-founded information support, credible support can come from the creative collection and evaluation of secondary data. This requires researchers to connect and validate different data sources, ultimately leading to decision-maker support in its own right, and support of more focused primary data collection. As this chapter and Chapter 5 unfold, examples of different types of secondary data will emerge and the applications of secondary data will become apparent.

Advantages and uses of secondary data Secondary data offer several advantages over primary data. Secondary data are easily accessible, relatively inexpensive and quickly obtained. Some secondary data sources can be accessed free of charge, but many sources do charge fees to reflect the investment made to gather, analyse and present accurate information. Nonetheless, with the availability of freely available data (of variable quality and integrity), there are suggestions that governmentsourced secondary data should be freely available, as argued in the following example.

Chapter 4 Secondary data collection and analysis

Real research

Free our data6 Marketers make extensive use of information that is collected by governments. In recent years the pressure has mounted for public data to be more freely available in order to stimulate innovation. Many businesses rely on accurate secondary data to make better business decisions, especially in targeting new markets. In doing this, they can draw on an array of government datasets and surveys. These data have the particular advantage of having a consistent national coverage, being relatively unbiased and created to high research standards. Examples of a number of UK-based government suppliers include: •

Office for National Statistics – especially for the Census and large-sample surveys

•

Post Office – the Postcode Address File

•

Ordnance Survey – grid references, map background and boundaries

•

Land Registry – house prices

•

Companies House – details of businesses.

Other countries have also developed an interest in the wide use of open data including France (www.data.gouv.fr), Germany (www.govdata.de) and many more, which are available via the EU Open Data portal (www.publicdata.eu). It has been argued that as public information is often collected at taxpayers’ expense, the barriers to its widespread use should be removed wherever possible. Users will have better information – a step towards the ‘perfect knowledge’ assumed in economists’ views of perfect markets.

Some secondary data, such as those provided by the National Censuses, are available on topics where it would not be feasible for a firm to collect primary data. Although it is rare for secondary data to provide all the answers to a non-routine research problem, such data can be useful in a variety of ways.7 Secondary data can help to: 1 Diagnose the research problem. 2 Develop an approach to the problem. 3 Develop a sampling plan. 4 Formulate an appropriate research design (e.g. by identifying the key variables to measure or understand). 5 Answer certain research questions and test some hypotheses. 6 Interpret primary data with more insight. 7 Validate qualitative research findings. Given these advantages and uses of secondary data, we state the following general rule: Examination of available secondary data is a prerequisite to the collection of primary data. Start with secondary data. Proceed to primary data only when the secondary data sources have been exhausted or yield marginal returns. The rich dividends obtained by following this rule are illustrated in the example at the start of this chapter. It shows that the collection and analysis of even one relevant secondary data source can provide valuable insights. The decision maker and researcher can use the ideas generated in secondary data as a very strong foundation to primary data design and collection. However, the researcher should be cautious in using secondary data, because they have some limitations and disadvantages.

Marketing Research

Disadvantages of secondary data Because secondary data have been collected for purposes other than the problem at hand, their usefulness to the current problem may be limited in several important ways, including relevance and accuracy. The objectives, nature and methods used to collect the secondary data may not be appropriate to the present situation. Also, secondary data may be lacking in accuracy or may not be completely current or dependable. Before using secondary data, it is important to evaluate them according to a series of factors. These factors are discussed in more detail in the following section.

Criteria for evaluating secondary data The quality of secondary data should be routinely evaluated, using the criteria presented in Table 4.2 and the discussion in the following sections.

Table 4.2

Criteria for evaluating secondary data

Criteria

Issues

Remarks

Specifications and research design

• Data collection method

Data should be reliable, valid and generalisable to the problem at hand

• Response rate • Population definition • Sampling method • Sample size • Questionnaire design • Fieldwork • Data analysis Error and accuracy

Examine errors in: • Approach

Assess accuracy by comparing data from different sources

• Research design • Sampling • Data collection • Data analysis • Reporting Currency

Time lag between collection and ublication; frequency of updates p

Census data are periodically updated by syndicated firms

Objective

Why the data were collected

The objective will determine the relevance of data

Nature

• Definition of key variables • Units of measurement • Categories used • Relationships examined

Reconfigure the data to increase their usefulness, if possible

Dependability

Source: • Expertise • Credibility • Reputation • Trustworthiness

Preference should be afforded to an original rather than an acquired source

Chapter 4 Secondary data collection and analysis

Specifications: research design and how the data were collected The specifications of the research design used to collect the data should be critically examined to identify possible sources of bias. Such design considerations include size and nature of the sample, response rate and quality, questionnaire design and administration, procedures used for fieldwork and data analysis and reporting procedures. These checks provide information on the reliability and validity (concepts developed in Chapter 13) of the data and help determine whether they can be generalised to the problem at hand. The reliability and validity can be further ascertained by an examination of the error, currency, objectives, nature and dependability associated with the secondary data.

Error: accuracy of the data The researcher must determine whether the data are accurate enough for the purposes of the present study. Secondary data can have a number of sources of error or inaccuracy, including errors in the approach, research design, sampling, data collection, analysis and reporting stages of the project. Moreover, it is difficult to evaluate the accuracy of secondary data because the researcher did not participate in the research. One approach is to find multiple sources of data, if possible, and compare them using standard statistical procedures.

Real research

Measuring media on the internet8 Gone are the days of the internet being a collection of static web pages. Now it extends across almost every platform and is intertwined with nearly every medium. TV, radio and mobile are now directly connected with the internet. Such is the change that the terms ‘TV’ and ‘radio’ are fast becoming redundant, in exchange for the terms ‘video’ and ‘audio’, as the English language evolves to keep up. The fragmentation of media has created more niche audiences than ever before; they are constantly dividing, subdividing and regrouping in many different forms at different levels on a national, even global scale. Publishers and broadcasters are now media companies with a mixed-content offering. The effects of the fragmentation of media have made it increasingly challenging for sample-based research to measure these fragmented audiences accurately. For instance, there might be 1,000 people a month who are regularly visiting a blog on gardening. These people have distinct interests and needs, and may well be a very valuable audience; however, in countries with populations of millions, these people are simply not being picked up. Publishers report their online traffic through ABCe (www.abc.org.uk; ABC is owned by the media industry and ABCe independently verifies and reports on media performance, providing trusted traffic and related data across a broad range of digital platforms). These industry-agreed standards are a step forward, as greater transparency will better inform advertisers and media agencies in their decisions when allocating advertising budgets. However, the development of the internet has brought a host of new opportunities and challenges for measuring the internet in the shape of blogs, video, audio, RSS feeds, podcasts, and so the list goes on. The TV, radio and mobile industry sectors are making positive steps to establish industry-backed measurement standards to help quantify online audiences. Broadcasters have been swift to make moves to measure video delivered over the internet. Major broadcasters have come together to form the

Marketing Research

BMWG (Broadband Measurement Working Group) to develop a common approach for measuring online video content to deliver accountability to rights holders. Broadcasters clearly feel that video over the internet has reached a point where a reliable measurement tool is needed. This is particularly important for commercial broadcasters, who are investing a great deal in developing a variety of video-on-demand services and will need to generate revenue from video advertising to sustain their businesses. The internet is a global medium, and so the international implications cannot be ignored. In fact, global measurement structures are helpful. The International Federation of Audit Bureaux of Circulation (IFABC) (www.ifabc.org) draws together ABCe’s sister organisations across the globe to implement constructive international measurement initiatives.

As the above example indicates, the accuracy of secondary data can vary. What is being measured? What rules apply to those measurements? What happens if there are rapid changes in what is being measured? With different researchers potentially measuring the ‘same’ phenomena, data obtained from different sources may not agree. In these cases, the researcher should verify the accuracy of secondary data by conducting pilot studies, or by other exploratory work that verifies the analytical framework used to arrive at certain figures. Often, by judicious questioning of those involved in compiling the figures, this can be done without much expense or effort.

Currency: when the data were collected Secondary data may not be current, and the time lag between data collection and publication may be long, as is the case with many census data, which may take up to two years from collection to publication. Moreover, the data may not be updated frequently enough for the purpose of the problem at hand. Decision makers require current data; therefore, the value of secondary data is diminished as they become older. For instance, although the Census of Population data are comprehensive, they may not be applicable to major cities in which the population has changed rapidly during the last two years.

Objective: the purpose for which the data were collected Data are invariably collected with some objective in mind, and a fundamental question to ask is why the data were collected in the first place. The objective for collecting data will ultimately determine the purpose for which that information is relevant and useful. Data collected with a specific objective in mind may not be appropriate in another situation. Working with our opening example, suppose that the magazine Inside Flyer (www.insideflyer.com) conducted a survey where the sample was made up of ‘frequent flyers’. The objective of the study could be ‘to uncover the airline characteristics consumers consider most important’. Virgin, however, may wish to target ‘business-class’ flyers and ‘to uncover perceptions related to trade-offs made in customer service–price–safety’. Even though there may be identical questions used in both surveys, the target participants may be different, the rationale for the study presented to participants will be different and, ultimately, the ‘state of mind’ that participants may be in when they come to comparable questions will be different. The Inside Flyer survey would be conducted for entirely different objectives from those Virgin has for its study. The findings from the Inside Flyer survey may not directly support decision making at Virgin, though they may help to define who Virgin should talk to and what questions it should put to them.

Nature: the content of the data The nature, or content, of the data should be examined with special attention to the definition of key variables, the units of measurement, the categories used and the relationships

Chapter 4 Secondary data collection and analysis

e xamined. If the key variables have not been defined, or are defined in a manner inconsistent with the researcher’s definition, then the usefulness of the data is limited. Consider, for example, secondary data on consumer preferences for TV programmes. To use this information, it is important to know how preference for programmes was defined. Was it defined in terms of the programme watched most often, the one considered most needed, most enjoyable, most informative, or the programme of greatest service to the community? Likewise, secondary data may be measured in units that may not be appropriate for the current problem. For example, income may be measured by individual, family, household or spending unit and could be gross or net after taxes and deductions. Income may be classified into categories that are different from research needs. If the researcher is interested in highincome consumers with gross annual household incomes of over €120,000, secondary data about those with income categories of less than € 20,000, € 20,001−50,000, € 50,001−75,000 and more than € 75,000 will not be of much use. Determining the measurement of variables such as income may be a complex task, requiring the wording of the definition of ‘income’ to be precise. Finally, the relationships examined should be taken into account in evaluating the nature of data. If, for example, actual behaviour is of interest, then data inferring behaviour from self-reported attitudinal information may have limited usefulness. Sometimes it is possible to reconfigure the available data – for example, to convert the units of measurement – so that the resulting data are more useful to the problem at hand.

Dependability: how dependable are the data? An overall indication of the dependability of data may be obtained by examining the expertise, credibility, reputation and trustworthiness of the source. This information can be obtained by checking with others who have used the information provided by the source. Data published to promote sales, to advance specific interests, or to carry on propaganda should be viewed with suspicion. The same may be said of data published anonymously or in a form that attempts to hide the details of the data collection research design and process. It is also pertinent to examine whether the secondary data came from an original source (one that generated the data), or an acquired source (one that procured the data from an original source and published them in a different context). Generally, secondary data should be secured from an original rather than an acquired source. There are at least two reasons for this rule: first, an original source is the one that specifies the details of the data collection research design; and, second, an original source is likely to be more accurate and complete than a surrogate source.

Classification of secondary data Internal data Data available within the organisation for which the research is being conducted.

Figure 4.1 presents a classification of secondary data. Secondary data may be classified as either internal or external. Internal data are those generated within the organisation for which the research is being conducted. An example of this source of data for any marketing decision maker and researcher is the corporate revenue ledger at individual transaction level. Analyses of who is buying and the different ways that these customers may be classified or segmented, what they bought, how frequently and the monetary value of their purchases, can give a basic level of understanding customer buying behaviour. With a number of years of transaction data, the life-stages of customer segments can be better understood and how customers have reacted to an array of marketing activities. One of the main problems that researchers face with accessing and analysing transaction data is ‘corporate territorialism’, i.e. the attitude that each department should only be concerned with the operational data it needs for the business to run on a day-to-day basis.9 (Given the growth and significance of this element of marketing decision support, secondary data generated from internal sources will be examined in more detail in Chapter 5.)

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Figure 4.1

Secondary data

A classification of secondary data

Internal

External

Requires further processing

Ready to use

Published materials

External data Data that originate outside the organisation.

Computerised databases

Syndicated services

External data, on the other hand, are those generated by sources outside the organisation. These data may exist in the form of published material, online databases, or information made available by syndicated services. Externally generated secondary data may be more difficult to access, more expensive and more difficult to evaluate for accuracy, in comparison with internal secondary data. These factors mean that, before collecting external secondary data, it is vital to gather, analyse and interpret any readily available internal secondary data and intelligence.

Published external secondary sources Sources of published external secondary data include local authorities, regional and national governments, the EU, non-profit organisations (e.g. Chambers of Commerce), trade associations and professional organisations, commercial publishers, investment brokerage firms and professional marketing research firms.10 In fact, such a quantity of data is available that the researcher can be overwhelmed. Therefore, it is important to classify published sources (see Figure 4.2). Published external sources may be broadly classified as general business data or government data. General business sources comprise guides, directories, indexes and statistical data. Government sources may be broadly categorised as census data and other publications. These data types are discussed further, with specific sources used as examples.

General business sources Businesses publish a lot of information in the form of books, periodicals, journals, news papers, magazines, reports and trade literature. Although some information may be in hard copy, an increasingly large volume of information is now available through databases that can be easily accessed online. Sources are also available to identify statistical data. 1 Guides. Guides are an excellent source of standard or recurring information. A guide may help identify other important sources of directories, trade associations and trade publications,

Chapter 4 Secondary data collection and analysis

Figure 4.2

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Published secondary data

A classification of published secondary sources General business sources

Government sources

Census data

Other government data

Guides

Directories

Indexes

Statistical data

so guides are one of the first sources a researcher should consult when commencing research. Libraries, whether these be public, at universities or within businesses, will have a guide to classify the resources they hold. Within library holdings will be databases such as WARC (www.warc.com), which compiles industry-based data and commentary to support marketers, communications and research professionals. Commercial guides can be used to assist decision makers or researchers to uncover current issues and sources regarding individual industries or countries. An example of one of these would be the Datamonitor guides (search for ‘guides’ on www.datamonitor.com). Another example is the @BRINT guide to business technology management and knowledge management sites with editorial comments (www. brint.com). 2 Directories. Directories are helpful for identifying individuals or organisations that collect specific data. Examples of directories used by researchers are the Hollis directories that support the industries of sponsorship and public relations (www.hollis-sponsorship. com; www.hollis-pr.com).

Real research

Hollis-PR.com For more than 40 years Hollis has been the public relations world’s major information provider, publishing the market-leading directories, such as Hollis UK PR Annual, Hollis Europe and Hollis-PR. Hollis-PR.com is a gateway to PR information requirements. It has a search engine that enables researchers to: • •

• •

Find a PR consultancy – to find the ideal agency partner. Source an in-house PR contact – through subscription – with access to 7,788 in-house PR contacts. Locate a specialist service – a free supplier search to locate specialist support. Search for a UK media contact – through subscription – with access to a UK media database for newspapers, magazines and broadcast media.

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Another example is Europages, a reference business directory in Europe, which classifies 23 million companies in 35 European countries, in 26 languages (www.europages. com). Other directories worth exploring include www.bizeurope.com and ESOMAR’s Directory of Research Organisations (http://directory.esomar.org). 3 Non-governmental statistical data. Business research often involves compiling statistical data reflecting market or industry factors. A historic perspective of industry participation and growth rates can provide a context for market-share analysis. Market statistics related to population demographics, purchasing levels, TV viewership and product usage are some of the types of non-governmental statistics available from secondary sources. As well as any published commentary presented in these resources, further statistical analyses and graphical manipulations can be performed on these data to draw important insights. Examples of nongovernmental statistical data include trade associations such as the Swedish Tourism Trade Association (www.sverigeturism.se). The Swedish Information ‘Smorgasbord’ is a large single source of information in English on Sweden, Swedish provinces, nature, culture, lifestyle, society and industry. Other examples include Euromonitor (www.euromonitor.com), which publishes monthly market research journals covering a great breadth of industries and countries across the world. Keynote (www.keynote.co.uk) produces reports focusing on European markets, built upon a combination of primary data collection and other secondary data sources. The United Nations provides an example of an organisation with a Statistics Division that provides a wide range of statistical outputs on a global basis (http://unstats.un.org). The Statistics Division produces printed publications of statistics and statistical methods in the fields of international merchandise trade, national accounts, demography and population, social indicators, gender, industry, energy, environment, human settlements and disability. The Statistics Division also produces general statistical compendiums, including the Statistical Yearbook and World Statistics Pocketbook.

Government sources European governments and the EU also produce large amounts of secondary data. Each European country has its own statistical office, which produces lists of the publications available (and the costs involved). Examples of national statistical offices include the Centraal Bureau voor de Statistiek Nederlands (www.cbs.nl), Danmarks Statistik (www.dst.dk), the Federal Statistical Office of Germany (www.destatis.de), the French Institut National de la Statistique et des Études Economiques (www.insee.fr) and the British Office for National Statistics (www. statistics.gov.uk). All of these links allow you to examine quickly the array of publications that they produce. Their publications may be divided into census data and other publications. 1 Census data. Most European countries produce either catalogues or newsletters that describe the array of census publications available and the plans for any forthcoming census. In the UK, for example, www.ons.gov.uk/ons/guide-method/census/2011/index.html contains the latest information about the 2011 Census in England and Wales. Census Marketing in Britain can supply unpublished data from the 1961, 1971, 1981, 1991 and 2001 Censuses in the form of Small Area Statistics (SAS). SAS are available for standard census areas within England and Wales, such as counties, local government districts, London boroughs, wards, civil parishes and enumeration districts. Maps can also be purchased to complement the data. Census data can be kept in electronic format, allowing them to be analysed and presented in a variety of formats at a detailed geographical level. Given the long periods between the national censuses and the amount of change that can occur in these periods, other data sources are used to maintain an up-to-date picture of specific regions. 2 Other government publications. In addition to the censuses, national statistical offices collect and publish a great deal of statistical data. As well as general population censuses, national statistical offices produce an array of nationally relevant statistics. The value of

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these may lie in evaluating and describing markets and operating environments and the challenges and opportunities these hold. The British Office for National Statistics covers areas that include: agriculture and environment; children, education and skills; crime and justice; the economy; government; health and social care; the labour market; people and places; the population; and travel and transport. Business and energy statistics may be viewed at www.statistics.gov.uk/hub/business-energy/. Examples of reports from the British Office for National Statistics include Social Trends, drawing together social and economic data from a wide range of government departments and other organisations. This report provides a comprehensive guide to British society today, and how it has been changing.

Real research

UK citizens rate health care relatively highly compared with the rest of the EU An established reference source, Social Trends, draws together social and economic data from a wide range of government departments and other organisations; it paints a broad picture of British society today, and how it has been changing. There are 13 chapters, each focusing on a different social policy area, described in tables, figures and text: population; households and families; education and training; labour market; income and wealth; expenditure; health; social protection; crime and justice; housing; environment; transport; and lifestyles and social participation. The zip file provides links to Excel spreadsheets that contain the data for each table, figure and map. An example of the output is encapsulated in the following extract from Social Trends News Release: Date: 11 November 2010 Coverage: United Kingdom Theme: Social and Welfare UK men born in 2007 could expect to live 1.6 years longer than the ‘average man’ in the EU-27, according to a report published today by the Office for National Statistics. However, women could expect to live 0.3 years less than the EU-27 average for females. The International comparisons chapter of Social Trends also shows that in 2007 life expectancy for UK women stood at 81.9 years at birth (82.2 for EU-27) compared with 77.7 years for men (76.1 for EU-27).

In the EU, statistics and opinion polls are published by the Statistical Office of the European Community in a series called Eurostat (http://europa.eu; http://europa.eu/documentation/ statistics-polls). Tables normally contain figures for individual member states of the EU, plus totals for all countries. Eurostat divides its publications into themes, which are: • • • • • • • • •

General and regional statistics Economy and finance Population and social conditions Industry trade and services Agriculture and fisheries External trade Transport Environment and energy Science and technology.

It also produces general titles, which include the Eurostat Regional Yearbook, The EU in the World – A Statistical Portrait, Europe in Figures – Eurostat Yearbook and Key Figures on European Business.

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To examine any of the national statistics offices in Europe and Global Regions, visit the United Nations Economic Commission for Europe website (www.unece.org/stats/links. html) and follow the country links. There are also links to many other important organisations with relevant statistics, such as the European Central Bank (www.ecb.int) and the International Monetary Fund (www.imf.org).

Databases A major category of secondary data is available in the form of browsable online databases.11 From the 1980s to date, the number of databases, as well as the vendors providing these services, has grown enormously. Browsable online databases offer a number of advantages over printed data, including:12 1 The data can be current, up to date and even ‘live’. 2 The search process is more comprehensive, quicker and simpler. Online vendors can provide ready access to hundreds of databases. Moreover, this information can be accessed instantaneously, and the search process is simplified as the vendors provide uniform search protocols and commands for accessing the database. 3 The cost of accessing these is relatively low, because of the accuracy of searching for the right data, and the speed of location and transfer of data. 4 It is convenient to access these data using many forms of working online, including mobile devices. Although online database information can be helpful, it is not necessarily free. It is vital to consider what costs are incurred in generating, presenting and updating quality and dependable information databases. The number of database vendors and the breadth of subjects covered can be vast and confusing, especially at the commencement of a project. Thus a classification of online databases is helpful.

Classification of online databases Online databases Databases that can be accessed, searched and analysed via the internet.

Online databases may be classified as bibliographic, numeric, full text, directory or specialpurpose databases, as shown in Figure 4.3.

Figure 4.3

Computerised databases

A classification of online databases

Online

Bibliographic databases

Numeric databases

Offline

Full-text databases

Directory databases

Specialpurpose databases

Chapter 4 Secondary data collection and analysis Bibliographic databases Databases composed of citations to articles in journals, magazines, newspapers, marketing research studies, technical reports, government documents and the like. They often provide summaries or abstracts of the material cited.

Numeric databases Databases containing numerical and statistical information that may be important sources of secondary data.

Full-text databases Databases that contain the complete text of secondary source documents comprising the database.

Directory databases Databases that provide information on individuals, organisations and services.

Special-purpose databases Databases that contain information of a specific nature, e.g. data on a specialised industry.

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Bibliographic databases are composed of citations to articles in journals, magazines, newspapers, marketing research studies, technical reports, government documents and the like.13 They often provide summaries or abstracts of the material cited. The IMRI database is a good example of this. It includes over 50,000 abstracts of market research reports and sources (including journals, databases, audits, published surveys, etc.). This is a comprehensive directory of marketing research agencies, publishers and associations in over 100 countries. Besides country listings, agencies appear in regions (e.g. Asia), specialist fields (e.g. quantitative) and market sectors (e.g. healthcare and pharmaceutical). The IMRI database is hosted on Datastar, Thompson/Dialog’s collection of information databases (www.dialog.com). Numeric databases contain numerical and statistical information. For example, some numeric databases provide time-series data about the economy and specific industries. The earlier examples of census-based numeric databases using data over a series of censuses provide an example of a numeric database. The Experian MOSAIC database is a good example of a numeric database (www.experian.co.uk/marketing-services/). Experian data include business and consumer demographics and classifications, mapping, economic forecasts and statistics, local area data and retail and business information. This numeric database is delivered in a range of formats, including databases, reports and products, such as Experian’s Mosaic consumer classification. Full-text databases contain the complete text of the source documents held in the database. They usually have the ability to conduct advanced searches for topics, authors, phrases, words and interconnections between these. Examples include Emerald Insight (www.emeraldinsight. com) and the Gale Newspaper Database (www.gale.cengage.com). Emerald is an independent publisher of global research with an impact in business, society, public policy and education. Its database provides access to more than 68,000 articles, some dating back as far as 1898. It has backfiles of over 120 business and management titles in one unified platform and access to 217 business and management e-journals. The Gale Newspaper Database indexes and provides full-text articles – for example, in the UK from the Financial Times, The Guardian, the Independent, the Independent on Sunday, The Observer, The Times and The Sunday Times. The Gale database is a global resource so is worth accessing for any specific country or region. The Gale Directory of Databases is published every six months. Volume 1 covers online databases and Volume 2 covers CD-ROMs and other offline databases. Directory databases provide information on individuals, organisations and services. European Directories (www.europeandirectories.com) is an example of a directory database. European Directories is a pan-European local search-and-lead generation company. It provides local search services to help customers find, evaluate and connect with local businesses across multiple media, including print, online and mobile. It can help advertisers ensure they have a strong presence wherever consumers might be searching for local businesses. Another example is the Directory of Open Access Journals (www.doaj.org). This online directory covers free, full-text, quality-controlled scientific and scholarly journals. Finally, there are special-purpose databases. A good example of a special-purpose database is the fashion-trend forecasting service WGSN (www.wgsn.com). WGSN is a leading online trend-analysis and research service, providing creative and marketing intelligence for the apparel, style, design and retail industries. Its data support all business functions, including design, production, manufacturing, purchasing, merchandising, marketing, product development and general management. WGSN has a 12-year archive, with more than 5 million images and 650,000 pages of information. In addition, virtually all libraries of major universities maintain special-purpose databases of research activities that reflect the distinct specialisms of that university. Beyond the internally generated, special-purpose databases, university libraries and reference libraries maintain online databases with instructions relating to what may be accessed and how it may be accessed. Another library source worth examining for online sources is the European Commission’s ‘Libraries’ site (http://europa.eu). The site, which is multilingual, is distributed by the EUROPA server, the portal site of the EU. It provides up-to-date coverage of European affairs and essential information on European integration. Users can access the websites of each of the EU institutions.

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Syndicated sources of secondary data Syndicated sources (services) Information services offered by marketing research organisations that provide information from a common database to different firms that subscribe to their services.

In addition to published data, or data available in the form of online databases, syndicated sources constitute the other major source of external secondary data. Syndicated sources, also referred to as syndicated services, are companies that collect and sell common pools of data designed to serve information needs shared by a number of clients. These data are not collected with a focus on a specific marketing problem, but the data and reports supplied to client companies can be personalised to fit specific needs. For example, reports could be organised based on the clients’ sales territories or product lines. Using syndicated services is frequently less expensive than commissioning tailored primary data collection. Figure 4.4 presents a classification of syndicated sources. Syndicated sources can be classified based on the unit of measurement (households and consumers or institutions). Household and consumer data may be obtained from surveys, purchase and media panels, or electronic scanner services. Information obtained through surveys consists of values and lifestyles, advertising evaluation, or general information related to preferences, purchase, consumption and other aspects of behaviour. Diary panels can focus upon information on purchases or media consumption, as illustrated in the following example. Electronic scanner services might provide scanner data only, scanner data linked to panels, or scanner data linked to panels and (cable) TV. When institutions are the unit of measurement, the data may be obtained from retailers, wholesalers or industrial firms. An overview of the various syndicated sources is given in Table 4.3. Each of these sources will be discussed.

Figure 4.4 Unit of measurement

A classification of syndicated services

Households/ consumers

Institutions

Retailers

Panels

Purchase

Audits

Media

Industrial firms

Electronic scanner services

Surveys

Psychographics and lifestyles

Wholesalers

General

Voluming tracking data

Direct enquiries

Advertising evaluation

Scanner panels

Scanner panel with cable TV

Clipping services

Corporate reports

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Real research

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Making the news14 In a technology-enabled world, where online news aggregation is common, mobile internet is a reality and social networking is mainstream, how do people consume news? A Taylor Nelson Sofres (TNS) (www. tnsglobal.com) syndicated study researched news consumption by addressing the intersections between the platforms (conventional platforms, from newspapers and TV to radio and news websites, as well as word-of-mouth channels), news brands, content and news consumers that constitute the news world. The study delivered to multiple clients a detailed understanding of the role and place of news in the lives of consumers. It provided evidence of the complex nature of news gathering, revealing how a news story first sparks interest, to where further information is sourced, both online and offline, to flesh out a story, through to the impact each platform and brand has on conveying facts, forming opinion and encouraging the sharing of opinion with others – thus extending the life cycle of the story and starting the news cycle afresh. The study relied on an innovative qualitative methodology, inspired by ethnography and made possible by technology, which allowed the observation and probing of research participants in any product category. Over the course of 10days, participants recorded all their contact with news, noting what they consumed, what stories attracted them and why, the platforms and brands they used and how they followed up and passed on the news. They were able to post links, photos, videos and comments throughout the day. TNS monitored their journeys, observing the participants’ routines and their thoughts and feelings as the news unfolded. This intensive process produced a rich record of news consumption and a valuable multimedia repository of information to review. In a follow-up stage, TNS met the participants in person in small groups, to talk through their diaries and explore themes thrown up by the online journeys; what caught their attention and why; the role of news in their lives, patterns of consumption and the relationship between platforms. Using mapping exercises, personification and other projective techniques, participants were asked about their perceptions of media brands and their relative positions, as well as about their expectation for the future of news consumption. Most participants were extremely engaged and committed, were compliant, doing all that was asked of them, and were unconstrained by the method. Some posted very personal contributions and had to be reminded that their contributions would be seen by others. As expected, there were also some poor contributors; some missed their daily updates, failed to upload photos and videos, were short on detail in their diary entries and provided little explanation. Participants could choose to say what they wanted about themselves as no one could check. However, TNS’s research did have a mechanism for accountability, because the participants knew they would meet TNS face to face at the end of the diary period.

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Table 4.3

Overview of syndicated services

Type

Characteristics

Advantages

Disadvantages

Surveys

Surveys conducted at regular intervals

Most flexible way of obtaining data; information on underlying motives

Market segmentation, Interviewer errors; advertising-theme participant errors; response-rate challenges selection and advertising effectiveness

Purchase panels

Households provide specific information regularly over an extended period of time; participants asked to record specific behaviour as it occurs

Recorded purchase behaviour can be linked to the demographic/ psychographic characteristics

Lack of representativeness; response bias; maturation

Media panels

Same as purchase Electronic devices panels automatically recording behaviour, supplemented by a diary

Scanner volume– tracking data

Household purchases recorded through electronic scanners in supermarkets

Scanner panels Scanner panels of with cable TV households that subscribe to cable TV

Data reflect actual purchases; timely data, less expensive

Uses

Forecasting sales, market share and trends;establishing consumer profiles, brand loyalty and switching; evaluating test markets, advertising and distribution

Same as purchase panels Establishing advertising; selecting media programme or air time; establishing viewer profiles Price tracking, modelling Data may not be representative; errors in effectiveness of in-store promotions recording purchases; difficult to link purchases to elements of marketing mix other than price

Data may not be Data reflect actual representative; quality of purchases; sample data limited control; ability to link panel data to household characteristics

Promotional mix analyses, copy testing, new-product testing, positioning

Relatively precise Audit services Verification of product movement by examining information at retail and wholesale levels physical records or performing inventory |analysis

Coverage may be incomplete; matching of data on competitive activity may be difficult

Measurement of consumer sales and market share; competitive activity; analysing distribution patterns; tracking of new products

Industrial product syndicated services

Data can be lacking in terms of content, quantity and quality, i.e. this equates more with business and competitor intelligence services

Determining market potential by geographical area; defining sales territories; allocating advertising budget

Data banks on industrial establishments created through direct enquiries of companies, clipping services and corporate reports

Important source of information in industrial firms; particularly useful in initial phases of research projects

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Syndicated data from households Surveys Surveys Interviews with a large number of participants using a questionnaire.

Omnibus survey A distinctive form of survey that serves the needs of a syndicate group. The omnibus survey targets particular types of participants such as those in specific locations, e.g. Luxembourg residents, or customers of particular types of product, e.g. business air travellers. With that target group of participants, a core set of questions can be asked, with other questions added as syndicate members wish.

Real research

Many marketing research companies offer syndicated services by conducting surveys and omnibus surveys. As with any survey, the process involves interviews with a large number of participants using a pre-designed questionnaire. (Survey design and the relative advantages and disadvantages of different survey types will be discussed in detail in Chapter 10.) The distinction made here is that rather than designing a survey for the specific needs of a client company, the syndicated survey is designed for a number of client companies. The needs of sometimes quite a disparate array of client companies can be met by a syndicated survey. The key benefits of the syndicated survey lie in combining the resources of a number of clients to craft a survey of high quality and the economies of scale this may bring to individual clients. The downside may be that not all the information needs of an individual client may be met, and additional primary data may need to be collected. One of the most prolific forms of syndicated survey is the omnibus survey. The distinction of the omnibus survey compared with ad hoc surveys is that they target particular types of participants, such as those in certain geographical locations – e.g. Luxembourg residents, or consumers of particular types of products – e.g. business air travellers. The following example illustrates just one of many omnibus surveys conducted by Ipsos MORI (www.ipsos-mori.com).

Clients speak their minds about UK advertising agencies15 Marketers rarely miss an opportunity to tell advertising agencies what they think of them. So there were few refusals to participate in a study of clients’ views on the UK communications industry. Conducted on behalf of the Institute of Practitioners in Advertising (www.ipa.co.uk), a section of Ipsos MORI’s (www.ipsos-mori.com) ongoing omnibus survey, Captains of Industry, asked a key question: ‘Were advertising and communications agencies good at supplying advice on intangible asset creation?’ The sample comprised 99 boardroom executives selected from a universe that included (1) the UK’s top 500 companies by market capitalisation; (2) the top 500 by turnover; and (3) the top 100 by capital employed. In answer to that key question, 64% replied ‘Yes – they did consider advertising and communications agencies as good at supplying advice on intangible asset creation.’ Other perceptions of advertising and communications agencies included: ‘26% indicated that advertising and communications agencies were good at supplying advice on organic growth creation whilst 37% indicated that they were poor at this’. Among those participants that make use of advertising and communications agencies (84), 55% rated the quality of management at the main marketing and communications agency they used as above average. In response to the survey, IPA President Moray Maclennan commented: The IPA and its members lead the way in championing effectiveness, which made it doubly appropriate to measure progress in our boardroom agenda. The data threw down a challenge to the industry regarding its reputation for generating organic growth.

With a defined target group of participants, a core set of questions can be asked, with other questions added as syndicate members wish. Other syndicate members can ‘jump on the omnibus’ and buy the answers to all the questionnaire responses, or to specific questions

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of their choice. Surveys and omnibus surveys may be broadly classified, based on their content, as psychographics and lifestyles, advertising evaluation, or general surveys. Psychographics Quantified profiles of individuals based upon lifestyle characteristics.

Lifestyles Distinctive patterns of living described by the activities people engage in, the interests they have andthe opinions they hold of themselves and the world around them.

1 Psychographics and lifestyles. Psychographics refers to the psychological profiles of individuals and to psychologically based measures of lifestyle. Lifestyles refers to the distinctive modes of living of a society or some of its segments. Together, these measures are generally referred to as activities, interests and opinions.16 Companies may wish to buy syndicated data that describe the lifestyles of consumers, as this can help them to understand further the characteristics of their existing and, especially, potential customers. A good example of a marketing research agency that works upon the measurement and marketing applications of lifestyles can be found at the Natural Marketing Institute (www.nmisolutions.com). 2 Advertising evaluation. The purpose of using surveys to evaluate advertising is to assess the effectiveness of advertising that may be delivered through print, broadcast, online, outdoors and social media.17 A good example of a marketing research agency specialising in advertising evaluation is Harvey Research (http://harveyresearch.co.uk). Evaluation of effectiveness is critical to all forms of advertising. Companies that communicate to target consumers wish to understand the impact of their advertisements and thus the return on their advertising investment. Companies that sell advertising space and services wish to demonstrate that their medium will have the best impact on particular consumers.18 The sums involved in planning, creating and delivering effective advertising mean that research has long played a part in supporting advertising decisions, and surveys continue to play a major role in that evaluation process. The subject of advertising research has a long history and very large literature base, with strong academic and practitioner viewpoints.19 A few examples may illustrate the complexity and value of advertising research. TV advertisements can be evaluated using either the recruited audience method or the in-home viewing method. In the former method, participants are recruited and brought to a central viewing facility, such as a theatre or mobile viewing laboratory. The participants view the advertisements and provide data regarding their knowledge, attitudes and preferences related to the product being advertised and the advertisement itself. In the in-home viewing method, participants evaluate advertisements at home in their normal viewing environment. New advertisements can be pre-tested at the network level or in local markets distributed via DVDs. A survey of viewers is then conducted to assess the effectiveness of the advertisements. One of the main contemporary challenges in measuring the impact of advertising is in isolating a specific medium, as illustrated in the following example. This example shows that creative research designs can be used to isolate and measure the impact of a single communications medium.

Real research

It can be measured20 Radio Ad Effectiveness Lab (RAEL, www.radioadlab.org) was founded in 2001 and is dedicated to providing research about how radio advertising works. One of its first studies was dedicated to the return on investment (ROI) on radio advertising. With the help of Millward Brown (www.millwardbrown.com) and Information Resources Symphony (IRI www.symphonyiri.com) and four adventurous advertisers, RAEL created a ‘realworld’ test. RAEL used IRI’s BehaviorScan Targetable TV test market capabilities to control the delivery of TV advertisements household by household, while simultaneously using test and control markets to deliver or not deliver radio advertising. This involved a six-month test of actual advertising campaigns for multiple advertisers. RAEL created four matching test cells: one with no local radio or national TV advertising; one with only the national TV ads; one with only an equivalent weight of local radio advertising;

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and one with equivalent weights of both national TV and local radio advertising. Alongside the survey data collected, RAEL also had corresponding scanner shopping data from IRI for four national advertisers. At the end of the six-month period, RAEL looked at the cell-by-cell details for each advertiser. On a sales-lift basis, the radio campaigns for the four advertisers acquitted themselves very well. The radio campaigns were linked to a statistically significant sales lift of 4.1%. Meanwhile, TV, with a much higher spend level, accounted for 7.5% in additional sales. When advertising costs were considered, radio delivered 49% better ROI than the corresponding (and similar weights of) national TV advertising.

3 General surveys. Syndicated surveys are also conducted for a variety of other purposes, including examination of purchase and consumption behaviour. Because a variety of data can be obtained, survey data have numerous uses. They can be used for market segmentation, as with psychographic and lifestyle data, and for establishing consumer profiles. Surveys are also useful for determining product image, measurement and positioning, and conducting price perception analysis.

Purchase and media panels

Media panels A data-gathering technique composed of samples of participants whose TV viewing behaviour is automatically recorded by electronic devices, supplementing the purchase information recorded in a diary or blog.

Real research

About a fifth of all research budgets is spent on panels in their various formats, among the largest investors in this format in Europe being Switzerland at 38%, Germany at 34% and the Netherlands at 31%.21 Panels were discussed in Chapter 3 in the context of longitudinal research designs. Panels are samples of participants who provide specified information at regular intervals over an extended period of time. These participants may be organisations, households or individuals, although household panels are most common. The distinguishing feature of panels is that the participants record specific behaviours as they occur. Previously, behaviour was recorded in a handwritten diary, and the diary returned to the research organisation every one to four weeks. Panel diaries have been gradually replaced by electronic diaries and blog diaries.22 Now, most panels are online, and consumption and media behaviour is recorded electronically, either entered online by the participants or recorded automatically by electronic devices. In media panels, electronic devices automatically record viewing behaviour, thus supplementing a diary. Media panels yield information helpful for establishing advertising rates by radio and TV networks, selecting appropriate programming and profiling viewer or listener subgroups. Advertisers, media planners and buyers find panel information particularly useful. Another media vehicle that competes heavily for advertising budgets is the internet. The following example illustrates how TNS use media panels to understand the likelihood of viewers responding to advertisements.

Targeting ad responders23 The Skyview panel, conceived and developed by BSkyB (www.sky.com) and TNS (www. tnsglobal.com), comprises 33,000 Sky households, from which detailed second-by- second TV viewing data covering all TV channels is collected via a set-top box. Of these homes, 6,000 are also members of Worldpanel, the service operated by TNS, which provides details on each household’s purchasing of grocery products on a continuous basis. Sky Media (www.skymedia.co.uk) is the media sales arm of BSkyB and it wanted to use

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data from Worldpanel to identify which households are the most responsive to advertising. Having identified these ‘high responders’, Sky Media could then go on to examine their viewing patterns and thus find ways in which advertising could be more effectively targeted at the most responsive buyers through the better use of timing advertisements throughout the day, on certain channels and specific programmes. Worldpanel data reveal when each household made a purchase of a product category and whether the advertised brand or another brand was bought. It was possible to count the number of times the advertised brand was bought when the household was exposed to the brand’s advertising. Sky Media built upon this relationship to help predict the likelihood of someone responding to an advertisement. To investigate this Sky Media studied 33brands across three categories: breakfast cereals, shampoo and yogurts. In each case it identified the ‘ad responders’. For each panellist it added a description of their demographics, together with their scores on 137 attitudinal statements and their propensity to view TV. On average, 13% of panellists were classified as ‘ad responders’. Those with the highest propensity to be ad responders were people who liked advertising, were heavy consumers of commercial TV and had two or more people in the household. By contrast, the least responsive were those who claimed not to like advertising, were living on their own and working full time.

Purchase panels A data-gathering technique in which participants record their purchases, either online or in a diary or blog.

Real research

Purchase panels provide information useful for forecasting sales, estimating market shares, assessing brand loyalty and brand-switching behaviour, establishing profiles of specific user groups, measuring promotional effectiveness and conducting controlled store tests. Compared with sample surveys (see Chapter 10), panels offer certain distinct advantages.24 Panels can provide longitudinal data (data can be obtained from the same participants repeatedly). They enable specific types of consumer to be targeted for study, relatively quicker than generating a bespoke sample. People who are willing to serve on panels may be more motivated to engage in a particular study and thus provide more and higher-quality data than one-off sample participants. In purchase panels, information is recorded at the time of purchase, eliminating recall errors.25 If information is recorded by electronic devices, it is generally more accurate as it eliminates recall errors. The disadvantages of panels include lack of representativeness, maturation and response biases.26 This problem is further compounded by refusal to respond and attrition of panel members. Over time, maturation sets in, and the panel members should be replaced. Response biases may occur, since simply being on the panel may alter behaviour. There has been much debate on the challenges of creating representative and/or probability-based samples, with some researchers claiming that panels are an unsustainable research method.27 (Due to the seriousness of this latter claim, the ‘scientific rigour’ of panels is further explored in Chapters 14 and 15.) In spite of these disadvantages, purchase panels are extensively used in marketing research, and the following example illustrates how they can effectively support decision makers.

SCI INTAGE – A Japanese nationwide retail panel survey28 In 1960, a time when Japan was fast developing into a consumer market, Marketing Intelligence Corporation (MiC), the forerunner of INTAGE Inc., was established as Japan’s first true comprehensive marketing research organisation. The fledgling firm’s first businesses were SDI (nationwide drug-store panel research) and custom research. In 1964 the company launched SCI, a nationwide household consumer panel research

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(www.intage.co.jp/english). SCI was based upon a sample of 12,008 two- or more member households. Data from this study were extensively used by Japanese retailers and the following example shows how SCI supported decision makers. One-day-only sales and short-term discount promotions were often run by Japanese retailers. Such price changes entailed costly operational and stock control complexities. Why did they change prices at short intervals despite the drawbacks? The situation had its basis in the unique characteristics of the purchasing behaviour of Japan’s consumers. According to SCI data on housewife purchasing behaviour, even when shopping for perishable foods is excluded, housewives shopped at supermarkets 2.5 times per week. Japanese housewives on average shopped at 4.7 supermarkets and 13.3 stores across all SCI channels during the course of a year. What these data revealed was that Japan’s consumers shopped every few days and at different stores rather than always shopping at the same stores. For this reason, retailers wanted to offer novel experiences to attract customers to their stores on as many shopping occasions as possible. They did not wish to continue discounting of a single product for a full week, but rather to rotate products frequently to be discounted for short periods of time.

Electronic scanner services The following example illustrates the nature and value of electronic scanner services, as undertaken by A.C. Nielsen, Worldwide Consumer Panel Services (http://uk.nielsen.com). A.C. Nielsen’s Panel Services operates in 27 countries, based on consumer purchase information from over 210,000 households. Another major global research company worth examining with expertise in panel services and electronic scanning is Kantar (www. kantarworldpanel.com).

Real research

A.C. Nielsen Worldwide Consumer Panel Services A.C. Nielsen Homescan was launched in 1989, the first continuous consumer panel in Europe to use in-home bar code scanners to collect data. The panel is regionally and demographically balanced to represent the household population and captures consumer package goods purchases brought back into the home, including variable weight and non-bar-coded fresh products. Each household provides daily information on its purchases of consumer goods for in-home use. Collected on a continuous basis, it is possible to measure the ongoing changes and interactions of households’ purchasing behaviour across all grocery and fresh-food products. Homescan incorporates both descriptive and diagnostic information. Consumer panel data provide information on purchaser attributes, purchase behaviour, market penetration, share of category requirements, brand loyalty, brand switching and parallel consumption, plus a wide range of other powerful analytics. The database provides insights into why consumers behave the way they do. Subscribers can get answers to questions specific to their brand, such as: How many households purchased a product on a trial basis? Did they return later to purchase again? What did buyers purchase before a marketing campaign; what did they purchase subsequently? Where did buyers of a brand come from? What else do buyers purchase? Where else do buyers shop? How store-loyal are shoppers? What is the demographic composition of buyers? How do lifestyles and attitudes impact upon purchasing behaviour?

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Scanner data Data obtained by passing merchandise over a laser scanner that reads the UPC from the packages.

Volume-tracking data Scanner data that provide information on purchases by brand, size, price and flavour or formulation.

Scanner panels Scanner data where panel members are identified by an ID card, allowing information about each panel member’s purchases to be stored with respect to the individual shopper.

Scanner panels with cable TV The combination of a scanner panel with manipulations of the advertising that is being broadcast by cable TV companies.

Real research

Although information provided by surveys and purchase and media panels is useful, electronic scanner services have continued to deliver great value to decision makers. (The role of scanned data as a foundation to developing sophisticated consumer databases is developed further in Chapter 5.) In this chapter we examine scanned data as a distinct source of syndicated data. Scanner data relates to retail data collected by bar codes at electronic checkouts. This code is then linked to the current price held on the computer and used to prepare a sales slip. Information printed on the sales slip includes descriptions as well as prices of all items purchased. Checkout scanners have revolutionised packaged goods marketing research. Three types of scanner data are available: volume-tracking data, scanner panels and scanner panels with cable TV. Volume-tracking data provide information on purchases by brand, size, price and flavour or formulation, based on sales data collected from the checkout scanner. This information is collected nationally from a sample of supermarkets (rather than individual supermarkets tracking their customers’ purchases using loyalty cards) with electronic scanners. In scanner panels, each household member is given an ID card. Panel members present their ID card at the checkout counter each time they shop. The checker scans their ID and each item of that customer’s order. The information is stored by day of week and time of day. Scanner panels with cable TV combine panels with new technologies growing out of the cable TV industry. Households on these panels subscribe to one of the cable or TV systems in their market. By means of a cable TV ‘split’, the researcher targets different advertisements into the homes of the panel members. For example, half the households may see test advertisement A during the 6 pm newscast while the other half see test advertisement B. These panels allow researchers to conduct fairly controlled experiments in a relatively natural environment. It is possible to combine store-level scanner data with scanner panel data to do integrated analyses of consumer behaviour. This was illustrated with the earlier Real Research example of the Skyview panel developed by BSkyB and TNS. The following example illustrates how panel and scanning organisations such as Nielsen are striving to make this work.

From fragmentation to integration29 Paul Donato is Executive Vice President and Chief Research Officer for The Nielsen Company (www.nielsen.com). His responsibilities include integrating all research functions within The Nielsen Company, overseeing the development and evaluation of all research and serving as Nielsen’s research liaison to clients and industry associations. In describing Nielsen’s drive to integrate more of its data he illustrated this through NielsenConnect: The concept of Connect is based on the fact that there are limits to how much you can ask any one person within a survey. That makes a strong case for integrating various databases with our people-meter panel (http://www.agbnielsen.net). We do this via a hub, where we take homes from the people-meter panel and for two years collect other media usage data from these homes. To start with, we put a Niesen/NetRatings meter in these panel households, but in the long term we may also measure other media. One of our visions is to measure internet usage in as many TV people-meter homes as we can. We have done some tests and we know that people react to internet measurement differently and we estimate that realistically only 30–40% of people-meter households will sign up for internet measurement as well. Our plan is to grow the number of TV panel households to around 37,000, which should yield approximately 12–13,000 TV plus online panel homes onto which the balance of the 130,000-strong Nielsen/NetRatings panel. Importantly, for internet measurement advertisers they will benefit from the large 130,000 sample, which enables them to evaluate smaller, more specialist sites.

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Scanner data are useful for a variety of purposes.30 National volume-tracking data can be used for tracking sales, prices and distribution, for modelling and for analysing early warning signals. Scanner panels with cable TV can be used for testing new products, repositioning products, analysing promotional mixes and making advertising decisions, including budget, copy and media and pricing. These panels provide researchers with a unique controlled environment for the manipulation of marketing variables.

Real research

GfK BEHAVIORSCAN GfK BEHAVIORSCAN tests advertising spots in a random sample of the test households. Because of the capability to split these into test and control groups, a range of different budgets or campaigns can be tested and compared. The comparability of test and control groups is achieved by ‘matching’, a mathematical optimisation program. Comparability is based on socio-demographic factors, purchasing behaviour in the category and, as far as the product is established, on the test product. GfK BEHAVIORSCAN can test the entire marketing mix of a product in a real environment controlled by members of the GfK team to produce results at the level of a complete household panel. It can help answer important questions such as: How many trial buyers do I gain? How satisfied are the customers? Which product variants and which packet size sell best? How do TV advertisements work? How profitable is the invested advertisement budget? How profitable are campaigns, mail shots, vouchers and in-home samples? What market share will I achieve with my new product? Which competitor does it attack and who will lose out?

Scanner data have an obvious advantage over surveys and panels: they reflect purchasing behaviour that is not subject to interviewing, recording, memory or expert biases. The record of purchases obtained by scanners is complete and unbiased by price sensitivity, because the panellist is not required to be particularly conscious of price levels and changes. Another advantage is that in-store variables such as pricing, promotions and displays are part of the dataset. The data are also likely to be current and can be obtained quickly. Finally, scanner panels with cable TV provide a highly controlled testing environment. A major weakness of scanner data can be a lack of representativeness. National volumetracking data may not be projectable onto the total population. Not all purchases are scanned in the manner of large supermarkets. Many types of retail and wholesale outlets, which consumers may physically or virtually shop at, may well be excluded. Scanner data provide product and media behavioural and sales information, but they do not provide information on underlying attitudes and preferences and the reasons for specific choices.

Syndicated data from institutions Retail audits Audit A data-collection process derived from physical records or performing inventory analysis. Data are collected personally by the researcher, or by representatives of the researcher, and are based on counts usually of physical objects rather than people.

As Figure 4.4 shows, syndicated data are available from retailers as well as industrial firms. A retail audit is a regular survey that monitors sales of products via a sample of retail outlets. Retail audit data allow decision makers to analyse their product structure, pricing and distribution policy, and their position in relation to their competition. The most popular means of obtaining data from retailers is an audit. This is a formal examination and verification of product movement carried out by examining physical records or analysing inventory. Retailers who participate in the audit receive basic reports and cash payments from the audit service, but the main beneficiary is the brand owner who wishes to monitor the

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sales of the brand through many retail outlets. Audit data focus on the products or services sold through the outlets or the characteristics of the outlets themselves. The uses of retail audit data include: (1) determining the size of the total market and the distribution of sales by type of outlet, region or city; (2) assessing brand shares and competitive activity; (3) identifying shelf-space allocation and inventory problems; (4) analysing distribution problems; (5) developing sales potentials and forecasts; and (6) developing and monitoring promotional allocations based on sales volume. Thus, audit data can be particularly helpful in understanding and developing the environmental context, should further stages of research need to be administered. Audits provide relatively accurate information on the movement of many different products. Furthermore, this information can be broken down by a number of important variables, such as brand, type of outlet and size of market. Audits may have limited coverage; not all categories of particular products or brands are necessarily included. In addition, audit information may not be timely or current, particularly compared with scanner data. At one time, there could be a twomonth gap between the completion of the audit cycle and the publication of reports. Another disadvantage is that, unlike scanner data, audit data cannot be linked to consumer characteristics. In fact, there may even be a problem in relating audit data to advertising expenditures and other marketing efforts. Some of these limitations are overcome in online audit panels. GfK (www.gfk.com/solutions/point-of-sales-tracking/point-of-sales-tracking/) performs online tracking in over 80 countries and covers markets such as tourism, optics and fashion. The following example illustrates the nature and value of its work for fashion brands.

Real research

GfK FashionLife GfK FashionLife offers market figures and the fast, fact-based delivery of detailed information to allow companies to steer their performance accordingly. The power to benchmark products and markets allows fashion companies to maintain a firm grip on insights by channel. Reporting includes information on sales volume, sales value and average prices, and forms the basis for a continuous service for both retailers and suppliers within the fashion industry. Reports are available from toplevel aggregation down to single-product level, and are customisable according to individual client needs. Delivery is on a monthly or weekly basis. Fashion products tracked by GfK FashionLife include: watches, luggage, jewellery, clothing and shoes, leisure and home textiles. GfK pitches the benefits of its online retail audit for fashion businesses as: fast weekly data directly from retailers; high levels of granularity in reporting; a basis for decisions on product assortments and ranges; a platform for understanding performance against competitors and the impact price has on market share; additional information to help target advertising and promotional activities; and help in maximising stock efficiency.

Industry services These provide syndicated data about industrial firms, businesses and other institutions. Examples of these services include Datamonitor, Bureau Van Dijk and Dun and Bradstreet. Datamonitor (www.datamonitor.com) is a provider of global business information delivering data, analysis and opinion across the automotive, consumer packaged-goods,

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energy and sustainability, financial services, logistics, pharmaceutical and health care, retail, sourcing, technology and telecoms industries. It supports over 6,000 of the world’s leading companies in strategic and operational decision making. Its market intelligence products and services are delivered online. Bureau Van Dijk (www.bvdinfo.com) provides a range of company information products that are co-published with many renowned information providers. Its product range includes databases of company information and marketing intelligence for individual countries, regions and worldwide. Its global database, Orbis, combines information from around 100 sources and covers nearly 65 million companies. It also provides e-publishing solutions, based on open and flexible platforms, and offers features such as search, secure delivery, e-commerce, rendering systems and hosting. Clients include publishers of books, scientific, technical and medical journals, news, directories and reference guides. Dun and Bradstreet (www.dnb.com, but also look for specific countries, e.g. Netherlands, http://dbnetherlands.dnb.com) has a global commercial database that contains more than 151 million business records. Through the D&B Worldwide Network clients gain access to perhaps the world’s largest global commercial business information database. D&B has global data coverage on business records in over 190 countries. To help ensure the accuracy and completeness of its information, D&B uses sophisticated data-collection tools and updates the database over 1.5 million times a day. Information provided by industrial services is useful for sales management decisions, including identifying potential target markets, defining territories and measuring market potential by geographical areas. It can also support communications decisions such as targeting prospects, allocating communications budgets, selecting media and measuring communications effectiveness. Given the rich competitive intelligence available, these sources of information are also useful for segmentation and positioning decisions. Industry services represent an important contextual source of support in defining the environmental context for management decisions and any subsequent bespoke marketing research. They are particularly valuable for researchers who aim to measure and understand the networks and relationships of industrial firms (to be addressed in more detail in Chapter 28).

Summary

In contrast to primary data, which originate with the researcher for the specific purpose of the problem at hand, secondary data and marketing intelligence are data originally collected for other purposes. Secondary data can be obtained quickly and are relatively inexpensive, though not free, especially for accurate, high-quality data. Secondary data have limitations, and should be carefully evaluated to determine their appropriateness for the problem at hand. The evaluation criteria consist of specifications, error, currency, objectivity, nature and dependability. A wealth of information exists in the organisation for which the research is being conducted. This information constitutes internal secondary data. External data are generated by sources outside the organisation. These data exist in the form of published (printed) material, online and offline databases, or information made available by syndicated services. Published external sources may be broadly classified as general business data or government data. General business sources comprise guides, directories, indexes and statistical data. Government sources may be broadly categorised as census data and other data. Online databases may be online or offline. Both online and offline databases may be further classified as bibliographic, numeric, fulltext, directory or specialised databases.

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Syndicated sources are companies that collect and sell common pools of data designed to serve a number of clients. Syndicated sources can be classified based on the unit of measurement (households and consumers or institutions). Household and consumer data may be obtained via surveys, purchase or media panels, or electronic scanner services. When institutions are the unit of measurement, the data may be obtained from retailers or industrial units. It is desirable to combine information obtained from different secondary sources. Several specialised sources of secondary data are useful for conducting international marketing research. The evaluation of secondary data becomes even more critical, however, because the usefulness and accuracy of these data can vary widely. Ethical dilemmas that can arise include the unnecessary collection of primary data, the use of only secondary data when primary data are needed, the use of secondary data that are not applicable and the use of secondary data that have been gathered through morally questionable means. The growth of online sources of externally generated secondary data has exerted demands upon researchers to be able to access, integrate and interpret these data. The emergence of social media research techniques has generated not only new research techniques, but also new forms of data that could raise questions about what constitutes ‘secondary data’ and ‘marketing intelligence’.

Questions

1 What are the differences between primary data, secondary data and marketing intelligence? 2 What are the relative advantages and disadvantages of secondary data? 3 At what stages of the marketing research process can secondary data be used? 4 Why is it important to locate and analyse secondary data before progressing to primary data? 5 How may secondary data be used to validate qualitative research findings? 6 What is the difference between internal and external secondary data? 7 How can intranets help in the location and dissemination of secondary data? 8 By what criteria may secondary data be evaluated? 9 What criteria would you look for when examining the design and specifications of secondary data? Why is it important to examine these criteria? 10 To what extent should you use a secondary data source if you cannot see any explicit objectives attached to that research? 11 If you had two sources of secondary data for a project, the first being dependable but out of date, the second not dependable but up to date, which would you prefer? 12 Evaluate the desirability of using multiple sources of secondary data and intelligence. 13 List and describe the main types of syndicated sources of secondary data. 14 Explain what an online panel is, giving examples of different types of panel. What are the advantages and disadvantages of online panels? 15 What is an audit? Describe the uses, advantages and disadvantages of audits.

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1 Select an industry of your choice. Using secondary sources, obtain industry sales figures and the sales of the major firms in that industry for the past year. Estimate the market shares of each major firm. From another source where this work may have already been completed, e.g. Mintel, compare and contrast the estimates: a To what extent do they agree? b 2

If there are differences in the estimates, what may account for these differences? Select an industry of your choice. Write a report on the potential growth in that industry and the factors that are driving that growth. Use both secondary data and intelligence sources to build your case. Using your library’s online databases, search through secondary data sources to gather data on the use of celebrities in the promotion of fashion brands. You are conducting a marketing research project to determine the effectiveness of celebrity endorsements in Louis Vuitton Moet Hennessy (www.lvmh.com). What secondary data sources have you found to be the most useful? As a marketing director at LVMH, how would you use secondary data that describe celebrity endorsement investments to determine whether you should continue to use celebrities in LVMH advertising campaigns? Visit the Eurostat website (ec.europa.eu/eurostat/web/links/) and follow a link to the national statistics office in a country of your choice. Write a report about the secondary data available from this office that would be useful to a national housing developer for the purpose of formulating its marketing strategy In a small group, discuss the following issues: ‘What are the significance and limitations of government census data for researchers?’ and ‘Given the growing array of alternative data sources that describe characteristics of individuals and households in a country, would it be a disaster for researchers if formal government censuses were scrapped?’

Notes 1. Peters, J., Appleby, M. and LaRue, S., ‘Virgin USA – a 21st century approach to brand development’, ESOMAR Annual Congress, Montreal (September 2008). 2. Fleisher, C.S., ‘Using open source data in developing competitive and marketing intelligence’, European Journal of Marketing 42 (7/8) (2008), 852–66; Rothberg, H.N. and Erickson, G.S., From Knowledge to Intelligence: Creating Competitive Advantage in the Next Economy (Burlington, MA: Butterworth–Heinemann, 2005); Aguilar, F.J., Scanning the Business Environment (London: Macmillan, 1967). 3. Adapted from Brownlie, D., ‘Environmental scanning’, in Baker, M.J., The Marketing Book, 3rd edn (Oxford: Butterworth–Heinemann, 1998), 158. 4. Mitchelson, L., ‘Gathering business intelligence in China – the ups and downs’, Admap Magazine, China supplement (February 2008).

5. Neves, M.A., ‘Strategic marketing plans and collaborative networks’, Marketing Intelligence & Planning 25 (2) (2007), 175–92; Rothberg, H.N. and Erickson, G.S., From Knowledge to Intelligence: Creating Competitive Advantage in the Next Economy (Burlington, MA: Butterworth–Heinemann, 2005), 21. 6. Dugmore, K., ‘Viewpoint: Public information – now it’s time to make it freely available’, International Journal of Market Research 49 (2) (2007), 153–4. 7. For applications of secondary data, see Allen, L. and Spencer, N., ‘Managing knowledge, maximising returns – revolutions in business information management’, ESOMAR Congress, Montreux (September 2009); Houston, M.B., ‘Assessing the validity of secondary data proxies for marketing constructs’, Journal of Business Research 57 (2) (2004), 154–61; Kotabe, M., ‘Using Euromonitor database in international marketing

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research’, Journal of the Academy of Marketing Science 30 (2) (Spring 2002), 172. 8. Foan, R., ‘Measuring media internet’, Admap Issue 496 (2008), 28–31. 9. Piercy, N.F., ‘Evolution of strategic sales organizations in business-to-business marketing’, Journal of Business & Industrial Marketing 25 (5) (2010), 349–59; Lawson, J., ‘Buying behaviour’, Database Marketing (October 2004), 35–8. 10. Allen, L. and Green, C., ‘Connecting insight with the organisation: knowledge management online’, Market Research Society, Annual Conference (2006); Fries, J.R., ‘Library support for industrial marketing research’, Industrial Marketing Management 11 (February 1982), 47–51. 11. Tasgal, A., ‘Inspiring insight through trends’, Market Research Society, Annual Conference (2009). 12. Jackson, M., Gider, A., Feather, C., Smith, K., Fry, A., Brooks-Kieffer, J., Vidas, C.D. and Nelson, R., ‘Electronic Resources & Libraries, 2nd Annual Conference 2007’, Library Hi Tech News 24 (4) (2007), 4–17. 13. Saw, G., Lui, W.W. and Yu, F., ‘2010: A library odyssey’, Library Management 29 (1/2) (2008), 51–66; Tenopir, C., ‘Links and bibliographic databases’, Library Journal 126 (4) (1 March 2001), 34–5. 14. Vir, J., Simpson, I. and Brown, K., ‘Making the news’, Market Research Society, Annual Conference (2009). 15. Anon., ‘Clients speak their minds about UK ad agencies’, WARC News (1 February 2008). 16. Lekakos, G., ‘It’s personal: Extracting lifestyle indicators in digital television advertising’, Journal of Advertising Research 49 (4) (December 2009), 404–18. 17. Bennett, G., Ross, M., Uyenco, B. and Willerer, T., ‘Lifestyles of the ad averse: A proposal for an advertising evaluation framework’, ESOMAR, Worldwide Multi Media Measurement (WM3), Dublin (June 2007). 18. Hu, Y., Lodish, L.M., Krieger, A.M. and Hayati, B., ‘An update of real-world TV advertising tests’, Journal of Advertising Research 49 (2) (June 2009), 201–6. 19. Nyilasy, G. and Reid, L.N., ‘The academicianpractitioner gap in advertising’, International Journal of Advertising 26 (4) (2007), 425–45.

20. Peacock, J. and Bennett, M., ‘It can be measured’, Research World (September 2005), 70–1. 21. ESOMAR, ‘Global Market Research’, ESOMAR Industry Report (2010), 104. 22. Bryant, J.A. and Christensen, L., ‘I want MySpace! Helping an industry innovator (re)innovate’, ESOMAR Online Research, Berlin (October 2010). 23. Roberts, A. and Bristowe, L., ‘Targeting ad responders’, Admap Magazine Issue 486 (September 2007). 24. Comley, P., ‘Panel management and panel quality issues – understanding the online panellist’, ESOMAR Conference on Panel Research, Budapest (April 2005); Eunkyu, L., Hu, M.Y. and Toh, R.S., ‘Are consumer survey results distorted? Systematic impact of behavioural frequency and duration on survey response errors’, Journal of Marketing Research 37 (1) (February 2000), 125–33. 25. Clancy, K.J., ‘Brand confusion’, Harvard Business Review 80 (3) (March 2002), 22; Sudman, S., On the Accuracy of Recording of Consumer Panels II, Learning Manual (New York: Neal-Schumen, 1981). 26. Sassinot-Uny, L. and Gadeib, A., ‘Panel satisfaction index. Quality target for online access panels owners?’ ESOMAR Panel Research, Orlando (October 2007). 27. de Jong, K., ‘CSI Berlin: The strange case of the death of panels’, ESOMAR Online Research, Berlin (October 2010). 28. Kondo, T., ‘Creating a win-win relationship by maximizing both manufacturer sales and retailer profits’, ESOMAR Asia Pacific Conference, Tokyo (March 2005). 29. Mareck, M., ‘From fragmentation to integration’, Research World (September 2007), 48–50. 30. Examples of scanner data applications include GonzálezBenito, O., Martínez-Ruiz, M.P. and Mollá-Descals, A., ‘Latent segmentation using store-level scanner data’, Journal of Product & Brand Management 17 (1) (2008), 37–47; Lemon, K.W. and Nowlis, S.M., ‘Developing synergies between promotions and brands in different price-quality tiers’, Journal of Marketing Research 39 (2) (May 2002), 171–85; Chintagunta, P.K., ‘Investigating category pricing behaviour at a retail chain’, Journal of Marketing Research 39 (2) (May 2002), 141–54.

5 Stage 1

Problem definition

Stage 2 Research approach developed

Stage 3 Research design developed

Stage 4 Fieldwork or data collection

Stage 5 Data integrity and analysis

Stage 6 Communicating research findings

Internal secondary data and analytics The research industry needs to evolve in order to weather the digital storm of change that threatens to engulf it.1

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Objectives After reading this chapter, you should be able to: 1 describe the nature and purpose of researchers utilising internal sources of secondary data; 2 appreciate how different types of company databases have developed into powerful means to understand customer behaviour; 3 understand how geodemographic information systems can help in integrating and displaying customer data; 4 understand how customer relationship systems can capture and model customer data and thus support marketing research; 5 understand how web analytics can capture and model customer data and thus support marketing research; 6 appreciate how different sources of customer data and marketing research can build up behavioural and attitudinal profiles of target markets; 7 appreciate the challenges of international data capture issues; 8 understand the ethical problems of having individual consumer data held on databases; 9 appreciate how different technological developments have increased the breadth of internally generated secondary data.

Overview This chapter covers a topic that would have only merited a few paragraphs as recently as 20 years ago, when internal secondary data searches would have been part of primary data collection. The cost and difficulty of collecting internal secondary data, compared to primary data, would have mitigated the potential advantages of these data sources. What has changed? In one word – technology. The growth in the use of internet-enabled services in managing customers, together with the widespread adoption of mobile internet-enabled devices such as smartphones and tablets, has led to an exponential increase in the volume of data available. This increase, combined with the corresponding reduction in the cost of data analysis, has been labelled ‘big data’. These changes have shaped the expectations of decision makers in terms of the information they can rely on to help them make timely and effective decisions. Due to the perceived cost-effectiveness of these new internal data-collection techniques, the pressure has been increased for primary data-collection techniques to justify a return on investment. The growth in secondary data is not without problems. Management expectations are often misplaced, as the growth in data collection far exceeds the ability to successfully analyse the data. There are also issues over access, as internal data, particularly in the case of analytics, may still end up being controlled by a third party. This chapter describes how use of internal secondary data, including analytics and databases, has grown to make major impacts upon how decision makers are supported. We start the chapter with examples of the use of databases, how they can directly support decision making, but also support the implementation of marketing research. We then move onto internal data-collection techniques that make use of unstructured data, particularly those based around the collection of analytics, and discuss the growing popularity of the concept of ‘big data’. Databases generated within companies or bought in from specialist sources are often viewed as a tool to generate direct sales and target promotion activities. However, internally generated customer databases are also a secondary data source of immense value to researchers. The first example illustrates how a customer database in the form of a customer relationship system (CRM) was used to support the development of online surveys. The second example illustrates how a customer database was interrogated and enhanced with the use of geodemographic data in order to develop more refined descriptions of customer segments and to model behaviour.

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Creation of a pan-European online customer panel for Nintendo2 Nintendo wished to develop a platform to integrate online customer surveys with data stored in its CRM system. Globalpark (www.globalpark.com) worked in close cooperation with Nintendo to develop a workflow that networked its existing CRM system with Globalpark survey software. As a result, almost 1 million registered Nintendo customers could be managed and surveyed with its EFS (Enterprise Feedback System) Panel. An interface in the EFS Panel made it possible to extract samples from the customer database according to specific criteria, such as socio-demographic features. The master data could be used to identify suitable participants for a specific survey. Collected data from the survey were then fed back into the integrated system. The entire survey process, from the development of the survey, the recruitment of participants from the Nintendo CRM system and the invitation via email, to field control and the delivery of rewards at the end of the survey, could be coordinated using the EFS Panel. This process allowed Nintendo to conduct online product tests, customer satisfaction analyses, communic ations campaigns and ad hoc marketing research projects.

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Geodemographics at Boden3 Boden (www.boden.co.uk) is renowned for catalogue-based retailing of high-quality women’s, men’s and children’s clothing. Starting in 1991, Johnnie Boden delivered his first catalogue with only eight menswear pieces. Boden now sends out over 20 million catalogues per annum, and 500 employees jointly share responsibility for shipping more than 4,000 orders per day. Boden identified a requirement to gain better insight into its growing customer base and purchased smartFOCUS (www.smartfocus.com) Intelligent Marketing Analysis solutions. This enabled better customer segmentation, with an increase in specific customer cells for targeting from 20 to 80 individual segments. Boden used the smartFOCUS analysis and visualisation, data mining and campaign-planning solutions to enhance its understanding of the 2.2 million people on its database. ‘Propensity to buy’ information, discovered through smartFOCUS, indicated that the womenswear range was delivering faster growth than other ranges; specifically, menswear buyers had a higher lapse rate and were more likely to buy every other year. This type of customer knowledge helped Boden plan more accurately and to forecast more effectively. Its purchase of MOSAIC geodemographic data (www.experian.co.uk/business-strategies) to enhance the Boden customer view enabled even more sophisticated segmentation analyses. Boden improved response rates by profiling profitable customers and identifying groups of prospects with similar profiles for specifically targeted marketing promotions. In addition, improved product transaction history enabled models to be built, ensuring that customer retention was maximised. The awareness and usage of this technology within Boden was also developing, with even the clothing designers requesting profile information on customers to create a better picture of their target audience. Designers wanted to ensure that more of their products met customer expectations.

There is no doubt that the database analyses in these opening examples acted (or could act) as an excellent foundation for marketing research design in deciding who to research and what issues to focus upon. The growth and impact of these sources mean that an examination of the opportunities and challenges inherent in internally generated secondary data is vital; the

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practice of marketing research cannot be independent or ‘siloed’.4 There are arguments that the perceived value of ‘traditional research’ and methods based upon reported attitudes and behaviour are eroding. A key factor in this erosion is that consumer data are now more abundant and automated. For example, web analytics provides masses of behavioural data on what consumers are looking for, what they do on a website, how they got there and, critically, whether they did what was wanted of them (e.g. buying a product). This behavioural data can carry more weight with decision makers, since what someone actually does could be considered more reliable than what they say, think, feel or plan to do. Similarly, online feedback and internally managed customer relationship management surveys are providing customer insight without necessarily involving marketing research in order to gather it.5 Some of the challenges and opportunities generated by the growth of internally generated data are encapsulated in the views of three leading research practitioners in the following example.

Real research

The enlightened researcher6 Colin Shearer, of SPSS (www.ibm.com/software/analytics/spss): I think in the future we will see a reassessment of where marketing research and related disciplines sit within an organisation. Historically, marketing research has been kept separate from things like CRM and marketing. There is a move to use the same techniques used to conduct surveys to collect feedback information from customers and act on it. The term that has been coined for this is ‘Enterprise Feedback Management’. It uses the same tools and techniques as marketing research, but in a different way, so it needs to be reconciled with traditional marketing research as supplied by agencies. Jim Spaeth, of the New York agency Sequent Partners (www.sequentpartners.com): I think marketing research will continue to evolve. The ‘digitalisation’ of almost everything, and the creation of continuous data streams, not for research but to run the business, will continue to change the nature of data collection from ad hoc to continuous. Analytic techniques will be validated through their empirical relationship with important business outcomes, all measured through the same enterprise data stream. Our emphasis will continue to move from data collection to data analysis and onto business decision support. Clare Bruce, CEO of the Consumer Insight Agency Nunwood (www.nunwood.com): There has been a stampede to use web technologies to collect data more quickly. We are using it to analyse data and devolve insight into our clients’ organisations. We also collect data online, but all our research and development from the technology point of view has been focused on enabling clients to disseminate insight more quickly and effectively. Our market analytics division takes the data and provides clients with a more in-depth, more strategic view on how the data can help, and more and more they are being asked to undertake implementation programmes so clients don’t just want answers to the questions, and insight, which is another layer on the raw data: they actually want us to tell them how to use it and guide their implementation.

The views in the above example illustrate not only the impact of new technologies and systems upon marketing research, but also the expectations of decision makers as to what marketing research should do to support them. The phenomenal growth in internally generated secondary data and the means to analyse, interpret and action these data have brought about much reflection and consternation within the marketing research industry (as discussed

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in Chapter 1). The nature, value and challenges of internally generated secondary data have been hotly debated over recent years but this is not a new phenomenon. To reflect upon the roots of such debates it is worth examining what internal secondary data are.

Internal secondary data

Internal secondary data Data held within an organisation for some purpose other than a research problem at hand.

Operational data Data generated about an organisation’s customers, through day-to-day transactions.

Chapter 4 described the nature, purpose and value of secondary data to researchers. A vital source of secondary data comes from within organisations that commission marketing research, namely internal secondary data. These data are generally seen as being drawn from operational data, i.e. data that represent the daily activities, transactions and enquiries of a business. Daily transactions may be held in different departments, such as sales, accounts or human resources, and stored in different manners. The use of operational data has presented opportunities to researchers for as long as businesses have been recording their daily transactions. Even in the days of transactions being recorded manually, it has been invaluable for researchers to track down different sources of data and analyse them. The value of such data at all stages of the marketing research process means that locating and analysing internal sources of secondary data should be the starting point in any research project. The main reasons are that they are invaluable in defining the nature of a marketing decision problem and in defining who should be questioned or observed, and the nature of questions and observations to be directed at these individuals. These reasons are fundamental to the quality, action orientation and perceived value of marketing research. In addition, as these data have already been collected, there are no additional data-collection costs, there should be fewer access problems (though individual managers may make access difficult for personal or political reasons) and the quality of the data should be easier to establish (in comparison with externally generated data). Most organisations have a wealth of in-house information, even if they are not marketing or customer focused, so some data may be readily available. For example, imagine a shoe manufacturer that has traditionally sold shoes to retailers, such as Grenson (www.grenson. com/uk/). It creates invoices for all its sales to these business accounts. Its accounts department handles this process and maintains the data that it generates. Yet, there exists much consumer behaviour data in these invoices. Examples of analysis include: • • • • • • • •

What products do customers buy? Which customers buy the most products? Which customers repeat purchases? Which customers are more active when there are special offers? Where are these customers located? Which customers are the most loyal? Which customers are the most profitable? Seasonal patterns of purchasing behaviour by product types and customer types.

Grenson has also developed e-business capabilities, with a website that enables it to sell its shoes directly to consumers. In such an instance Grenson would have the ability (perhaps for the first time if it has not previously invested in marketing research) to understand the above characteristics of the final consumers of its products, rather than characteristics of the retailer intermediaries. Beyond transactional data, there may also be data that relate to promotional activities such as spending on advertising, trade fairs, sponsorship deals or personal selling. It is not unusual for large organisations to have a multiplicity of different data sources, e.g. sales orders, customer relationship management, assets, stock, distribution, advertising, marketing and accounting. Each of these operational data systems may have its own databases but there is no guarantee that these systems and databases are linked.7 Thus the researcher may be faced with many discrete and/or integrated internal data sources from which characteristics of

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Customer database A database that details characteristics of customers and prospects, which can include names and addresses, geographic, demographic and buying-behaviour data.

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customers, their past behaviour and potential behaviour may be discerned. The norm for many companies is to integrate formally the data about their customers and invest in developing and maintaining a customer database. The customer database can be used to design and deliver marketing activities and strategies, and the response from these activities is fed back to improve and update it. Databases support techniques such as segmentation analysis, which at one time was developed from data gathered from relatively small samples collected at considerable expense. With a customer database, insights can be developed from larger samples obtained at almost no marginal cost as the data usually were gathered in the course of normal business operations.8 The increasing use of store or loyalty cards has seen a major growth in the generation of these kinds of data. Such an example of a customer database is illustrated in the following example.

Consumer Zoom: the French experience on loyalty card data9 More than 90% of French households hold at least one loyalty card from a hypermarket or supermarket brand name, and more than one in two participate in at least two programmes. Major retailers have information on several million clients, with a detail by product (European Article Number – EAN-13 bar codes are product identification numbers) and this for each till receipt. The development of store loyalty programmes has enabled researchers to follow and analyse consumer behaviour at the point of sale. After several years dedicated to client recruitment and optimisation of their programmes, FMCG retailers are now reviewing the use of the huge databases generated by loyalty programmes. This information is first used to analyse purchases of store loyalty card holders, then to describe behavioural characteristics of these customers. An additional method of analysis now exists, thanks to the size of the fast-moving consumer goods stores’ (FMCG) customer databases: the analysis of consumer behaviour on product categories and consumer reaction before marketing stimuli displayed by manufacturers and retailers. Marketing-Scan (www.marketingscan.fr) developed a Consumer Zoom approach through a partnership built with two French retailers, including the Auchan store (www.auchan.fr). One level of analysis performed by Consumer Zoom was the study of purchase habits by product category. Retailers as well as manufacturers are interested in this approach, as it is possible to find brand growth opportunities by analysing customers’ purchase habits. The Auchan Consumer Zoom tool is built from a representative sample of 600,000 store loyalty card holders.

Loyalty card At face value, a sales promotion device used by supermarkets, pharmacists, department stores, petrol stations and even whole shopping centres and towns to encourage repeat purchases. For the researcher, the loyalty card is a device that can link customer characteristics to actual product purchases.

The essence of the Auchan Consumer Zoom example is that the scanned data of products sold in Auchan stores are linked to known customers: the system links customer identification to product usage. Any promotional offers, competitive activity, new-product offerings, discounts or where to locate a new store, to name but a few marketing activities, can be analysed and related to classifications of customer. This example also illustrates one of the most prolific devices designed to capture customer behaviour data, i.e. the storecard or loyalty card. The loyalty card is the device that supermarkets, pharmacists, department stores, petrol stations and even whole shopping centres and towns have developed in order to link customer characteristics to actual product purchases. The loyalty card may be offered to customers as they make a purchase in a store. Basic customer data can be gathered as customers normally complete an application form, which may include their name and address, demographic details, household details, media usage

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and even some lifestyle characteristics. Once customers use their loyalty cards, the products they have purchased are scanned and a link can be made through the ‘swiped’ card to their characteristics, which can then be related to the scanned data of their product purchases. In return, the customers earn ‘points’ for their total spend and may earn additional points for buying particular products. From the researchers’ perspective, many benefits also accrue from the internally generated secondary data from a loyalty card and product scanning system. The following list summarises the benefits to the researcher: 1 Profiles of customers can be built up. The types of individual who are being attracted to a store, particular types of products and responses to different types of promotion can be monitored. The returns and contributions made by particular types of customer can be measured. Profiles of the ‘ideal’ customer type can be built up, and plans developed to attract potential customers based upon these profiles. 2 One big laboratory. Experimental methods will be described in Chapter 11, but, in essence, the monitoring of customers, markets and interrelated marketing mix activities allows for many causal inferences to be established. For example, what is the effect, and upon whom, of raising the price of Häagen-Dazs ice cream by 10%? What is the effect of placing a coupon code to give a discount on after-sun lotion, placed via a Facebook brand page? 3 Refining the marketing process. With a series of responses to planned marketing activities, statistical models of consumer response can be built with associated probabilities of a particular outcome. Likewise, models of the consumers over their lifetimes can be built. Again, statistical models can be built with associated probabilities of particular types of product being bought at different stages of a consumer’s life. 4 Developing a clear understanding of ‘gaps’ in the knowledge of consumers. The scanner and loyalty card electronically observe behaviour but do not encapsulate attitudinal data. The nature and levels of satisfaction, what is perceived as good-quality service, or what image is associated with a particular brand, are examples of attitudinal data. The use of the database helps to identify target populations to measure and the attitudinal data that need to be collected. In all, there can be a much greater clarity in the nature of primary marketing research that tackles attitudinal issues. 5 Linking behavioural and attitudinal data. If attitudinal data are elicited from consumers, the data gathered can be analysed in their own right. It is possible, however, to link the gathered data back to the behavioural data in the database. The term ‘fusing’ the data from different sources is used. The key to fusing lies in identifying individual participants so that one large dataset is built up. The notion of fusing together databases and survey data from different sources is at the heart of building a strong understanding of both the behaviour and motivation of consumers. The iterative knowledge gained from consumer interactions means that new targeted offerings can be formulated, and the nature of the customers’ response can be recorded. Researchers and decision makers can model and learn much about customers’ behaviour from transaction data. They should also be able to see the gaps in their knowledge of the current and potential customers. The awareness of these gaps in knowledge can be the foundation of well-designed and actionable marketing research. In the development of good research designs, the customer database can be seen as a vital resource to the researcher when conducting internal secondary data searches. The idea of accessing a customer database represents a clear opportunity for researchers, but such a resource may not be singular and can be integrated with many other databases and systems. There are a whole array of different means to capture electronically customer transaction behaviour and even potential customers through their search for information to buy services and products.

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It is beyond the scope of this chapter to describe and evaluate fully the array of technologies, e-business methodologies and touchpoints with consumers that are impacting contemporary business. Many of these systems and technologies can be integrated, and so pulling apart all these touchpoints with consumers represents a major task. We will, therefore, concentrate on four major subject areas where internally generated data can be integrated with marketing research to produce greater consumer and marketing insights. A summary of how these can be integrated with marketing research will then be presented to illustrate the power of measuring and understanding consumers in different and integrated manners. The main areas are geodemographic data analyses, customer relationship management (CRM) systems, big data and web analytics.

Geodemographic data analyses

Geodemographic information system (GIS) At a base level, a GIS is a business tool that matches geographic information with demographic information. This match allows subsequent data analyses to be presented on thematic maps.

Thematic maps Maps that solve marketing problems. They combine geography with demographic information and a company’s sales data or other proprietary information.

Insight gleaned from databases, as illustrated in the preceding section, can emerge from the linking of different data sources from operational data that relate to customers. The ability to create those links and to display analyses graphically has long been achieved with the use of a geodemographic information system (GIS). At a base level, a GIS is a business tool that matches geographic information with demographic information, allowing analyses to be presented on thematic maps. This base can be built upon with data from customer databases, databases from other sources and survey data. The combined data again can be presented on maps and in conventional statistical tables. Though the creation of geodemographic information systems comes from a variety of externally generated data sources, they have been instrumental in empowering decision makers to make sense of their internally generated secondary data – namely, customer databases. The earliest forms of GISs were developed in the early 1980s and were immediately a great success – not only in their ability to integrate a disparate array of data sources, but also their ability to display analyses in a very clear and engaging manner. The geographic dimension of where consumers live is vital as a base to the system. Growing up and living in different geographical locations can have an effect upon what consumers buy and the nature of their lifestyles. Look at the huge diversity of consumers around Europe! It is easy to see differences in consumers and their spending habits, between countries and regions within countries, between cities and towns and areas within a town, and even between different sides of a street. Differences can be seen between geographical locations that affect the lifestyle of residents, the array of products and services they buy, their ability to buy different types of products and services and their hopes, fears and aspirations. The founding premise of a GIS is that the type of property a consumer lives in says much about the consumer’s lifestyle and consumption patterns. For example, consumers living in small, onebedroom flats over shops in a city centre will tend to have very different lifestyles and consumption patterns from those living in large, detached, rural properties. Consumers in different property types have different propensities or probabilities of buying particular goods and services and of undertaking activities that make up their lifestyle. They also have different propensities to use and be exposed to different types of media. From a marketing decision-making perspective, geography can be pivotal in strategic thinking. Knowing where one’s consumers are located affects the means and costs of distribution. For example, should a new retail outlet be built and, if so, in which city and then in which part of that city? Which customers will have to pass our competitors in order to get to us? What features and facilities should the outlet have? The location of consumers also affects the means to communicate with them. Are consumers dispersed over a wide area or tightly clustered together? Do they read the same type of newspaper or magazine? Do they watch the same TV programmes or films at the cinema? Do they prefer to spend more time on Facebook or YouTube? The following example of the charity Sense Scotland shows how the organisation used geodemographic analyses to generate a greater depth of understanding their donors.

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Connecting to the ‘Captains of Industry’ – Sense Scotland Sense Scotland (www.sensescotland.org.uk) is a significant service-providing organisation that is engaged in policy development for children and adults with complex support needs because of deafblindness or sensory impairment, learning disability or physical disability. As part of an ongoing process of profiling and analysing its donor database, Sense Scotland commissioned CCR Data (www.ccr.co.uk) to find out about the types of donors who had previously been asked to convert from a home money box to a direct debit payment for donations. CCR analysed Sense Scotland’s donor database using Experian’s Mosaic Scotland consumer classification. This allowed CCR to assess Sense Scotland’s previous performance with individual donor segments and its performance related to Mosaic Scotland groups. For example, Mosaic Scotland Type A01 ‘Captains of Industry’ made up 6.67% of the donors who had been asked to convert. This type of consumer, the wealthiest in Scotland, made up only 1.92% of the population, which revealed that the original method of targeting donors had worked well. Further analysis showed that each person who had converted from the ‘Captains of Industry’ group had given 22% more than the average donor in regular gifts. Using Sense Scotland’s donor database and Mosaic data, CCR was able to refine further the process of analysing donor profiles and behaviour prediction. Following this analysis, Sense Scotland made the decision to develop a completely new form of profiling the donors on its database.

Geodemographic classification This groups consumers together based on the types of neighbourhood in which they live. If sets of neighbourhoods are similar across a wide range of demographic measures, they may also offer similar potential across most products, brands, services and media.

One of the major factors that have seen decision makers engage with geodemographics are the maps and other graphical devices used to present data analyses. Such data analyses can be used to portray a huge variety of consumer characteristics and essential differences between target consumers. A map can identify all properties in a country (or even countries), all roads, shopping centres and major facilities in towns and cities. Data related to where consumers live and shop can be easily portrayed on these maps. The data typically originate from a number of internal and external sources and have the common feature of being able to relate to a specific postcode or zip code. Examples of such a system are those produced by CACI (www.caci.co.uk) and Experian Mosaic (www.experian.co.uk/business-strategies). The CACI system has been well established in the UK for many years, giving detailed analyses of specific locations and specific industry types, such as telecommunications, retailing and finance. Experian Mosaic is also well established in the UK but has also developed systems specifically tailored for a number of countries throughout the world. The sources and details of data available in each of the above countries differ, as does the legislation that determines what can be stored and analysed on databases. Typically for each country, statistics can be gathered and used to develop individual GISs based upon census data, postal address files, electoral registers, consumer credit data, directories of company directors, mail-order purchase records, car registrations and data on access to retail outlets. From the data collected, the purpose is to classify consumers on a geodemographic basis. Experian defines a geodemographic classification as follows: Geodemographic classification groups consumers together based on the types of neighbourhood in which they live. If a set of neighbourhoods are similar across a wide range of demographic measures, they will also offer similar potential across most products, brands, services and media. With the variables chosen for a particular country, i.e. the types of data that are available to build a GIS, cluster analyses are performed (Chapter 25 details the nature and purpose of cluster analysis). These analyses help to create consumer classifications, based upon the types of property the consumers live in and the propensity of consumers to have certain lifestyles

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and behave in particular manners. The analyses ensure that each of the descriptions used is reasonably homogeneous in terms of demographic measurements and consumer behaviour. As well as being able to discriminate and describe distinctive groups of consumers, the analyses produce ‘pictures’ of consumers that are meaningful to marketing decision makers. Experian has also produced ‘Mosaic Global’ (www.experian.co.uk/business-strategies/ mosaic-global) as a consistent segmentation system that covers over 380 million of the world’s households. It is based on the proposition that the world’s cities share common patterns of residential segregation. Each country has its ghettos of ‘Metropolitan Strugglers’, suburbs of ‘Career and Family’, and communities of ‘Sophisticated Singles’. In terms of their values and lifestyles, each type of neighbourhood can display strong similarities in whichever country it is found. Using local data from 25 countries and clustering methods, Experian has identified 10 types of residential neighbourhood, each with a distinctive set of values, motivations and consumer preferences, which can be found in each of the countries. Mosaic Global uses the data from the national Mosaic classification systems for the following countries: Australia, Austria, Belgium, Canada, Czech Republic, Denmark, Finland, France, Germany, Greece, Hong Kong, Israel, Ireland, Italy, Japan, The Netherlands, New Zealand, Norway, Romania, Singapore, Spain, Sweden, Switzerland, the UK and the USA. The resulting analyses have produced a classification of 10 main consumer types. The example below describes characteristics of the Mosaic Global group labelled as ‘Sophisticated Singles’. With a GIS, it is possible to pinpoint where the ‘Sophisticated Singles’ are in any of the countries analysed, whether they are clustered in particular regions or cities, or whether they are dispersed. If one were to dig deeper within each country, there would be clear differences in the proportions of these groups between cities and regions. From these classifications and the data that can be added from other internal databases, models of behaviour can be developed for consumers in markets across the world. The profile of customers that a company has can be compared with national, regional or city profiles. Data that are captured on customer databases can be mapped out. For example, ING Bank NV can map out which customers have responded to an offer to take out a personal loan at a discounted rate, as well as building up a profile of those who respond. In addition to customer behaviour from an organisation’s customer database being added to the GIS, survey data can also be added. The key that would link the survey to the customer database may be either a named customer or a postcode. The following cases illustrate how geodemographic data from both Experian Mosaic and CACI have been integrated with marketing research techniques. In the first case study, Experian’s Mosaic was used to create more valid and reliable sampling frames for international surveys and more detailed analyses of target markets. In the second study, CACI’s GIS was used after stages of qualitative interviewing and telephone interviewing were conducted.

Real research

‘Sophisticated Singles’ ‘Sophisticated Singles’ contains young people, mostly single and well educated, who positively enjoy the variety and stimulation afforded by life in large cities. Typically international in their outlook and with a rich network of personal contacts, they are quick to explore and adopt new social and political attitudes and are important agents of innovation, in terms of both lifestyles and the adoption of consumer products. Most are at the stage of their lives when the development of ‘human’ capital, i.e. skills, contacts and knowledge, continues to take precedence over the maximisation of their incomes or indeed the accumulation of financial assets. Much of their income is spent on ‘experiences’, such as entertainment, eating out, travel, books and magazines, rather than on equipment. They exhibit a variety of household arrangements and typically marry and have children later in their lives. Such people gravitate towards the smarter downtown areas of major cities, where they spend short periods of time living in small, rented apartments.

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Research Now and Mosaic Research Now (www.researchnow.com) specialise in managing access panels across the globe and international online fieldwork for both business-toconsumer and business-to-business relationships. It has combined the details of its 2 million panel members with Experian’s multi-country analysis (www. experian.co.uk/business-strategies). Mosaic classifies 1 billion consumers across 25 countries, covering Europe, the Americas and Asia-Pacific. The partnership enables international researchers to improve the design of their surveys through detailed sample definitions and selection, being able to monitor and manage sample quotas during fieldwork. With more detailed profiles of consumers available through this link, individual clients can have specific market-segment specifications applied to their study, which can be applied to survey findings in data analyses and tables.

Real research

Segmentation of the baby milk market10 The formula milk market has an unusual feature in that the vast majority of women will have given negligible thought to the product prior to becoming pregnant, and, because of the intent and encouragement to breastfeed, relatively little even during their pregnancy. When the time comes to buy the product, mothers are confronted with a bewildering choice of brands, milk types, pack and product formats and sizes. Somehow, they have to make a decision on what is best for their baby and for themselves. SMA (www. smanutrition.co.uk) wanted to ensure that they were providing products, formats and communications that were in tune with mothers’ complex needs. SMA established that a segmentation study was needed and thus established a cross-functional team of marketing, marketing research and sales personnel from SMA, researchers from Leapfrog (www. leapfrogresearch.co.uk) and management consultants. The first phase was to conduct qualitative research to deepen the understanding of mothers and their attitudes and behaviour, particularly in respect of feeding patterns and choices. Leapfrog ran 38 paired in-depth interviews across the UK and Ireland that included first-time and subsequent mothers. The qualitative research produced a wealth of data on mothers, their influences and decision processes and also theories on market segmentation, which needed quantitative validation and refinement. The second phase was to conduct telephone interviews of first-time pregnant women, first-time mothers and subsequent mothers. A key factor in the choice of telephone interviewing was the need for a very wide geographical dispersion so as to enable subsequent geodemographic modelling. The sampling frame used to contact participants was built from four sources: a commercial mailing list, the customer base of a leading retailer, callers to the SMA careline and the SMA Mums’ Network. The telephone interviews covered full details of feeding behaviour and the influences on every decision made (e.g. the switch from a first milk to a milk

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for a hungrier bottle-fed baby). In addition there was extensive attitudinal information, which formed the basis of developing segmentation. The development of a national set of segments was the first step towards realising the individual needs of the customer base at a level of detail never previously achieved. The starting point was to identify each segment down to postcode-sector level. CACI (www.caci.co.uk) was commissioned to undertake this exercise, using its geodemographic tool ACORN. The task was achieved by matching key attributes in CACI lifestyle segments to those identified in the SMA customer segmentation exercise, resulting in SMA being able to identify the type of mother residing at each postcode-sector level. The next step was to share the segmentation analyses and descriptions with the entire SMA division at a specially organised conference. A video was specifically created in order to bring each of the defined segments to life. The process helped to validate the accuracy of the segments, based upon the salesperson’s knowledge of different localities. The customer segmentation work provided SMA with strong evidence to help design its customer relationship (CRM) programme. The whole project also helped management consultants design a model for SMA, allowing the business to understand the core dynamics of the feeding experience by key stages in babies’ development. This was the first time that SMA’s market share data was based upon the number of customers (penetration figures) using infant formula, rather than volume and value sales. SMA experienced record levels of women joining their CRM programme and has seen more first-time bottle-feeding mothers than ever using the SMA brand, as measured by TNS (www.tnsglobal.com).

In this example, the organisation did not previously have a clear means to measure and understand its existing or potential customers. There was a distinct role and integration of qualitative and quantitative research that helped it to characterise its target markets. Geodemographic analyses helped the organisation to refine its profiles of target markets and get a sense of the potential markets and, with its research data, to understand what would be needed to turn prospective customers into actual customers. Having used geodemographics in this study, SMA could subsequently map out and form graphical representations of customers’ behaviour, their attitudes and their levels of satisfaction; there is much that could be achieved in representing characteristics of how SMA customers relate to its brand. Of note also in this example is how the data and analyses of customers were used as a foundation for the CRM programme. We continue by examining the nature and impact of (CRM) tools that have emerged from the database marketing and geodemographics industries. Remember that the customer data generated in the following evaluation of CRM systems can be mapped out using GISs.

Customer relationship management Customer relationship management (CRM) The processes involved in the identification of profitable customers and/ or customer groups and the cultivation of relationships with these customers. The aim of such processes is to build customer loyalty, raise retention rates and therefore increase profitability.

The foundation of customer relationship management (CRM) is to analyse and target the ‘right people’ with the ‘right offers’, aiming to understand profitability trends at the individual customer level, to know who to target, why and with what.11 Marketing decision makers continue to realise the benefits of analysing customer data held within operational databases within their organisations. This realisation and the technological developments in collecting, analysing and presenting insight in customer-generated data have developed into the concept and practice of CRM. CRM definitions can vary, but in essence the concept can be seen as: The processes involved in the identification of profitable customers and/or customer groups and the cultivation of relationships with these customers. The aim of such processes is to build customer loyalty, raise retention rates and therefore increase profitability.12

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The growth of CRM has emerged from the use and subsequent integration of various direct marketing channels (direct mail, telemarketing) and the rise of e-business, e-communication and the increasing use of the internet as a conduit for customer care and sales.13 In the same manner that consumer insights generated from social media sources have impacted upon the practice of traditional marketing research, CRM practitioners are integrating social media data with internally generated customer data.14 The main challenge of implementing CRM is to integrate customer data from the post, telephone, personal visits, e-business and social media into a central database, so that it holds all transactions and contacts with each customer (and indeed browsing, potential customers) allied with the ability to update the data constantly and to access them immediately, whenever necessary.15 The principles of CRM are straightforward: organisations gather accurate data about their customers and prospects from all the sources that contact or engage with them. They analyse and sometimes model these data to generate insight into the behaviour of different customers. They can then formulate marketing strategies and offerings that differentiate between customer segments, sometimes differentiating down to the individual customer level. Greater resources can be focused on higher-value or higher-prospect customers. Every opportunity is used to amass additional data about each customer to personalise offerings and build a closer relationship16, and indeed to build stronger models of customer behaviour. The following example illustrates how the fashion retailer Debenhams has used customer data, generated through its storecard and CRM system, to help model and predict customer behaviour.

Real research

Customer analytics are in style at Debenhams17 As a key player in the UK fashion retail market, Debenhams (www.debenhams.com) has to create the best possible customer experience and needs to understand what its customers want from its 139 stores. Understanding customer shopping habits can be seen as crucial for any retailer, and identifying trends early can be critical to success. Debenham’s team of analysts was responsible for researching and evaluating all aspects of the customer relationships, including analysing customer buying habits as well as marketing campaigns and activity around new store openings. Debenhams used SPSS’s Predictive Analytics (www-01.ibm.com/software/analytics/spss) to support three areas of the analytics team’s work: (1) supporting planning and decision making within buying and merchandising; (2) supporting marketing and CRM activity; and (3) analysing potential new stores. Using the software, the analytics team could look at which special offers were generating the most sales, as well as identify ‘cross-sell’ opportunities; for example, if a customer bought a new shirt, which tie was the customer most likely to buy to go with it? The team also applied analytics to understand why some lines were selling better than others. The SPSS tool has also played a crucial role in the life cycle of new store openings, from strategy to actual openings. This included preparing the initial business case and evaluating the optimum mix of product lines to carry, through to evaluating marketing campaigns for the new store.

The use of the term ‘CRM’ has grown rapidly over past years and now encompasses many functions associated with superior customer service and management, relationship building and electronic shopping. CRM often includes sales force and front office applications that assist in customer interaction, the addition of customer and product information, and sometimes have the ability to integrate with other operational systems, including finance, inventory and ERP (Enterprise Resource Planning) to develop a full e-business or Webbased system.18 There is no doubting the value and impact of CRM systems in generating

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customer insight, but for researchers the means by which data are generated on individual customers can generate conflicts with the fundamentals of their code of practice. The ESOMAR International Code on Market and Social Research states in its ‘Basic Principles’:19 Market research shall be clearly distinguished and separated from non-research activities including any commercial activity directed at individual participants (e.g. advertising, sales promotion, direct marketing, direct selling etc.). Participant anonymity has been a hallmark of bone fide marketing research for as long as it has been professionally practised. However, ESOMAR has recognised that one of the biggest threats to the industry lies in the alternative data sources that decision makers use, which includes customer insight generated from CRM data: As CRM databases improve, a growing amount of data collection needs to be nonanonymous and linked to customer databases – at the moment marketing research is not well placed to contribute to that process.20 These concerns over the use of research data for wider purposes, together with the ethical issues around the use of anonymisation, are covered in more detail in Chapter 29. However, both the opportunities and the challenges generated by the collection and use of CRM data can be seen as a microcosm of those presented by the emergence of big data, which is discussed next.

Big data Big data is a term that has reached widespread use within business as well as among the media, academics and politicians. As might be expected from such a broad range of groups, the meaning of the term ‘big data’ varies depending on the needs of the group who are discussing it. In general terms, big data describes a range of technological and commercial trends enabling the storage and analysis of huge amounts of customer data.21 Much of the commercial promise of big data is in the ability to generate valuable insights from collecting new types and volumes of data in ways that were not previously economically viable.

Real research

What is ‘big data’ anyway? Although the term big data has been widely discussed, many of the definitions can be vague and driven by hype rather than reality. One of the firms closely associated with the push behind big data is IBM, which has attempted to provide some clarity with the following definition:22 Every day, we create 2.5 quintillion bytes of data – so much that 90% of the data in the world today has been created in the last two years alone. This data comes from every where: sensors used to gather climate information, posts to social media sites, digital pictures and videos, purchase transaction records, and cell phone GPS signals to name a few. This data is big data.

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One of the more confusing aspects of big data is that it is not solely, or even mainly, about the ‘bigness’ or volume of data. Data volume is one of four dimensions of big data that have been identified by IBM:23 1 Volume. This relates to the ‘bigness’ in big data – in other words, the amount of data that are being collected. As the definition of big data given by IBM illustrates, the increase in data being collected is nearly exponential. However, the volume is not simply about data being created but also the amount of data that are being stored. 2 Velocity. Beyond volume of data, velocity is a lesser aspect of the technological side of big data that is less obvious. Data are collected in real time when they come from sensors on cars, on mobile devices or from websites. They can also be accessed and analysed in real time. One practical example of this can be seen when searching for a name on Facebook: despite more than a billion users of the service, data can be returned almost instantly for a a search. 3 Variety. Until as recently as the mid-2000s, most of the data collected through the internet were in text form. This had a number of advantages in that they were relatively easy to store and access. However, data now exist in a wide variety of formats and the majority of data that are stored are now in text or video formats. 4 Veracity. While originally there were only three dimensions, a fourth dimensions was added by IBM – veracity. This refers to the non-technical issues that surround big data. Although these factors have often frustrated technologists, they will be familiar to marketing researchers as they reflect many of the existing challenges with carrying out research. These include the extent to which business leaders trust the information they use to make decisions, as well as issues around data quality when working with big data. On top of these technical dimensions lies a number of economic factors, in that technology has not only enabled the expansion of data collection but dramatically reduced the costs of doing so. As the marginal cost of data collection reduces, often close to zero, organisations collect almost any amount of data without necessarily regarding the cost. This creates a number of opportunities in terms of marketing research but also a number of ethical issues (which are discussed in detail in Chapter 29).

Problems with big data •

•

Data quality. As the saying goes: rubbish in rubbish out. Just because large volumes of data are being collected doesn’t mean that the data will be useful. For example, if geo location data from a mobile device are collected every 30 seconds as opposed to once a day, nearly 3,000 times more data are being collected. However, there are likely to be relatively few commercial uses where it is necessary to know a location every 30 seconds (not to mention a number of ethical issues from collecting such data). Just because more data are being collected it doesn’t mean that more types of data are being collected. As with traditional market research techniques, the most sought after customer insights can remain the most difficult to source. Skills in analysing data. While collecting data might be the (comparatively) easy part, successful analysis of very large secondary data sets requires a different skillset from those typically possessed by marketing researchers. The required skills are technical and are built around the techniques needed to deal with large volumes of unstructured data. The shortage of individuals with such ‘data science’ skills has been identified as a major barrier to achieving the potential of big data.24 Organisations and culture. Just because there are new technologies and increasing sources of data does not mean that the age-old issues around data sharing within firms have been solved. Much of the value around big data is centered on the combination and

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analysis of multiple data sets. However, to achieve this requires a high level of cooperation within organisations. One of the criticisms of big data is that the perception that collecting data has value led to the hoarding of data within existing organisational silos, without recognising that value can only be found through sharing the data across organisations.

Web analytics Web analytics The process of collection, measurement and analysis of user activity on a website to understand and help achieve the intended objective of that website.

The process of measuring and understanding the interaction with, and impact of, a website can be broadly termed as web analytics. This refers to the collection, measurement and analysis of user activity on a website to better understand and help achieve the intended objectives of that website. As well as focusing upon their own customers, organisations may include activities such as competitor web analysis, which is the practice of assessing and analysing the strengths and weaknesses of competing websites. With internally generated secondary data, web analytics can enable researchers and decision makers to build upon existing customer data. Handled correctly, researchers can undertake behavioural analyses of customers that can enhance known demographic, geographic and other behavioural characteristics. As well as developing profiles of customers, analyses can be performed to gauge how existing and potential customers respond to different stimuli (advertising, marketing and customer service). Web analytics can make it possible to track every page viewed, every element ‘moused over’, every menu dropped down, every key pressed, every video watched. Tracking techniques can collect the most complete picture of what a visitor does on a site, even capturing data entered into a form that the visitor chooses not to submit.25 In the tracking and analysis of web interactions, knowledge of customers can be created. Figure 5.1 summarises this process, starting from individual website clicks being captured, through to an understanding of how visitors (which includes potential customers who turn into customers – or not) are browsing a website. Once actual shopping takes place via the website, further customer details and their behaviour can be recorded and modelled. This figure highlights the important distinction between ‘browsing’ and ‘shopping’ behaviour and what insight can be developed as a potential customer moves to become an actual customer.

Figure 5.1 Data

Building consumer profiles from website events

Website event

Click

Website visit

Visit Browsing

Repeat visit

Visitor

Person identified

Customer Shopping

Knowledge

Person profiled

High-value customer

The value of measuring and understanding browsing and actual purchasing behaviour is illustrated in the following example. Holiday and travel industries have seen major competitive changes and pressures through consumers being able to organise and buy products and services directly from websites. This example shows how Thomson Holidays has realised the benefits of these changes through capturing customer behaviour from its website.

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Thomson Holidays: behavioural conversion programme26 The holiday industry is hugely competitive, with tough challenges facing major operators in an industry where customer loyalty is hard won. Using enquirer tracking, email and web analytics, Thomson Holidays (www.tuitravelplc.com) developed its Engagement Warehouse, which captured the on- and offline pre-purchase behaviour of millions of customers and prospects. It combined historical transactions, live web and email click, search and select behaviour, retail store visits and enquirer touchpoints to help it understand how customers and prospects acted before making a purchase. This was a strategic investment in a technical capability that allowed Thomson to know when its prospects were actively thinking about and planning holidays, what products they were considering and when they wanted to go. Thomson could identify individuals who were currently in the market, seek out those who want to go away at different times, to different places, with or without children, to 5-star hotels or budget products. It was a sophisticated data structure, with proprietary software, triggered web services, email and web content integration, delivering strategic and competitive advantage through eCRM services in a highly commoditised and pricesensitive market. The Engagement Warehouse extended Thomsons’s understanding of customers’ pre-purchase journey and was at the heart of a well-defined data strategy engaging all Thomson contacts, historical transactions, email engagement and web analytics. It revealed previously untapped analytical trends and tactical and strategic opportunities.

A large range of different web analytics products exist, although the dominant player in the market is Google Analytics (www.google.com/analytics), which provides both paid and free versions of its software. In addition to its pricepoint – free is an attractive proposition for any business – Google Analytics also integrates demographic information gathered from Google’s own databases including, for example, data gathered from users of Android smartphones. This provides data on age profile, gender, interests and current purchase intentions for website visitors, among other thing. This information is highly valuable and provides access to data that would not normally be available through secondary data analysis. It also provides a reminder of why provision of secondary data by Google is seen as a threat to the business of many established reseach firms. As might be expected, free software comes with a catch. If Google Analytics is used as an analytics service, then the data on visitors are held by Google and only anonymised data will be made available to website owners, and researchers. In other words, individual visitors cannot be tracked. This is often less of a practical issue than might be thought in terms of addressing research questions, and can help to ensure compliance with the need to maintain anonymised data. However, if websites have a need to track individual visitors (for example, if they are collecting purchase data via an ecommerce site), then paid services may be more appropriate. Lower-cost examples include Crazy Egg (www.crazyegg.com) or Kissmetrics (www.kissmetrics.com). Beyond this are full enterprise-level implementation services, such as Adobe Analytics (www.adobe.com/marketing-cloud/web-analytics.html), which allow customisation of analytics options while maintaining control of the underlying data – at a cost. In a full-enterprise system, the integration of web-user data is included with other customer data sources. This is illustrated in Figure 5.2, where potential sources of customer touchpoints with an organisation are brought together to create enhanced customer profiles and models of their behaviour. This figure illustrates how a ‘visitor’ can connect with an organisation in a range of ways.

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Certain customers may choose to connect to and shop with an organisation in one way; others may use a range of methods to browse, plan, experience and finally make a purchase. Each of these connections may be deemed a visit. The use of a visitor profile database is illustrated in the following example of Europe’s largest retailer, Tesco. The example shows how Tesco has used data from the loyalty card, plus web analytics data, to build customer profiles and targeted offerings. It also shows how Tesco builds and integrates marketing research.

Figure 5.2 Visitor profile database

Demographic data Mail order Offline shopping (loyalty card data)

Call centre activity Visitor profile database

Transaction data

Campaign data (email, search engine, etc.)

Online behaviour (browsing and shopping) Geographic data

Real research

Tesco: integrating research and analytics27 The UK supermarket giant Tesco (www.tesco.com) first introduced its Clubcard in 1995, and now has an estimated 16 million members equating to around three-quarters of the total number of people who shop at Tesco in the UK each week. Every purchase made in its stores delivers 45 separate pieces of information to the company, based around factors ranging from price to whether a customer has opted for an own-label or branded product, and a ‘basic’ or more unusual item. Tesco customers are sorted into a variety of different demographic profiles, such as whether they have children or pets, or whether they appear to make complex or simple meals. Dunnhumby (www.dunnhumby.com), the marketing firm that pioneered the Clubcard platform, and which is now owned by Tesco, assesses 100 transactions a second, or around 6 million shopping trips a day. Tesco also has a major online shopping facility, allowing it to identify and profile consumers who shop online and/or in-store. The information that is generated through its databases helps Tesco decide which goods to stock, where promotional activity could boost sales and even when it could expand its store-brand range. Tesco has integrated its market research and analytics capability. In order to understand ‘why’ consumers are behaving in the way it has identified, Tesco can target specific customers, pre-populate the survey with known customer data, tailor questions that are specific to the behaviour of that customer and offer a reward that is meaningful to the customer. Tesco estimates that 16% of its margin is attributable to the knowledge it gets from its customer database. That makes the database a $3.2 billion asset. Alongside offering Tesco an insight into the behaviour of its customers, major FMCG firms, such as Coca-Cola, Nestlé and Unilever, pay to access these data.

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Web analytics can reveal what consumers do online and how they respond to different pieces of digital communications. What consumers do online and what it physically means to be ‘online’ are changing dramatically. The growth of social media interactions is adding richness and complexity to web analytics, providing decision makers with not only masses of behavioural data on consumers, but also some attitudinal and emotional data. The wealth of data can carry more weight with decision makers, as the capturing of what consumers actually do could be considered more reliable than what consumers say they think, feel or will do in response to survey questions. In a world where customer touchpoints and brand engagement are being constantly captured, the marketing research industry must take full advantage of these digital tools rather than seeing them as a distinct and alien form of encapsulating consumer behaviour. If seen as a source of internal secondary data upon which much richer consumer insights can be built, web analytics provides additional and immense opportunities for the researcher. As in the Tesco example above, neither web analytics nor loyalty card data can totally reveal the underlying reasons for consumer behaviour. A richness of psychological reasoning and emotive connections to products, brands and experiences may be missing. With the established skills to provide valid measurements of populations, researchers can provide data sets that bridge others and put them in context, both in place and in time.28 The key to gaining rich insights into consumers, the drivers of their behaviour and thus the distinctive role and power of the researcher, comes from examining how different types of data may be linked and integrated. Examples of data integration have been used throughout the chapter; the following section presents a simple framework to describe and evaluate the distinctive means to encapsulate consumers.

Linking different types of data The examples in the sections above illustrate how different types of data can be linked to form richer and more powerful analyses of existing and potential customer characteristics. The following study takes these examples further by illustrating how Nestlé has made organisational changes that have delivered a stronger understanding of the nature, dynamics and influences upon its customers.

Real research

Boosting consumer excellence at Nestlé29 When Denyse Drummond-Dunn joined Nestlé in 2004, the company’s sources of consumer information were fragmented. She set out to bring together three departments where consumer information was available: consumer services, consumer insights and consumer relationship management. This integration of the three departments came after a major change in the way Nestlé developed consumer insights. The company built consumer insights on four different sources of information. A first source was market data, such as sales or media data. Second, it used information derived from consumer ‘Safaris’, e.g. during consumer events organised by Nestlé or during ‘consumer experience sessions’. A third source was information developed through marketing research, both quantitative and qualitative. The fourth source consisted of data about the wider environment the company operates in, such as socio-economic trends or competitive activity data. ‘Integrating information from different sources is not new’, Denyse pointed out: What is unique at Nestlé is that we not only integrate information from different sources, but also ensure that the ensuing consumer insights are actually applied when we take decisions. This is done in all business units and countries we operate in.

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These examples illustrate what may be seen as one of the primary functions of supporting marketing decision makers, i.e. helping them to build a clear vision of the nature and dynamics of their target markets. Traditionally this would be seen as performing segmentation analyses and using these analyses to define and select target markets. It is not intended to work through the theory, practice or implementation of segmentation or target marketing. However, it is worth examining how different data sources can be linked and integrated to make segmentation and targeting work more effectively. Figure 5.3 sets out five basic methods of segmenting markets. Individually, each of these methods delivers different levels of insight to decision makers. They also demand that different types of data be captured, with differing challenges in that capturing process. The figure is somewhat deceiving in that it may imply that the process of building stronger profiles of consumers is a linear process and that once one level is complete, one moves on to the next. The reality is that consumers may be constantly changing, and the building up of profiles of consumers is an iterative process and may never be complete. The examples in this chapter reveal that consumer data can be constantly updated to represent who the consumers are, where they are located, what they ‘do’ and why they behave in that manner (and indeed could behave).

Figure 5.3 Methods of segmenting markets

Segmentation methods

Demographic

Geographic

Behavioural

Psychographic

Psychological

e.g. census data

e.g. Post Office data

e.g. web analytics and loyalty cards

e.g. loyalty cards and surveys

e.g. surveys

Increases in difficulty in measuring Clarity of ‘picture’ of consumers

Figure 5.3 gives examples of where data may be obtained from, to help build up profiles of customers and markets. In the example of ‘psychographics’ or lifestyle measurements, data may be generated from CRM databases, web analytics or surveys. In the case of CRM data and web analytics, the purchasing or even browsing of particular types of products can indicate characteristics of a lifestyle. In a more direct manner, questions in a survey or qualitative study can help to build a profile of lifestyle behaviour. In its own right, ‘lifestyle’ can be a valid means of segmenting a market, perhaps positioning products and services to consumers who aspire to a particular lifestyle. However, being able to combine demographic measurements, broader behavioural characteristics and a knowledge of where these consumers live helps to build a ‘picture’ of consumers that facilitates strong marketing decisionmaking support. Figure 5.3 indicates that as one moves from the demographic through to psychological characteristics, the measurement and capturing process can become more difficult. Putting aside the differences in techniques to capture ‘demography’, ‘behaviour’ or ‘psychology’, what is being captured becomes more difficult as one moves towards psychological variables. If one considers psychological variables that are vital to marketing that could be captured, examples such as satisfaction, loyalty, trust and quality are not as easy to capture as questions such as gender, age or where one lives. Chapter 12 will explore the concept of measurement in more depth, but at this stage consider what ‘satisfaction’ actually means, and then the problems of measuring that concept in a valid and consistent manner.

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Conversely, as the measurements become more difficult to conduct, they add more to the ‘picture’ of consumer and market profiles. To say that a market is primarily female, aged between 25 and 40 and lives in a detached property with a mortgage, starts to build a very basic ‘picture’ of target consumers. To add details of their media behaviour, the array of products and services they buy, characteristics of their lifestyle and even something of their dreams and aspirations in life can help to build up a rich and, for decision makers, a much more powerful ‘picture’ of target consumers. Examining the variety of data sources that can be used in an interrelated manner to build market profiles, it is easy to see distinct contributions from externally generated secondary data founded in GISs, transactional scanned data, loyalty card data, customer data in CRM systems, web analytics data, the use of traditional survey work and, indeed, other forms of quantitative and qualitative marketing research. The challenges in integrating these sources together can be summarised as: 1 Data challenges. To source, gather, validate, store, integrate, feed, model, analyse and interpret internally and externally generated quantitative and qualitative data. 2 Information systems challenges. To manage this array of data and develop and support emergent marketing knowledge in an organisation. 3 Marketing challenges. To keep abreast of the nature and dynamism of what should be an organisation’s target markets and performance in those markets. There is a clear interdependence among the different data sources and, as in the Nestlé example, with the will and means to integrate these sources, much more powerful consumer insights can be generated. The main approaches to generating consumer insight can be summarised, as in Figure 5.4. Though each of the four segments is presented as a distinct approach, and there are organisations that deliver these distinct specialisations, there is much overlap in how they work.

Figure 5.4 Approaches to gaining consumer insight

• Primary data collection through exploratory and conclusive means • Secondary data collection – internal and externally generated

Marketing research

Social • Can impact exclusively media on the practice and aims research of the other quadrants • Passive – observation • Active – directed engagement

Customer analytics

Business intelligence

• CRM systems • Web analytics • Geodemographic information systems • Transactional and browsing behaviour

• Internal financial and operational analyses • Competitior intelligence

This overlap is especially prevalent in the development and use of social media research (as discussed in detail in Chapter 17). Experts in CRM, web analytics and business intelligence, as well as marketing research, see the development of their discipline tightly interwoven with developments in social media research. This social media research has the potential to add many psychological characteristics of consumers, and as such has much to add to the other three approaches laid out in Figure 5.4. The explosion of data generated through social

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media and internet developments could well lead to far more integration between these approaches. This explosion and its impact are described in the following example, from ‘Using math marketing to increase your return on investment’ by Dimitri Maex (President of OgilvyOne New York, www.ogilvy.com).

Real research

Moving beyond the traditional single customer view30 Research data is the raw material for marketing, and the volumes gathered every day are staggering. Imagine for a moment that you had a database that held every word ever spoken by a human being, every utterance from the dawn of language on to the babble you hear around you right now. That’s a damn big database, right? You would need twenty databases of that size to hold the data that will exist by the end of next year. And the amount of data we spool out skyrockets every year! Not all of this data can be used by companies to improve their marketing efforts. After all, much of it is junk, but quite a bit of it can be helpful. Companies that adapt to the new scales of available data will thrive. Adapting organisations will adopt a single enterprise view of their business, not to replace the traditional single customer view but to augment it. This will allow them to access huge volumes of data, producing intricate analytics and targeted messaging that has both mass economies of scale and single-customer precision. Companies that adapt to the new scales of available data will thrive. Those that do not, well, no one said that evolution was kind.

This view of the impact of continuing digitisation of everyday life means that ever more individual-level data about consumer behaviour will be available for marketers to respond to.31 Marketing research, like any of the other approaches in Figure 5.4, has to recognise that it contributes part of a wider understanding required to formulate effective and successful business and marketing strategies. Relying on marketing research as a sole data source, or arguing that it is the most valid data source, could lead to a very one-dimensional view of consumers and the worlds they live in. Researchers need to recognise that marketing research has a distinctive role to play in a single-enterprise view of a business, adding value and distinction through being able to: 1 Focus upon existing and potential customers. 2 Use quantitative and qualitative approaches to tap into a rich array of consumer attitudes, emotions and aspirations. 3 Tap into a rich array of sensory and experiential characteristics of consumers. 4 Draw on a well-established and robust theoretical base in measuring and understanding consumers. 5 Draw on a well-established and robust theoretical base in being ‘representative’ and generalising populations. 6 Demonstrate social responsibility through a long-established, proactive and open code of conduct. ‘Old-style’ researchers, who may conduct studies to meet specific objectives and just deliver the results of the research, are becoming rare. Even if researchers were to see the nature and scope of their work in this narrow sense, they would be designing and delivering relatively weak research by not tapping into the array of internally generated secondary data

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that are at their disposal. In order to utilise internal secondary data, researchers need to equip themselves with more information-gathering skills and techniques than they have been traditionally trained to do.32 In order to thrive, researchers need to become ‘data curators’ by embracing and integrating new information sources. We must ensure that we are the ‘aggregators’ not just the aggregated.33

Real research

Diageo uses Google Analytics to empower its global brand managers Diageo is a leading global producer of alcoholic beverages, including some of the world’s best-known brands such as Guinness, Johnnie Walker, Smirnoff and Baileys and with annual revenues of €14,500 million. For a company of Diageo’s size, the logistics of delivering accurate analytics across hundreds of websites in over 20 countries was a daunting task. Marketing and brand managers required instant access to their website’s analytics reports in their native language. Though Google hosts and manages the server and hardware infrastructure for the entire Google Analytics platform, Diageo worked with a specialist agency to deploy Google Analytics across its global brands and to train its marketing teams. ConversionWorks (www.conversionworks.co.uk), a Google Analytics certified partner, worked with each brand’s web design agency. ConversionWorks quickly found that Diageo’s needs were very different from those of smaller organisations that have marketing teams centralised in one location. With potentially thousands of marketing executives spread around the globe, their challenge was to bring the data to the brand managers and not have them chasing after them. Using the Google Application Programming Interface, Diageo was able to show the latest reports and data directly on their intranet dashboards. Data were automatically extracted from each Google Analytics account and shown each time executives logged into the intranet.

Real research

Mobile surveys at TOMORROW FOCUS Media34 TOMORROW FOCUS Media (www.tomorrow-focus.de) is one of Germany’s leading internet marketing providers. Its portfolio includes FOCUS online and HOLIDAYCHECK, as well as partner portals CHIP Online, FAZ.net and FREUNDIN.de. It knew that 350,000 people had downloaded its iPhone app and were keeping abreast of the news (350,000 downloads). However, it did not have any hard facts about the users of its app, e.g. how many were male or female or how old they were. It was already conducting ‘traditional’ online surveys, but in order to measure and understand customer characteristics of its apps, it decided to conduct surveys on iPhones and iPads. Working with GlobalPark (www.globalpark.com), it selected 1,930 users of the iPhone app and included a small advertisement within the news content, asking them to participate in a survey. Of these, 152 completed the whole questionnaire. TOMORROW FOCUS was able to start building up a profile of its app users and to update this periodically by running additional surveys.

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The project highlighted that it was possible to survey hard-to-reach consumers via iPhones. TOMORROW FOCUS discovered that a very high percentage of its app users had a high salary and tended to be younger than the users of its website; most were also male. In its newer iPad app survey, it discovered that the app was used mainly in the evenings and at weekends for leisure purposes. The users of the iPad were also predominantly male and with a very high income.

Summary

The overall focus of this chapter has been to demonstrate that internally generated secondary data offer significant opportunities, not only for decision makers but also for researchers. As with all good secondary data sources, they have a major impact upon the design, focus and value of primary data collection, analyses and interpretation. For the researcher, databases help to build profiles of consumers, linked to the products, communications and distribution methods those consumers favour. Databases present opportunities to experiment in ‘one big laboratory’, build models of consumer behaviour, develop an understanding of the gaps in knowledge of consumers and make links between behavioural and attitudinal data. Much of the data that offer these benefits capture customer buying and even browsing behaviour. The use of the ‘loyalty card’ is one example. Different types of data, including scanner, loyalty card, CRM, web analytics and survey data, may be combined and displayed using geodemographic information systems (GISs). Using base geographic and demographic data, characteristics of existing and potential customers can be analysed and mapped out. Disparate database and analytics-based research sources can be integrated to create powerful consumer insights. As well as what may be seen as traditional forms of marketing research, methods of customer transaction analysis and business intelligence can be mutually supportive and integrated. Social media research methods can add further insights to these forms of gaining consumer insight. There are distinctive forms of expertise and organisations that support these individual approaches. Researchers may see the growth in big data and the skills required to make the most of these techniques as a competitive threat. Alternatively, marketing research can embrace these approaches as an opportunity and be proactive in seeking the means to deliver superior consumer insight. The challenges in integrating these approaches lie in the characteristics of the data they generate – information systems that portray emergent knowledge in an organisation and marketing challenges of what should be an organisation’s target markets and its performance in those markets. The emergence of ‘big data’ and the growing opportunities presented by analytics will shape many of the challenges and opportunities that researchers face going forward.

Questions

1 How may ‘operational data’ held in organisations help to build up an understanding of customer behaviour? 2 What kinds of data can be gathered through electronic scanner devices? 3 What other sources, beyond electronic scanner devices, electronically observe customer behaviour? 4 Describe the benefits to the marketing decision maker of being able to capture data that identify characteristics of consumers and their shopping behaviour in a store.

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5 Describe the benefits to the researcher of being able to capture data that identify characteristics of consumers and their shopping behaviour in a store. 6 Why may the characteristics of consumers differ, based upon where they live? 7 What is a geodemographic classification of consumers? 8 How may data from customer relationship management systems support the practice of marketing research? 9 How may the data from web analytics support the practice of marketing research? 10 How does the compilation of different types of data help to build a strong ‘picture’ of consumer characteristics? 11 What is big data? What are the core dimensions of big data (the four Vs)? 12 What might be the limitations of using Google Analytics as a source of data for marketing research projects?

Exercises

1 Visit the websites of Acorn (www.caci.co.uk) and Mosaic (www.experian.co.uk/ business-strategies). Imagine that you have been commissioned to select a geodemographic system to help a newspaper publisher in a major European city. a For such a business, how may a geodemographic system be used for marketing decision making? b

For such a business, how may a geodemographic system aid marketing research design?

Present the case of which of the above systems would best suit such a business. 2 Call in at a supermarket or store that operates a reward or loyalty card scheme that requires you to apply for membership. Pick up an application form and examine the nature of questions you are expected to answer. a What marketing research use can be made of the data collected from this application form? b

Evaluate the design of this form and make recommendations on how the nature of questions could be improved. 3 You are a marketing manager for Nescafé coffee. One of your major customers is a supermarket that uses a loyalty card scheme to observe its customers electronically. a What would this supermarket know about coffee-buying behaviour through its scheme? b

If it would not share this with you, evaluate any marketing research, web analytics and social media research techniques that you think could generate the same knowledge. 4 Visit the SPSS website (www.ibm.com/software/analytics/spss) and evaluate its ‘predictive analytics’ products. Write a report on how marketing research may feed into and/or feed from predictive analytics for key decisions that may be planned by either a bank or major retailer. 5 Visit the Google website (www.google.co.uk/analytics/) and evaluate its Google Analytics 360 Suite, designed for enterprise users. Write a report on the potential limitations of using Google Analytics as an enterprise tool.

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Notes 1. Woodnutt, T. and Owen, R., ‘The research industry needs to embrace radical change in order to thrive and survive in the digital era’, Market Research Society, Annual Conference (2010). 2. Havermans, J., ‘Knowing everything a customer wants’, Research World (January 2006), 18–19. 3. www.smartfocus.com, accessed 14 January 2011. 4. Berelowitz, M., ‘Ready for Enterprise 2.0?’, Market Leader 3 (June 2009), 48–51. 5. Woodnutt, T. and Owen, R., ‘The research industry needs to embrace radical change in order to thrive and survive in the digital era’, Market Research Society, Annual Conference (2010). 6. Murphy, D., ‘The enlightened researcher’, Research World (December 2006), 18–20. 7. Macer, T., ‘Conference notes – making technology decisions in combining attitudinal and behavioural data’, International Journal of Market Research 51 4 (2009), 543–6. 8. Bakken, D.G., ‘Riding the value shift in market research: only the paranoid survive’, ESOMAR Best Paper Overall, Congress Odyssey, Athens (September 2010). 9. Jolly, M. and Battais, L., ‘Loyalty card databases, revolutionary analysis in shopping behaviour’, ESOMAR Retail Conference, Valencia (February 2007). 10. Hindmarch, J., Wells, C. and Price, F., ‘“It’s as vital as the air that they breathe”. The development of a segmentation of the baby milk market by SMA Nutrician and Leapfrog Research & Planning’, Market Research Society, Annual Conference (2005). 11. Noble, Y., ‘Personalisation, relevance and consistency in database marketing’, Admap 497 (September 2008). 12. Oktar, S., ‘Integrating decision making and marketing intelligence’, ESOMAR Technovate Conference, Cannes (January 2003). 13. Greenberg, P., ‘The impact of CRM 2.0 on customer insight’, Journal of Business & Industrial Marketing 25 (6) (2010), 410–19; Evans, M., Nancarrow, C., Tapp, A. and Stone, M., ‘Future marketers: future curriculum; future shock?’, Journal of Marketing Management 18 (5–6) (2002), 579–96. 14. Greenberg, P., ‘The impact of CRM 2.0 on customer insight’, Journal of Business & Industrial Marketing 25 (6) (2010), 410–19. 15. Dawe, A., ‘Integration is the thing’, The Times – Special Edition e-CRM (11 April 2001), 2–3. 16. Sumner-Smith, D., ‘Getting to know clients lifts profits’, The Sunday Times (26 September 1999), 17. 17. Havermans, J., ‘Knowing everything a customer wants’, Research World (January 2006), 18–19. 18. Fletcher, K., ‘Consumer power and privacy’, International Journal of Advertising 22 (2) (2003), 249–71.

19. ICC/ESOMAR International Code on Market and Social Research (December 2007), 4. 20. ESOMAR, ‘Global Market Research’, ESOMAR Industry Report (2010), 48–9. 21. Nunan, D. and Di Domenico, M., ‘Market research and the ethics of big data’, International Journal of Market Research 55 (4) (2013). 22. IBM, ‘What is big data?’ Available at: http://www-01. ibm.com/software/data/bigdata/what-is-big-data.html, accessed 1 April 2016. 23. IBM, ‘What is big data?’ Available at: http://www-01. ibm.com/software/data/bigdata/what-is-big-data.html, accessed 1 April 2016. 24. Manyika, J., Chui, M., Brown, B., Bughin, J., Dobbs, R. and Hung Byers, A., ‘Big data: The next frontier for innovation, competition and productivity’, McKinsey Global Institute Report (2011). Available online at: http:// www.mckinsey.com/Insights/MGI/Research/Technology_ and_Innovation/Big_data_The_next_frontier_for_ innovation, accessed 31 March 2016. 25. Sterne, J., ‘Web analytics and the march toward better measurement’, Marketing NPV 4 (3) (2007), 18–19. 26. Anon., ‘TUI UK: Engagement warehouse & behavioural conversion programme’, Direct Marketing Association – UK: Gold Award (2010). 27. Maex, D., ‘Learning to read the river: Using math marketing to increase your return on investment’, WPP Atticus Awards: Highly Commended (2009); Anon., ‘Tesco uses loyalty scheme to drive growth’, WARC News (7 October 2009); Rawlinson, R., ‘Beyond brand management – the anatomy of the 21st century marketing professional’, Market Leader 34 (Autumn 2006). 28. Passingham, J. and Blyth, B., ‘A small rock holds back a great wave: Unleashing our potential’, ESOMAR Congress Odyssey, Athens (September 2010). 29. Havermans, J., ‘Boosting consumer excellence’, Research World (April 2006) 2829. 30. Maex, D., ‘Learning to read the river: Using math marketing to increase your return on investment’, WPP Atticus Awards: Highly Commended (2009). 31. Hayward, M., ‘Conference notes – connecting the dots: Joined-up insight finally becomes possible’, International Journal of Market Research 51 (2) (2009). 32. Page, A. and Lai, S., ‘Understanding your competitors: Completing the marketing intelligence jigsaw’, ESOMAR Asia Pacific Conference, Tokyo (March 2005). 33. Woodnutt, T. and Owen, R., ‘The research industry needs to embrace radical change in order to thrive and survive in the digital era’, Market Research Society, Annual Conference (2010). 34. Wilke, A., ‘Mobile surveys win new business for TOMORROW FOCUS Media’, GlobalPark Case Study (2011).

6 Stage 1

Problem definition

Stage 2 Research approach developed

Stage 3 Research design developed

Stage 4 Fieldwork or data collection

Stage 5 Data integrity and analysis

Stage 6 Report preparation and presentation

Qualitative research: its nature and approaches Qualitative research helps the marketer to understand the richness, depth and complexity of consumers.

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Objectives After reading this chapter, you should be able to: 1 explain the difference between qualitative and quantitative research in terms of the objectives, sampling, data collection and analysis and outcomes; 2 describe why qualitative research is used in marketing research; 3 understand the basic philosophical stances that underpin qualitative research; 4 understand the nature and application of ethnographic approaches; 5 understand how qualitative researchers develop knowledge through a grounded theory approach; 6 explain the potential of action research to qualitative researchers; 7 discuss the considerations involved in collecting and analysing qualitative data collected from international markets; 8 understand the ethical issues involved in collecting and analysing qualitative data; 9 describe how developments in social media research have changed established qualitative research techniques and added new techniques.

Overview Qualitative research forms a major role in supporting marketing decision making, primarily as an exploratory design but also as a descriptive design. Researchers may undertake qualitative research to help define a research problem, to support quantitative, descriptive or causal research designs, or as a design in its own right. Qualitative research is often used to generate hypotheses and identify variables that should be included in quantitative approaches. It may also be used after or in conjunction with quantitative approaches, where illumination of statistical findings is needed. Qualitative research designs can also be used in isolation, after secondary data sources have been thoroughly evaluated or even in an iterative process alongside secondary data sources. In this chapter, we discuss the differences between qualitative and quantitative research and the role of each in marketing research. We present reasons for adopting a qualitative approach to marketing research (Stage 2 of the marketing research process). These reasons are developed by examining the basic philosophical stances that underpin qualitative research. The concept of ethnographic techniques is presented, with illustrations of how such techniques support marketing decision makers. The concept of grounded theory is presented, illustrating its roots, the steps involved and the dilemmas for researchers in attempting to be objective and sensitive to the expressions of participants. Action research is an approach to conducting research that has been adopted in a wide variety of social and management research settings. Action research is developing in marketing research, especially in areas such as product, communications and brand design. The concept of co-creation in design through action research offers great potential for consumers, decision makers and researchers alike. The roots of action research are presented, together with the iterative stages involved and the concept of action research teams. Technological developments are changing the manner in which traditional qualitative research techniques are conducted, creating new opportunities for the generation of insight. Examples of these changes and new techniques will be presented, along with the challenges and opportunities these present.

We begin by evaluating the nature of qualitative research with the use of two examples. Given the nature of its products and competitive environment, the first example illustrates how Weihenstephan has used qualitative research in the development of an online research

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community. The second example illustrates how LG Electronics uses qualitative techniques to support design decisions. Note in this example how LG uses different techniques to capture characteristics of consumers that it may be totally unaware of. These examples illustrate the rich insights into the underlying behaviour of consumers that can be obtained by using qualitative techniques.

Real research

The Weihenstephan online research community1 Weihenstephan is a German dairy company belonging to the international Mueller Dairy Group (www.muellergroup.com). As a premium brand it faced major challenges in the German dairy market, which was characterised by very strong private-label brands. It faced numerous strong national brands with intense promotional activities in high-volume categories such as fruit yogurts, flavoured milk drinks and desserts. These categories were affected by very important and influential topics for consumers – e.g. sustainability, fair treatment of farmers and GMO-free products (genetically modified organisms). Weihenstephan recognised that social media were profoundly changing the basics of interpersonal communication, but it also saw several new challenges for researchers arising from this ‘web evolution’: discussion groups developed without being previously sampled; answers were given to questions that had not yet been asked; well-constructed interviews were replaced by dynamic social interaction in virtual communities. In planning its response to the challenges and opportunities to social media research, Weihenstephan felt it could establish two types of research community: (1) by expanding an already existing open consumeroriented website (www.weihenstephan-erleben.de) into a branded open-source community; and (2) setting up a dedicated, closed, online research community. It saw the development of co-creation processes in these communities providing the advantages of combining the classical focus group concept with the benefits of Web2.0. Both types of community could have the same functionalities and features (e.g. creating user profiles, establishing different forums and including quantitative research elements such as voting). Weihenstephan chose the second option, the closed online research community, establishing one place for conducting all qualitative and quantitative marketing research. Qualitative–exploratory questions were investigated within the community. The company targeted around 100–150 participants representing various regions in Germany (equally spilt in urban areas of Munich, Stuttgart, Cologne, Berlin and Hamburg). Its community is working and several key projects have been discussed, including new concept and product ideas in existing subcategories, possible line extensions and general attitudes and habits in possible new sub-categories for the brand.

Real research

Living with your customers2 When designing domestic appliances, the German branch of Korean-based LG Electronics needed a way to find out what people need from its kitchen equipment, washers and vacuum cleaners. The answer was to use ethnographic research with a combination of video diaries and long in-depth interviews so that it could understand

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its customers through sharing their experiences. The company combined the two methods, because one drawback of filming participants was that they might behave atypically, being aware that they were in a test situation. There can also beverbal or subconscious non-verbal communication with the camera operator. The company therefore used the two methods to apply what it saw as ‘non-presence while being present’ in different households and countries. The projects were directed to find out how European consumers used electrical appliances, their workflow in the kitchen, how they go about doing their laundry and their habits in wet and dry floor cleaning. The company believed that habitual non-conscious behaviour should be researched in an authentic environment with a minimum of external factors, so it worked at participants’ homes, usually for a period of five to eight days. It carried out research focusing on the kitchen (10 households each in Hamburg, London and Paris), laundry (10 households each in Hamburg, Budapest, Stockholm, Madrid and London) and vacuum cleaning (15 households in Paris, Budapest, Madrid and London). To observe kitchen behaviour, it installed cameras focused on major appliances for a week for the video diaries. For the laundry study, it installed fixed cameras with a motion detector to observe behaviour with the washing machine and dryer. If these appliances were in the bathroom or toilet, where no one wanted to be filmed, participants themselves could switch the camera on whenever they used the appliances. The company adjusted the technical equipment and location of video cameras according to different individuals and households so it could observe how people sorted clothes, dealt with stains, dried their laundry and did the ironing.

In qualitative research, research agencies and companies are continually looking to find better ways to understand consumers’ thought processes and motivations. This has led to a wealth of research approaches, including techniques borrowed from anthropology, ethnography, sociology and psychology. For example, Philips has a specialist team of researchers, including ethnographers, anthropologists and psychologists. As Marco Bevolo, Design Director at Philips Design, says:3 At Philips Design, we have created research tools to enable ethnographic insights to be delivered into the creative process in a truly actionable way. We aim to push the agenda of research from the side of future studies, people research and their lively embodiment into advanced design.

Primary data: qualitative versus quantitative research Qualitative research An unstructured, primarily exploratory design based on small samples, intended to provide depth, insight and understanding.

Quantitative research Research techniques that seek to quantify data and, typically, apply some form of measurement and statistical analysis.

Primary data are originated by the researcher for the specific purpose of addressing the problem at hand (as explained in Chapter 4). Primary data may be qualitative or quantitative in nature, as shown in Figure 6.1. Dogmatic positions are often taken in favour of either qualitative research or quantitative research by researchers and decision makers alike. Indeed, many researchers will define themselves as either ‘qual’ or ‘quant’. The positions are founded upon which approach is perceived to give the most accurate measurements and understanding of consumers. The extreme stances on this issue mirror each other. Many quantitative researchers are apt to dismiss qualitative studies completely as giving no valid findings, indeed as being little better than journalistic accounts. They assert that qualitative researchers ignore representative

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Figure 6.1 A classification of marketing research data

Secondary data

Primary qualitative data

Primary quantitative data

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Description

Experiment

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sampling, with their findings based on a single case or only a few cases. Equally adamant are some qualitative researchers, who firmly reject statistical and other quantitative methods as yielding shallow or completely misleading information. They believe that to understand cultural values and consumer behaviour, especially in its full contextual richness, requires interviewing or intensive field observation. Qualitative techniques they see as being the only methods of data collection sensitive enough to capture the nuances of consumer attitudes, motives and behaviour.4 There are great differences between the quantitative and qualitative approaches to studying and understanding consumers. The arguments between qualitative and quantitative researchers about their relative strengths and weaknesses are of real practical value. The nature of marketing decision making encompasses a vast array of problems and types of decision maker. This means that seeking a singular and uniform approach to supporting decision makers by focusing on one approach is futile. This should have become apparent when evaluating the huge array of data sources that can generate consumer insight (as discussed in Chapter 5). Defending qualitative approaches for a particular marketing research problem through the positive benefits it bestows and explaining the negative alternatives of a quantitative approach is healthy, and vice versa. Business and marketing decision makers have always used both approaches, and will continue to need both.5 The distinction between qualitative and quantitative research can be in the context of research designs (as discussed in Chapter 3). There is a close parallel in the distinctions between ‘exploratory and conclusive research’ and ‘qualitative and quantitative research’. There is a parallel, but the terms are not identical. There are circumstances where qualitative research can be used to present detailed descriptions that cannot be measured in a quantifiable manner: for example, in describing characteristics and styles of music that may be used in an advertising campaign, or in describing the interplay of how families go through the process of choosing, planning and buying a holiday.6 Conversely, there may be circumstances where quantitative measurements are used conclusively to answer specific hypotheses or research questions using descriptive or experimental techniques. Beyond answering specific hypotheses or research questions, there may be sufficient data to allow data mining or an exploration of relationships between individual measurements to take place.

The nature of qualitative research Qualitative research encompasses a variety of methods that can be applied in a flexible manner, to enable participants to reflect upon and express their views or to observe their behaviour. It seeks to encapsulate the behaviour, experiences and feelings of participants

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in their own terms and context; for example, when conducting research on children, an informal and child-friendly atmosphere is vital, considering features such as the decoration of the room with appropriately themed posters.7 Qualitative research is based on at least two intellectual traditions.8 The first, and perhaps most important, is the set of ideas and associated methods from the broad area of in-depth psychology and motivational research.9 This movement was concerned with the less conscious aspects of the human psyche. It led to a development of methods to gain access to individuals’ subconscious and/or unconscious levels. So, while individuals may present a superficial explanation of events to themselves or to others, these methods sought to dig deeper and penetrate the superficial. The second tradition is the set of ideas and associated methods from sociology, social psychology and social anthropology, and the disciplines of ethnography, linguistics and semiology. The emphases here are upon holistic understanding of the world-view of people. The researcher is expected to ‘enter’ the hearts and minds of those they are researching, to develop an empathy with their experiences and feelings. Both traditions have a concern with developing means of communication between the researcher and those being researched. There can be much interaction between the two broad traditions, which in pragmatic terms allows a wide and rich array of techniques and interpretations of collected data. Qualitative research is a significant contributor to the marketing research industry, accounting for substantial expenditure (around 13% of all spending on marketing research methods).10 If one considers the growth and development of social media research, much of which is qualitative in nature, it is clear to see that this form of research is growing and of major impact upon decision making. In commercial terms, it is a global industry that generates revenues over 1 billion annually. However, it is not just a matter of business value. Qualitative thinking has had a profound effect upon marketing, strategic and design thinking and the marketing research industry as a whole.

Rationale for using qualitative research It is not always possible, or desirable, to use structured quantitative techniques to obtain information from participants or to observe them. Thus, there are several reasons to use qualitative techniques. These reasons, either individually or in any combination, explain why certain researchers adopt a particular approach (Stage 2 of the marketing research process) to how they conduct research, analyse data and interpret their findings: 1 Preferences and/or experience of the researcher. Some researchers are more oriented and temperamentally suited to do this type of work. Just as some researchers enjoy the challenge of using statistical techniques, there are researchers who enjoy the challenges of qualitative techniques and the interpretation of diverse types of data. Such researchers have been trained in particular disciplines (e.g. anthropology) and philosophies (e.g. hermeneutics) that traditionally make use of qualitative research designs and techniques. 2 Preferences and/or experience of the research user. Some decision makers are more oriented to receiving support in a qualitative manner. This orientation could come from their training, but it could also be due to the type of marketing decisions they have to take. Decision makers working in a creative environment of product design, advertising copy or the development of brand ‘personalities’, for example, may have a greater preference for data that will feed such design and visually based decisions. In the following example, consider how decision makers would get to understand and cope with the frustrations felt by consumers. Consider also the implications for a brand

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if designers and marketers do not fully understand the consumer behaviour that was presented in a visual manner.

Real research

I once sat with a women who was ironing for five hours11 Microsoft’s chief design anthropologist, Anne Kirah, set out what she believed was one of her most successful research projects. She watched 40 ordinary, randomly chosen American families try to set up and use an early version of Windows XP. Not one of them managed to do it. After many hours of frustration most ended up furious with M icrosoft, and the video she took of these families made a big impact at Microsoft. The first assumption from management was that something was wrong with the people she had chosen, among them a couple in their seventies. What management realised was that, on the contrary, there was something wrong with the way they had been testing software until then: volunteers who had completed the task in laboratory conditions were all tech enthusiasts and therefore not at all representative of the population. Anne says: I am an observer; that is what an ethnographer is. It is not taking a list of questions you would otherwise ask online and, sitting in someone’s kitchen, asking the same thing. I go to people’s homes when they wake up and leave when they go to bed; I go with them. If they are changing a baby’s nappy, I watch them do it. I once sat with a women who was ironing for five hours. I do not go into homes to study computers. I do not give a damn whether they have a computer or not. If you really want to know what makes people tick, and their motivations and aspirations, that is where innovation comes from. Do not ask them questions, listen to them.

3 Sensitive information. Participants may be unwilling to answer or to give truthful answers to certain questions that invade their privacy, embarrass them, or have a negative impact on their ego or status. Questions that relate to sanitary products and contraception are examples of personally sensitive issues. In business-to-business marketing research, questions that relate to corporate performance and plans are examples of commercially sensitive issues. Techniques that build up an amount of rapport and trust, that allow gentle probing in a manner that suits individual participants, can help researchers get close to participants, and may allow sensitive data to be elicited. 4 Subconscious feelings. Participants may be unable to provide accurate answers to questions that tap their subconscious. The values, emotional drives and motivations residing at the subconscious level are disguised from the outer world by rationalisation and other ego defences. For example, a person may have purchased an expensive sports car to overcome feelings of inferiority. But if asked ‘Why did you purchase this sports car?’ that person may say ‘I got a great deal’, ‘My old car was falling apart’, or ‘I need to impress my customers and clients’. The participants do not have to put words to their deeper emotional drives until researchers approach them! In tapping into those deeper emotional drives, qualitative research can take a path that evolves and is right for the participant.

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5 Complex phenomena. The nature of what participants are expected to describe may be difficult to capture with structured questions. For example, participants may know what brands of wine they enjoy, what types of music they prefer or what images they regard as being prestigious. They may not be able to clearly explain why they have these feelings or where these feelings are coming from. The following example illustrates a qualitative research challenge that tapped into and revealed characteristics of sensitive information, subconscious feelings and complex phenomena. The use of visual ethnography for MTV proved to be highly engaging and relevant for the participants.

Real research

Visual ethnography at MTV12 MTV Networks (www.mtvne.com) wanted to understand identity construction among young people. Instead of using a traditional ethnographical approach, it used an alternative approach that combined principles from visual ethnography and netnography. Using pictures for observing individuals in their environment is at the core of visual ethnography. In the early days of visual ethnography, pictures were mainly taken by the observer. A new approach has shifted control towards participants, who take their own (self-relevant) pictures. In line with this new approach, MTV gave full control to the participants. The user-generated ethnography took place in two phases. First, participants got the general instruction to take pictures of all aspects of their lives that they believed that MTV should know about in order to get a better understanding of who they were and to get a sense of their daily lives. Next, at several times they received ‘special tasks’. These tasks were created to make sure that they collected enough ‘relevant observations’ in order to help answer the research questions. When creating the special tasks, it was important not to mention the topic of the study directly. Instead, each participant was asked to photograph the context where their identity manifests itself. A special role was assigned to clothes and peers. Clothes are one of the main product categories that teenagers use to express their identity. Participants were therefore asked to take pictures of clothes that they wear on several different types of occasions: clothes that they wear at home as a reflection of their personal identity; clothes that represent their social identity; clothes that give insights into their aspirational identity; clothes that they do not want to wear. A similar reasoning was applied for peers, asking participants to take pictures of the friends and people they find important (social identity), others with whom they are not friends but would like to be friends (aspirational identity), adolescents whom they would not like to be friends with (non-group) and others who are different than themselves but still socially acceptable. This last group was included to get a more detailed view on all social groups. To get a better understanding of personal identity, participants were also invited to take pictures of objects that were typical of themselves. Finally, participants were asked to take pictures of the place where they could really be themselves.

6 The holistic dimension. The object of taking a holistic outlook in qualitative research is to gain a comprehensive and complete picture of the whole context in which the phenomena of interest occur. It is an attempt to describe and understand as much as possible about the whole situation of interest. Each scene exists within a multi-layered and interrelated context, and it may require multiple methods to ensure the researcher covers all angles. This orientation helps the researcher discover the interrelationships among the various components of the phenomenon under study. In evaluating different forms of consumer behaviour,

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the researcher seeks to understand the relationship of different contextual environments upon that behaviour. Setting behaviour into context involves placing observations, experiences and interpretations into a larger perspective.13 An example of this may be measuring satisfaction with a meal in a restaurant. A questionnaire can break down components of the experience in the restaurant and quantify the extent of satisfaction with these. But what effect did the ‘atmosphere’ have upon the experience? What role did the type of music, the colour and style of furniture, aromas coming from the kitchen, other people in the restaurant, the mood when entering the restaurant, feelings of relaxation or tension as the meal went on, contribute to the feeling of atmosphere? Building up an understanding of the interrelationship of the context of consumption allows the qualitative researcher to build up this holistic view. This can be done through qualitative observation and interviewing. 7 Developing new theory. This is perhaps the most contentious reason for conducting qualitative research. (Chapter 11 details how causal research design through experiments helps to generate theory.) Qualitative researchers may argue that there are severe limitations in conducting experiments on consumers and that quantitative approaches are limited to elaborating or extending existing theory. The development of ‘new’ theory through a qualitative approach is called ‘grounded theory’, which will be addressed later. 8 Interpretation. Qualitative techniques often constitute an important final step in research designs. Large-scale surveys and audits often fail to clarify the underlying reasons for a set of findings. Using qualitative techniques can help to elaborate and explain underlying reasons in quantitative findings.14

Philosophy and qualitative research15 Theory A conceptual scheme based on foundational statements, or axioms, that are assumed to be true.

Operationalised The derivation of measurable characteristics to encapsulate marketing phenomena; e.g. the concept of ‘customer loyalty’ can be operationalised through measurements such as the frequency of repeat purchases or the number of years that a business relationship has existed.

Empiricism A theory of knowledge. A broad category of the philosophy of science that locates the source of all knowledge in experience.

Positivism A philosophy of language and logic consistent with an empiricist philosophy of science.

Paradigm A set of assumptions consisting of agreed-upon knowledge, criteria of judgement, problem fields and ways to consider them.

Positivist perspectives In Chapter 2 we discussed the vital role that theory plays in marketing research. Researchers rely on theory to determine which variables should be investigated, how variables should be operationalised and measured, and how the research design and sample should be selected. Theory also serves as a foundation on which the researcher can organise and interpret findings. Good marketing research is founded upon theory and contributes to the development of theory to improve the powers of explanation, prediction and understanding in marketing decision makers.16 The dominant perspective of developing new theory in marketing research has been one of empiricism and, more specifically, positivism. The central belief of a positivist position is a view that the study of consumers and marketing phenomena should be ‘scientific’ in the manner of the natural sciences. Researchers of this persuasion adopt a framework for investigation akin to the natural scientist. For many, this is considered to be both desirable and possible. A fundamental belief shared by positivists is the view that the social and natural worlds ‘conform to certain fixed and unalterable laws in an endless chain of causation’. 17 The main purpose of a scientific approach to marketing research is to establish causal laws that enable the prediction and explanation of marketing phenomena. To establish these laws, a scientific approach must have, as a minimum, reliable information or ‘facts’. The emphasis on facts leads to a focus upon objectivity, rigour and measurement. As an overall research approach (using the description of a paradigm or research approach, as developed in Chapter 2) qualitative research does not rely upon measurement or the establishment of ‘facts’ and so does not fit with a positivist perspective. However, if qualitative research is just seen as a series of techniques, they can be used to develop an understanding of the nature of a research problem and to develop and pilot questionnaires. In other words, the positivist perspective of qualitative research is to see it as a set of techniques, applied as preliminary stages to more ‘rigorous’ techniques that measure, i.e. surveys and questionnaires. This use of qualitative techniques is fine but can have many limitations.

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Conducting in-depth interviews, focus groups or ethnographic techniques can help enormously in understanding the language and logic of consumers. In turn, this understanding of a language and logic can strengthen and focus the design of surveys and questionnaires. However, using qualitative techniques just to develop quantitative techniques represents a narrow perspective of their rich, creative and exploratory powers. As an illustration, we will examine how different perspectives of the nature and value of qualitative research can impact upon how a technique may be conducted – in this case, focus group discussions. The term ‘focus group discussion’ is commonly used across all continents, yet it subsumes different ways of applying the technique. There are two main schools of thought that underpin the technique, which may be termed ‘cognitive’ and ‘conative’. The American, Japanese and European illustrations used simplify much of the variations that occur and develop within these two schools. The examples serve to illustrate the origins, thinking and focus that can be adopted in running focus groups: 1 Cognitive. American and Japanese researchers generally follow this tradition, which largely follows a format and interviewing style as used in quantitative studies. ‘Americanstyle groups’ is shorthand in Europe for large groups (10 participants on average), a structured procedure and a strong element of external validation. Within the cognitive approach, the analysis or articulation has been worked on before, and so the interviews are largely meant to confirm or expand on known issues. The following example presents a caricature of the Japanese style of focus group to illustrate a cognitive underpinning. 2 Conative. European researchers generally follow this tradition. This style assumes a different starting point – one that emphasises exploration, with analysis taking place during and after the group. There is less structure to the questions, with group members being encouraged to take their own paths of discussion, make their own connections and let the whole process evolve.

Real research

Japanese focus groups18 The aspiration in using the focus group in Japan is to replicate the often-stimulating, rich and thought-provoking experience (for clients) that one finds in the West. Yet, many of the practices and reflexes in use in the West are at odds with the need at the heart of Japanese research orthodoxy to reduce the bias in the focus group. For instance, the moderator has been discouraged from explaining too much about the concept of the focus group, what marketing research does and what the study at hand is trying to achieve. Sharing such information has been considered contamination of the participants and introducing a bias. For the moderator to show human warmth beyond the strictly polite has likewise been considered a biasing approach. Free expression of opinion and having an opinion is a value in Western culture, whereas in Japan it is not. NonJapanese clients are inevitably frustrated with the failure to achieve a group that engages in an open discussion with the sharing of deep thoughts and opposing statements: people there do not usually and openly express an opinion on things and people. As part of the quantitative heritage of qualitative research in Japan, and the consequent obsession with avoiding bias, the focus group room has been synthetic, grey and devoid of emotion and ‘homeyness’ in an attempt to reach a neutral, bias-free setting. Japanese research has introduced boardrooms and office chairs into rooms with no windows and artificial light on grey walls. Is it a surprise that it is hard for participants to talk about their daily lives and personal matters? The successful application of home-visit and ethnography research in Japan demonstrates that, in relaxed and humanised conditions, consumers can talk more openly about their inner needs and private thoughts. We

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believe that a room with a relaxing décor, music in the background, dimmed lights and even alcohol can help the participant engage in the group situation and offer deeper insight. What this means is that it is important to create a more at-home atmosphere.

Table 6.1 summarises the differences between the American (cognitive) and European (conative) approaches to conducting focus groups. Note the longer duration of the European approach to allow the exploration to develop. To maintain the interest and motivation of participants for this time period, the interview experience must be engaging, stimulating and enjoyable. International marketers have always been aware that qualitative research, as it developed in the USA and Europe, involves quite different practices, stemming from different premises and yielding different results. American-style qualitative research started from the same evaluative premise as quantitative research but on a smaller scale. This made it cheaper, quicker and useful for checking out the less-critical decisions. European-style qualitative research started from the opposite premise to quantitative research: it was developmental, exploratory and creative rather than evaluative. It was used as a tool of understanding, to get underneath consumer motivation.19 The American style uses a detailed discussion guide, which follows a logical sequence and is usually strictly adhered to. The interviewing technique involves closed questions and straight answers. This type of research is used primarily to inform about behaviour and to confirm hypotheses already derived from other sources. For this reason, clients who have attended groups often feel they do not need any further analysis; the group interaction supplies the answers. Transcripts are rarely necessary and reports are often summarised, or even done away with altogether. Table 6.1

The two schools of thought about ‘focus group discussions’20

Characteristics

Cognitive

Conative

Purpose

Demonstration

Exploration

Sample size

10–12

6–8

Duration

1.5 hours

1.5 to 6 hours

Interviewing

Logical sequence

Opportunistic

Questions

Closed

Open

Techniques

Straight questions, questionnaires, hand shows, counting

Probing, facilitation, projectives, describing

Response required

Give answers

Debate issues

Interviewer

Moderator

Researcher

Observer’s role

To get proof

To understand

Transcripts

Rarely necessary

Usually full

Analysis

On the spot

Time-consuming

Focus of time

Preplanning

Post-fieldwork

Accusations against other style

‘Formless’

‘Over-controlling’

Suited for

Testing or proving ideas

Meaning or understanding

Output

To be confirmed in quantitative studies

Can be used in its own right to support decision makers

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The European style is used primarily to gain new insight; it also works as a discussion guide, but in a less structured way. The interviewing technique is opportunistic and probing. Projective techniques are introduced to help researchers understand underlying motivations and attitudes. Because the purpose is ‘understanding’, which requires a creative synthesis of (sometimes unconscious) consumer needs and brand benefits, analysis is time-consuming and usually involves full transcripts. In the above descriptions of American and European traditions of applying qualitative techniques, it is clear that the American perspective is positivist, i.e. aims to deliver a ‘factual’ impression of consumers. The facts may be established, but they may not be enough; they may not provide the richness or depth of understanding that certain marketing decision makers demand. So, although a positivist perspective has a role to play in developing explanations, predictions and understanding of consumers and marketing phenomena, it has its limitations and critics. In a seminal paper that reviews the evolution and future of qualitative research, the eminent qualitative practitioner Peter Cooper encapsulated the power of focus groups, viewed in a non-positivist manner. He argued that they have delivered and continue to deliver understanding and anticipation of consumers, opening up factors driving choice, adapting to and predicting the changing power and influence of consumers:21 Forming groups has given us primates our evolutionary competitive edge. They enable us to learn, solve problems, communicate, share experiences, and understand others. Around the flickering campfire we swapped stories, developed relationships, built up togetherness, groomed one another, resolved conflicts, played games, adopted roles, deceived, told falsehoods, and invented spirits and gods. There is a compulsion about groups that we all share. One explanation is that in the contemporary world where campfires no longer exist and there is reduced opportunity for real social interaction, joining in groups is yearned for. But focus groups are not kinship groups. True, participants are paid to come, but most are made up of people who do not know one another, and are largely drawn from wider circles that happen to have some behaviour in common. We know them as types not as people. This is where their everlasting fascination lies. Participants are often deliberately strangers, ‘virtual ’ people, who then disappear. We know that people posture, exaggerate, deceive, but we can step into their shoes for a fleeting few hours. The dominance of positivist philosophy in marketing research has been and is being challenged by other philosophical perspectives, taken and adapted from disciplines such as anthropology and sociology. These perspectives have helped researchers to develop richer explanations and predictions and especially an understanding and a meaning, as seen through the eyes of consumers.

Interpretivist perspectives In general, there are considered to be two main research paradigms that are used by marketing researchers.22 These are the positivist paradigm and the interpretivist paradigm (though these are by no means the only research paradigms that may be adopted by researchers).23 Table 6.2 presents alternative names that may be used to describe these paradigms. While it may be easier to think of these as quite clear, distinct and mutually exclusive perspectives of developing valid and useful marketing knowledge, the reality is somewhat different. There is a huge array of versions of these paradigms, presented by philosophers, researchers and users of research findings. These versions change depending upon the assumptions of researchers and the context and subjects of their study, i.e. the ultimate nature of the research problem. It has long been argued that both positivist and interpretivist paradigms are valid in conducting marketing research and help to shape the nature of techniques that researchers apply.24

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Table 6.2

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Alternative paradigm names Positivist

Interpretivist

1. Quantitative

1. Qualitative

2. Objectivist

2. Subjectivist

3. Scientific

3. Humanistic

4. Experimentalist

4. Phenomenological

5. Traditionalist

5. Revolutionist

In order to develop an understanding of what an interpretivist paradigm means, Figure 6.2 presents characteristic features of the two paradigms.

Comparison of positivist and interpretivist perspectives The paradigms can be compared through a series of issues. The descriptions of these issues do not imply that any particular paradigm is stronger than the other. In each issue there are relative advantages and disadvantages specific to any research question under investigation. The issues are dealt with in the following subsections. 1 Reality. The positivist supposes that reality is ‘out there’ to be captured. It thus becomes a matter of finding the most effective and objective means possible to draw together information about this reality. The interpretivist stresses the dynamic, participant-constructed and evolving nature of reality, recognising that there may be a wide array of interpretations of realities or social acts. Figure 6.2 Reality

Paradigm features POSITIVIST Objective

ITERPRETIVIST Subjective

Researcher participant

POSITIVIST Independent

ITERPRETIVIST Interacting

Values

POSITIVIST Unbiased

ITERPRETIVIST Biased

Researcher language

POSITIVIST Impersonal

ITERPRETIVIST Personal

Theory and research design

POSITIVIST • Deduction • Determinist • Cause/effect • static • Context free • Laboratory • Prediction/control • Reliability/validity • Representative • Experimentation INTERPRETIVIST • Induction • Freedom of will • Multiple influences • Organic/evolving • Context bound • Ethnographic • Understanding • Preceptive decision making • Theoretical sample • Case studies

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2 Researcher–participant. The positivist sees the participant as an ‘object’ to be measured in a reliable or consistent manner. The interpretivist may see participants as ‘peers’, or even ‘companions’, seeking the right context and means of observing and questioning to suit individual participants. Such a view of participants requires the development of rapport an amount of interaction and evolution of method as the researcher learns of the best means to gain access and elicit information. 3 Values. The positivist seeks to set aside his or her own personal values. The positivist’s measurements of participants are being guided by established theoretical propositions. The task for the positivist is to remove any potential bias. The interpretivist recognises that their own values affect how they observe, question, probe and interpret. The task for interpretivists is to reflect upon and realise the nature of their values and how these impact upon how they observe, question and interpret. 4 Researcher language. In seeking a consistent and unbiased means to measure, the positivist uses a language in questioning that is uniformly recognised. This uniformity may emerge from existing theory (to allow comparability of findings) and/or from the positivist’s vision of what may be relevant to the target group of participants. Ultimately, the positivist imposes a language and logic upon target participants in a reliable or consistent manner. The interpretivist seeks to draw out the language and logic of target participants. The language used may differ between participants and develop in different ways as the interpretivist learns more about a topic and the nature of participants. Causality Causality applies when the occurrence of X increases the probability of the occurrence of Y.

Extraneous variables Variables other than dependent and independent variables, which may influence the results of an experiment.

Determinism A doctrine espousing that everything that happens is determined by a necessary chain of causation.

Target population The collection of elements or objects that possess the information sought by the researcher and about which inferences are made.

Reliability The extent to which a scale produces consistent results if repeated measurements are made on the characteristic.

Validity The extent to which a measurement represents characteristics that exist in the phenomenon under investigation.

Case study A detailed study based upon the observation of the intrinsic details of individuals, groups of individuals and organisations.

5 Theory and research design. In the development of theory, the positivist seeks to establish causality (to be discussed in detail in Chapter 11) through experimental methods. Seeking causality helps the positivist to explain phenomena and hopefully predict the recurrence of what has been observed in other contexts. There are many extraneous variables that may confound the outcome of experiments, hence the positivist will seek to control these variables and the environment in which an experiment takes place. The ultimate control in an experiment takes place in a laboratory situation. In establishing causality through experiments, questions of causality usually go hand in hand with questions of determinism; i.e. if everything that happens has a cause, then we live in a determinist universe. The positivist will go to great pains to diagnose the nature of a research problem and establish an explicit and set research design to investigate the problem. A fundamental element of the positivist’s research design is the desire to generalise findings to a target population. Most targeted populations are so large that measurements of them can only be managed through representative sample surveys. The positivists use theory to develop theconsistent and unbiased measurements they seek. They have established rules and tests of the reliability and validity of their measurements, and continually seek to develop more reliable and valid measurements. In the development of theory, the interpretivist seeks to understand the nature of multiple influences of marketing phenomena through case studies. The search for multiple influences means focusing upon the intrinsic details of individual cases and the differences between different classes of case. This helps the interpretivist to describe phenomena and hopefully gain new and creative insights to understand ultimately the nature of consumer behaviour in its fullest sense. The consumers that interpretivists focus upon, live, consume and relate to products and services in a huge array of contexts, hence the interpretivist will seek to understand the nature and effect of these contexts on the chosen cases. The contexts in which consumers live and consume constitute the field in which interpretivists immerse themselves to conduct their investigations. In understanding the nature and effect of context upon consumers, the interpretivist does not consider that everything that happens has a cause and that we live in a determinist universe. There is a recognition and respect for the notion of free will. The interpretivist will go to great pains to learn from each step of the research process and adapt the research design as their learning develops. The interpretivist seeks to diagnose the

Chapter 6 Qualitative research: its nature and approaches

Evolving research design A research design where particular research techniques are chosen as the researcher develops an understanding of the issues and participants.

Theoretical sampling Data-gathering driven by concepts derived from evolving theory and based on the concept of ‘making comparisons’.

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nature of a research problem but recognises that a set research design may be restrictive and so usually adopts an evolving research design. A fundamental element of the interpretivist’s research design is the desire to generalise findings to different contexts, such as other types of consumer. However, rather than seeking to study large samples to generalise to target populations, the interpretivist uses theoretical sampling. This means that the data-gathering process for interpretivists is driven by concepts derived from evolving theory, based on the notion of seeking out different situations and learning from the comparisons that can be made. The purpose is to go to places, people or events that will maximise opportunities to discover variations among concepts. Interpretivists use theory initially to help guide which cases they should focus upon, the issues they should observe and the context of their investigation. As their research design evolves they seek to develop new theory and do not wish to be ‘blinkered’ or too focused on existing ideas. They seek multiple explanations of the phenomena they observe and create what they see as the most valid relationship of concepts and, ultimately, theory. Interpretivists seek to evaluate the strength of the theory they develop. The strongest means of evaluating the strength of interpretivist theory lies in the results of decision making that is based on the theory. Interpretivists continually seek to evaluate the worth of the theories they develop. A principal output of research generated by an interpretivist perspective should therefore be findings that are accessible and intended for use. If they are found to be meaningful by decision makers and employed successfully by them, this may constitute further evidence of the theory’s validity. If employed and found lacking, questions will have to be asked of the theory, about its comprehensibility and comprehensiveness and about its interpretation. If it is not used, the theory may be loaded with validity but have little value.

Summarising the broad perspectives of positivism and interpretivism Deduction A form of reasoning in which a conclusion is validly inferred from some premises, and must be true if those premises are true.

The positivist seeks to establish the legitimacy of his or her approach through deduction. In a deductive approach, the following process unfolds: •

•

• •

•

An area of enquiry is identified, set in the context of well-developed theory, which is seen as vital to guide researchers, ensuring that they are not naïve in their approach and do not ‘reinvent the wheel’. The issues upon which to focus an enquiry emerge from the established theoretical framework. Specific variables are identified that the researchers deem should be measured, i.e. hypotheses are set. An ‘instrument’ to measure specific variables is developed. ‘Participants’ give answers to set and specific questions with a consistent language and logic. The responses to the set questions are analysed in terms of a prior established theoretical framework. The researchers test theory according to whether their hypotheses are accepted or rejected. From testing theory in a new context, they seek to develop existing theory incrementally.

Such a process means that positivists reach conclusions based upon agreed and measurable ‘facts’. The building and establishment of ‘facts’ forms the premises of deductive arguments. Deductive reasoning starts from general principles from which the deduction is to be made, and proceeds to a conclusion by way of some statement linking the particular case in question. A deductive approach has a well-established role for existing theory: it informs the development of hypotheses, the choice of variables and the resultant measures.25 Whereas the deductive approach starts with theory expressed in the form of hypotheses, which are then

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Induction A form of reasoning that usually involves the inference that an instance or repeated combination of events may be universally generalised.

tested, an inductive approach avoids this, arguing that it may prematurely close off possible areas of enquiry.26 The interpretivist seeks to establish the legitimacy of their approach through induction. In an inductive approach, the following process unfolds: •

•

• •

•

An area of enquiry is identified, but with limited or no theoretical framework. Theoretical frameworks are seen as restrictive, narrowing the researcher’s perspective and an inhibitor to creativity. The issues upon which to focus an enquiry are either observed or elicited from participants in particular contexts. Participants are aided to explain the nature of issues in a particular context. Broad themes are identified for discussion, with observation, probing and in-depth questioning to elaborate the nature of these themes. The researchers develop their theory by searching for the occurrence and interconnection of phenomena. They seek to develop a model based upon their observed combination of events. Such a process means that interpretivists reach conclusions without ‘complete evidence’.

With the intense scrutiny of individuals in specific contexts that typify an interpretivist approach, tackling large ‘representative’ samples is generally impossible. Thus, the validity of the interpretivist approach is based upon ‘fair samples’. Interpretivists should not seek only to reinforce their own prejudice or bias, seizing upon issues that are agreeable to them and ignoring those that are inconvenient. If they are to argue reasonably, they should counteract this tendency by searching for conflicting evidence.27 Their resultant theory should be subject to constant review and revision.

Ethnographic research

Ethnography A research approach based upon the observation of the customs, habits and differences between people in everyday situations.

It is clear that an interpretive approach does not set out to test hypotheses but to explore the nature and interrelationships of marketing phenomena. The focus of investigation is a detailed examination of a small number of cases rather than a large sample. The data collected are analysed through an explicit interpretation of the meanings and functions of consumer actions. The product of these analyses takes the form of verbal descriptions and explanations (sometimes supported by visuals or other forms of art), with quantification and statistical analysis playing a subordinate role. These characteristics are the hallmark of a research approach that has developed and been applied to marketing problems over many years in Europe, and increasingly so across the globe. This research approach is one of ethnographic research. Ethnography as a general term includes observation and interviewing and is sometimes referred to as participant observation. It is, however, used in the more specific case of a method that requires a researcher to spend a large amount of time observing a particular group of people, by sharing their way of life.28 Ethnography is the art and science of describing a group or culture. The description may be of a small tribal group in an exotic land or a toy factory in Poland. The task is much like the one taken on by the investigative reporter, who interviews relevant people, reviews records, takes photographs, weighs the credibility of one person’s opinions against another’s, looks for ties to special interests and organisations and writes the story for a concerned public and for professional colleagues. A key difference between the investigative reporter and the ethnographer, however, is that whereas the journalist seeks out the unusual, the murder, the plane crash, or the bank robbery, the ethnographer writes about the routine daily lives of people. The more predictable patterns of human thought and behaviour are the focus of enquiry.29 The origins of ethnography are in the work of nineteenth-century anthropologists who travelled to observe different pre-industrial cultures. An example in a more contemporary

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context could be the study of death rituals in Borneo, conducted over a period of two years by the anthropologist Peter Metcalf.30 Today, ‘ethnography’ encompasses a much broader range of work, from studies of groups in one’s own culture, through experimental writing, to political interventions. Moreover, ethnographers today do not always ‘observe’, at least not directly. They may work with cultural artefacts, such as written texts, or study recordings of interactions they did not observe at first hand,31 or even, as in the following example, the observations of teenagers as viewed through photographs taken on their mobile phones.

Chocolate or mobile? 32

Real research

Ayobamidele Gnädig and Oliver Schieleit are project directors at the German qualitative research agency H.T.P. Concept (www.htp-concept.de). They asked teenagers to photoblog their snacking habits with their mobile phones and saw that many of these were ‘boredom-relief’ moments where they were waiting for trains, buses or friends who were late for an appointment. When they spent time with them, a whole day or just an afternoon, they saw this moment crop up time and again. They also believe they witnessed a change, in that these moments were increasingly being filled differently than maybe five or ten years ago. Instead of quickly buying a Mars bar at the nearby kiosk, a young teen was just as likely to spend time waiting for a bus in writing text messages to friends. This meant that, in some contexts, the text message had become ‘top of the mind’ over the chocolate bar. Through understanding by observing and not by probing the dynamics, H.T.P. Concept offered a first step for chocolate brands to develop new ideas, communications and distribution concepts to address this opportunity.

Ethnography cannot reasonably be classified as just another single method or technique.33 In essence, it is a research discipline based upon culture as an organising concept and a mix of both observational and interviewing tactics to record behavioural dynamics. Above all, ethnography relies upon entering participants’ natural-life worlds, at home, while shopping, at leisure and in the workplace. The researcher essentially becomes a naïve visitor in that world by engaging participants during realistic product-usage situations in the course of daily life. Whether called on-site, observational, naturalistic or contextual research, ethnographic methods allow marketers to delve into actual situations in which products are used, services are received and benefits are conferred. Ethnography takes place not in laboratories but in the real world. Consequently, clients and practitioners benefit from a more holistic and better nuanced view of consumer satisfactions, frustrations and limitations than in any other research method.34 Researchers apply ethnographic methods in natural retail or other commercial environments in order to fully appreciate the nature of consumer experiences. There are several objectives that lie behind these studies, one of which is oriented towards a detailed ecological analysis of sales behaviour. In other words, consumer interactions with all of the elements that comprise retail store environments: lighting, smells, signage, display of goods, the location, size and orientation of shelving. Observing how these may impact upon the consumers’ experience and their ultimate buying behaviour can be of great value to designers and marketers. The ethnographer’s role is to decode the meaning and impact of these ecological elements. Often, these studies utilise time-lapse photography as a tool for behavioural observation and data collection over extensive periods of time, and can avoid actual interaction with consumers. Ethnographic research achieves this immersion with consumers through the following aims: •

Seeing through the eyes of others. Viewing events, actions, norms and values from the perspective of the people being studied.

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•

• •

•

Description. Built up in many written and visual forms to provide clues and pointers to the layers of ‘reality’ experienced by consumers. Contextualism. Attending to mundane detail to help understand what is going on in a particular context. Whatever the sphere in which the data are being collected, events can be best understood when they are situated in the wider social and historical context. Process. Viewing social life as involving an interlocking series of events. Avoiding early use of theories and concepts. Rejecting premature attempts to impose theor ies and concepts that may exhibit a poor fit with participants’ perspectives. This will be developed further in this chapter when we examine grounded theory. Flexible research designs. Ethnographers’ adherence to viewing social phenomena through the eyes of their participants or subjects has led to a wariness regarding the imposition of prior and possibly inappropriate frames of reference on the people they study. This leads to a preference for an open and unstructured research design, which increases the possibility of coming across unexpected issues.

The following example displays characteristics of all the above aims and introduces new developments in ethnography as applied in marketing research.

Real research

Netnography at Nivea35 Nivea is the best-known brand of the multinational corporation Beiersdorf, based in Hamburg, Germany. In order to integrate the voice of consumers beyond traditional marketing research techniques, such as concept tests or focus groups, the Nivea Body Care Division instituted a holistic co-creation process that included the application of netnography. They used this approach to start new-product development, helping R&D to immerse and orientate itself in the consumers’ world. The goal was to draw a landscape of needs, wishes, concerns, consumer language and potential product solutions by users, which were explicitly and implicitly expressed in online communities and social media. They started with a broad search of more than 200 online communities, forums and blogs in three languages, screening all kinds of ‘consumer tribes’ that have emerged online. The most relevant and insightful communities and forums on cosmetics, health, lifestyle, fashion, sports and do-it-yourself were observed and analysed, examples being beauty24.de, bubhub.com.au, badgerandblade.com, glamour.de or undershirtguy.com. To follow this search, threads of consumer conversations were analysed using qualitative data software. In the field of deodorants, the consumer dialogue revealed that users speak about a number of issues revolving around the buying, application and effectiveness of deodorants in their own language and with a distinct classification. In order to overcome issues consumers also resorted to self-made remedies or diverted substances from their intended use. Certain needs, concerns or suggestions for product improvements repeatedly occurred in consumers’ online conversations. Those ‘gold nuggets’ , i.e. fresh, relevant, inspiring and enduring findings, were then aggregated to consumer insights. For example, one consumer insight introduced Nivea to do-it-yourself solutions that were exchanged between users online. Those self-made remedies were systematically structured, depicted and supported by a coding report of consumer

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statements. The consumer insights helped Beiersdorf to develop a deep understanding of consumers, the language they use and what truly bothers them. Applying the netnography method, Beiersdorf was able to identify trends in the field of body care and obtain innovative product and marketing ideas. In the final step of the netnography, product designers joined the research team and helped to interpret and translate the consumer insights into initial products.

Netnography An adaptation of ethnography that analyses the free behaviour of individuals in online environments.

Co-creation The practice of developing new designs, including products or marketing communications, through collaboration with consumers.

This example introduces the method of netnography, an adaptation of ethnography that analyses the free behaviour of individuals in online environments.36 Observing online communities can be much faster, simpler and less expensive than traditional ethnography. It is also unelicited, so more natural and unobtrusive than surveys and interviews. Netnography can refer to the passive process of following conversations and interactions on the internet at the individual level; this was the approach taken by Nivea. It can also involve a more active engagement with consumers on the net directing questions, or becoming a participant observer in a community.37 Passive or active netnography approaches create privacy, security and safety challenges for researchers. Social media have changed the rules on how ‘findable’ somebody is. This has enormous implications for privacy and safety. Debates about what is ‘in the public domain’, and what can be used when, where and how, will impact enormously upon the development of codes of conduct for researchers. The use of social media data and mobile devices are both increasingly important as part of ethnographic research respectively (and are covered in more detail in Chapters 17 and 18 respectively). Irrespective of ethical challenges they may bring, the use of ethnographic approaches has rapidly developed in marketing research. The Nivea example illustrates a very creative and engaging use of netnography as part of a co-creation process. Co-creation is the practice of developing new designs, including products or marketing communications, through collaboration with consumers. In the early 2000s, large advertisers including Nike established successful co-creation projects. The Danish toy company Lego was another advocate of co-creation, with a project beginning in 2004 signing up ‘master-builders’ to help design products. Initially, only four people were invited to join; the following year 10 collaborators joined, followed by 100 from 10,000 consumers who applied.38 Enthusiasm for what Lego was doing spread to the blogosphere and to social networks, with a host of unofficial websites set up by fans suggesting further innovations to the firm.39 One of the key features of all the descriptions and illustrations of forms of ethnography is the context in which the consumer is behaving. The researcher observes people experiencing, taking in and reacting to communications, product and services and retail experience all behaving naturally in the set context. For example, in the context of shoppers this does not just mean the retail outlet they visit. The processes of choosing and buying products, of using products or giving them as gifts, of reflecting upon and planning subsequent purchases, are all affected by contextual factors. Context operates on several levels, including the immediate physical and situational surroundings of consumers, as well as language, character, culture and history. Each of these levels can provide a basis for the meaning and significance attached to the roles and behaviour of consumption:40 Can we divorce the ways we buy, use and talk about products from the cultural and linguistic context within which economic transitions occur? The answer is an emphatic NO. The ethnographer may observe the consumer acting and reacting in the context of consumption. The ethnographer may see a shopper spending time reading the labels on cat food, showing different brands to their partner, engaged in deep conversation, pondering, getting

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frustrated and putting tins back on the shelf. The ethnographer may see the same shopper more purposefully putting an expensive bottle of cognac into a shopping trolley without any discussion and seemingly with no emotional attachment to the product. The ethnographer may want to know what is going on. How may the consumer explain their attitudes and motivations behind this behaviour? This is where the interplay of observation and interviewing helps to build such a rich picture of consumers. In questioning the shopper in the above example, responses of ‘we think that Rémy Martin is the best’ or ‘we always argue about which are the prettiest cat food labels’ would not be enough. The stories and contexts of how these assertions came to be would be explored. The ethnographer does not tend to take simple explanations for activities that, in many circumstances, may be habitual to consumers. Ethnographic practice takes a highly critical attitude towards expressed language. It challenges our accepted words at face value, searching instead for the meanings and values that lie beneath the surface. In interviewing situations, typically this involves looking for gaps between expressed and non-verbal communication elements. For example, if actual practices and facial and physical gestures are inconsistent with a participant’s expressed attitudes towards the expensive cognac, we are challenged to discover both the reality behind the given answer and the reasons for the ‘deception’. Ethnographic research is also effective as a tool for learning situationally and culturally grounded language – the appropriate words for everyday things, as spoken by various age or ethnic groups. Copywriters and strategic thinkers are always pressed to talk about products and brands in evocative and original ways. Ethnography helps act as both a discovery and an evaluation tool.41 To summarise, ethnographic approaches are useful when the marketing research objectives call for:42 1 High-intensity situations. To study high-intensity situations, such as a sales encounter, meal preparation and service or communication between persons holding different levels of authority. 2 Behavioural processes. To conduct precise analyses of behavioural processes, e.g. radio listening behaviour, home-computer-purchasing decisions or home-cleaning behaviour. 3 Memory inadequate. To address situations where the participant’s memory or reflection would not be adequate. Observational methods can stand alone or can complement interviewing as a memory jog. 4 Shame or reluctance. To work with participants who are likely to be ashamed or reluctant to reveal actual practices to a group of peers. If they were diabetic, for example, participants may be reluctant to reveal that they have a refrigerator full of sweet snacks something that an ethnographic observer would be able to see without confronting the subject.

Listening Listening involves the evaluation of naturally occurring conversations, behaviours and signals. The information that is elicited may or may not be guided, but it brings the voice of consumers’ lives to brand.

In these applications, the ethnographer is expected to analyse critically the situations observed. The critique or analysis can be guided by theory but, in essence, the researcher develops a curiosity, thinks in an abstract manner and at times steps back to reflect and see how emerging ideas connect. By reacting to the events and participants as they face them, to draw out what they see as important, ethnographers have the ability to create new explanations and understandings of consumers. This ability to develop a new vision, to a large extent unrestricted by existing theory, is the essence of a grounded theory approach, which is explained and illustrated in the next section. Before we evaluate the nature and application of grounded theory, it is worth examining one final example of an ethnographic study that embraces the idea of ‘listening’. Listening involves the evaluation of naturally occurring conversations, behaviours and signals. The information that is elicited may or may not be guided, but it brings the voice of consumers’ lives to brand. Every day, millions of consumers talk about all aspects of their

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lives online. This wealth of naturally occurring consumer expression offers the opportunity to understand consumers on their terms, using their language and logic. Due to the internet, high-speed access and the ‘conversational webs’ of blogs, forums, social networks, Twitter, communities and wikis, people are talking with one another about their problems, experiences, likes and dislikes, life in general, and their feelings and experiences of brands. By tuning in to relevant conversations (i.e. by listening), it is argued that more can be learned about consumer attitudes and needs than through traditional ‘questioning’ methods alone. Advocates of listening approaches would argue that researchers have interacted with ‘participants’ on their terms: they ask the questions they want to ask, the way they want to ask them, when they want to ask them. This can be seen as intrusive and out of step with the lives of consumers and is not conducive to developing a thorough, context-laden understanding of consumer opinions and needs.43 By listening, researchers may be able to learn more about consumers and prospects by understanding the natural, rich, unfiltered word of mouth around products and service experiences. This approach is illustrated in the following example.

Real research

The essentials of listening at Hennessy Cognac44 Hennessy (www.hennessy.com), the leading cognac brand, discovered a rising trend in links made between its company website and BlackPlanet.com, the largest social network for African-Americans. Digging deeper, Hennessy learned that numbers of BlackPlanet members linked their personal pages to Hennessy’s site. Some went further, decorating their pages with borrowed images of Hennessy brands. By listening to signals embedded in linking behaviour, Hennessy had stumbled upon a passionate market it was not aware of. Interested to learn more about these consumers, Hennessy then studied a random sample of BlackPlanet member web pages to understand their themes and use of brand imagery. Hennessy also commissioned an online survey with research partner CRM Metrix (www.crmmetrix.com) to profile audience attitudes, usage and influence. Hennessy discovered that visions of the Hennessy brand expressed in the member pages ‘were not necessarily ours, but this does not make them any less valid’. Research showed that ‘the brand belongs as much to its consumers as to its managers . . . We must listen without prejudice.’ Stated another way, this was a shining illustration of customer ‘co-creation’ and extraordinary brand engagement. The survey data described 8 of 10 of these individuals as ‘high-value’ consumers, with a strong influence on the alcohol choices of people around them. About half the participants were opinion leaders, a higher-than-usual percentage. Recognising the inherent and potential long-term value in BlackPlanet members, Hennessy then sought to learn what would improve its site and make it more interesting and enjoyable. Hennessy went further than just tweaking the site; it asked for and listened to suggestions about ‘what would make your experience of drinking Hennessy cognacs more enjoyable?’. Realising that BlackPlanet members enjoyed drinking socially and mixing Hennessy into drinks, it added recipes highlighting cognac as an ingredient and offered Hennessy-branded e-invitations for parties. Fiveyears after the initial round of responses, the Hennessy site showed the brand’s ongoing commitment to listening and evolving the relationship and experience. In 2009, Hennessy’s ‘Artistry’ initiative sponsored musicians and music tours, streamed music and showcased artists. Hennessy also added a social networking component by creating a presence on Facebook and YouTube.

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Grounded theory Grounded theory A qualitative approach to generating theory through the systematic and simultaneous process of data collection and analysis.

The tradition of grounded theory was developed by Glaser and Strauss in the late 1950s and published in their seminal work The Discovery of Grounded Theory in 1967.45 At that time, qualitative research was viewed more as impressionistic or anecdotal, little more than ‘soft science’ or journalism.46 It was generally believed that the objective of sociology should be to produce scientific theory, and to test this meant using quantitative methods.47 Qualitative research was seen to have a place, but only to the extent to which it developed questions that could then be verified using quantitative techniques. Glaser and Strauss accepted that the study of people should be scientific, in the way understood by quantitative researchers. This meant that it should seek to produce theoretical propositions that were testable and verifiable, produced by a clear set of replicable procedures. Glaser and Strauss defined theory as follows:48 theory in sociology is a strategy for handling data in research, providing modes of conceptualization for describing and explaining. The theory should provide clear enough categories and hypotheses so that crucial ones can be verified in present and future research; they must be clear enough to be readily operationalized in quantitative studies when these are appropriate. The focus upon developing theory was made explicit in response to criticisms of ethnographic studies that present lengthy extracts from interviews or field observations. Strauss sought to reinforce his view of the importance of theory, illustrated by the following quote:49 much that passes for analysis is relatively low-level description. Many quite esteemed and excellent monographs use a great deal of data, quotes or field note selections. The procedure is very useful when the behavior being studied is relatively foreign to the experiences of most readers or when the factual assertions being made would be under considerable contest by skeptical and otherwise relatively well-informed readers. Most of these monographs are descriptively dense, but alas theoretically thin. If you look at their indexes, there are almost no new concepts listed, ones that have emerged in the course of research. In contrast to the perhaps casual manner in which some ethnographers may be criticised for attempts at developing theory, the grounded theorist follows a set of systematic procedures for collecting and analysing data. This systematic procedure is used to encourage researchers to use their intellectual imagination and creativity to develop new theories, to suggest methods for doing so, to offer criteria to evaluate the worth of discovered theory and to propose an alternative rhetoric of justification.50 The most distinctive feature of grounded theory is its commitment to ‘discovery’ through direct contact with the social phenomena under study, coupled with a rejection of a priori theorising. This feature does not mean that researchers should embark on their studies without any general guidance provided by some sort of theoretical understanding. It would be nigh on impossible for a researcher to shut out the ideas in the literature surrounding a particular subject. However, Glaser and Strauss argued that preconceived theories should be rejected, as they obstruct the development of new theories by coming between researchers and the subjects of their study. In other words, the strict adherence to developing new theory built upon an analytical framework of existing theory can result in ‘narrow-minded’ researchers who do not explore a much wider range of explanations and possibilities. With the rejection of a priori theorising and a commitment to imaginative and creative discovery comes a conception of knowledge as emergent. This knowledge is created by researchers in the context of investigative practices that afford them intimate contact with the subjects and phenomena under study.51 The following example illustrates the use of grounded theory in the development of theory related to how advertising works. The study was conducted by a senior marketing research professional and a professor of advertising. The example is then followed by a description of the process involved in developing theory through a grounded theory process.52

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Agency practitioners’ meta-theories of advertising53 What do advertising agency practitioners think about how advertising works? This study’s basic aim was to understand practitioners’ thinking about the work of advertising in their own terms. As there was little substantive research of this perspective, a grounded theory approach to qualitative research was used. Semi-structured, in-depth interviews were used as the key field method; these allowed the discovery of participant- determined points of view. Preliminary preparations for data collection started well before actual interviewing. Informal interviews were conducted with qualitative–ethnographic experts. Email and phone conversations were exchanged about the feasibility of the project, opinions about method and tips for effective interviewing were exchanged. Based on the insights gained in these preparations and from the relevant literature, an initial interview guide was developed. This was built around three questions: (1) what the content of practitioners’ knowledge is; (2) how practitioners know what they know; and (3) how they use this knowledge in everyday practice. The interview guide used both opening ‘grand tour’ questions as well as more specific probes. Twenty-eight participants were interviewed until theoretical saturation was achieved (i.e. concepts were identified and linked to other concepts until no new information was obtained). Three occupational groups were interviewed: account managers, account planners and creative directors. Interviews lasted from 45 to 90 minutes. Most took place in the participants’ offices. Practitioners were encouraged to talk freely but were also probed using academic theories in the early stages of the interviews for comparative purposes. Extensive field notes were composed immediately following the interviews. These reflections helped refine ways of asking questions and with the development of emerging concepts. The field notes were entered into the NVivo (www.qsrinternational.com) qualitative data analysis software. The findings, presented in a manuscript format, were checked with participants. They agreed that the content accurately reflected their thoughts. This study was the first attempt to get at agency practitioners’ fundamental presuppositions about advertising knowledge in a thoroughly holistic and theoretically informed way.

Attempting to gain an objective viewpoint Much of the thinking and application of qualitative data analysis is inextricably linked to the collection of data (as will be discussed in detail in Chapter 9). For the grounded theorist, data collection and analysis occur in alternating sequences. Analysis begins with the first interview and observation, which leads to the next interview or observation, followed by more analysis, more interviews or fieldwork and so on. It is the analysis that drives the data collection. Therefore there is a constant interplay between the researcher and the research act. Because this interplay requires immersion in the data, by the end of the enquiry the researcher is shaped by the data, just as the data are shaped by the researcher. The problem that arises

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during this mutual shaping process is how one can become immersed in the data and maintain a balance between objectivity and sensitivity. It could be argued that objectivity is necessary to arrive at an impartial and accurate interpretation of events. Sensitivity is required to perceive the subtle nuances and meanings of data and to recognise the connections between concepts. Both objectivity and sensitivity are necessary in making sense of data and creating insight. Objectivity enables the researcher to have confidence that the findings are a reasonable, impartial representation of a problem under investigation, whereas sensitivity enables creativity and the discovery of new theory from data.54 During the analytic process, grounded researchers attempt to set aside their knowledge and experience to form new interpretations about phenomena. Yet, in their everyday lives, they rely on knowledge and experience to provide the means for helping them to understand the world in which they live and to find solutions to problems encountered. Most researchers have learned that a state of objectivity is impossible and that in every piece of research, quantitative or qualitative, there is an element of subjectivity. What is important is to recognise that subjectivity is an issue and that researchers should take appropriate measures to minimise its intrusion into their investigations and analyses. Being objective means a constant drive for transparency in the actions, decisions and conclusions taken in relation to data. Qualitative researchers should have an openness, a willingness to listen and to ‘give voice’ to participants, in whatever manner they wish to express themselves. This is particularly important given the array of forms of expression that are possible through social media. Good qualitative research means hearing what others have to say, seeing what others do and representing these as accurately as possible. It means developing an understanding of those they are researching, while recognising that their understanding is often based on the values, culture, training and experiences that they bring from all aspects of their lives; these can be quite different from those of their participants.55 As well as being open to participants, qualitative researchers should reflect upon what makes them, as observers, ‘see’ and ‘listen’ in particular ways. This usually means that, while working on a particular project, the researcher keeps a diary or journal. This diary is used to make notes about the conditions of interviews and observations, of what worked well and what did not, of what questions the researcher would have liked to ask but did not think of at the time. As the researcher reads through the diary in the analysis process, the entries become part of the narrative explored, and reveal to the researcher and to others the way the researcher has developed their ‘seeing’ and ‘listening’. (Again, research diaries will be covered in more detail in examining qualitative data analysis in Chapter 9.)

Developing a sensitivity to the meanings in data Having sensitivity means having insight into, and being able to give meaning to, the events and happenings in data. It means being able to see beneath the obvious to discover the new. This quality of the researcher occurs as they work with data, making comparisons, asking questions and going out and collecting more data. Through these alternating processes of data collection and analysis, meanings that are often elusive at first later become clearer. Immersion in the data leads to those sudden insights.56 Insights do not just occur haphazardly; rather, they happen to prepared minds during interplay with the data. Whether we want to admit it or not, we cannot completely divorce ourselves from who we are and what we know. The theories that we carry around in our heads inform our research in multiple ways, even if we use them quite unselfconsciously.57 Ultimately, a grounded theory approach is expected to generate findings that are meaningful to decision makers and appropriate to the tasks they face. Ethnographic techniques are well suited to being driven by a grounded research approach. As with other interpretivist forms of research, if it is found meaningful by decision makers and employed successfully by them, there is further evidence of the theory’s validity. Another qualitative approach that is absolutely meaningful to decision makers in that its primary focus is to deliver actionable results is called action research.

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Action research Background

Action research A team research process, facilitated by a professional researcher(s), linking with decision makers and other stakeholders who together wish to improve particular situations.

The social psychologist Kurt Lewin had an interest in social change, and specifically in questions of how to conceptualise and promote social change. Lewin is generally thought to be the person who coined the term ‘action research’ and gave it meanings that are applicable today.58 In action research, Lewin envisaged a process whereby one could construct a social experiment with the aim of achieving a certain goal.59 The classic case of the origins of action research comes from the early days of the Second World War. The case revolved around a problem that essentially was a traditional marketing research challenge. Lewin was commissioned by the US authorities in their quest to use tripe as part of the regular daily diet of American families.60 The research question was: ‘To what extent could American housewives be encouraged to use tripe rather than beef for family dinners?’ Choice cuts of beef were scarce at this time and were destined primarily for the fighting troops. Lewin’s approach to this research question was to conduct a study in which he trained a limited number of housewives in the art of cooking tripe for dinner. He then surveyed how this training had an effect on their daily cooking habits in their own families. In this case, action research was synonymous with a ‘natural experiment’, meaning that the researchers in a real-life context invited participants into an experimental activity. This research approach was very much within the bounds of conventional applied social science, with its patterns of authoritarian control, but it was aimed at producing a specific, desired social outcome. The above example can be clearly seen from a marketing perspective. It is easy to see a sample survey measuring attitudes to beef, to tripe, to feeding the family and to feelings of patriotism. From a survey, one can imagine advertisements extolling the virtues of tripe, how tasty and versatile it is. But would the campaign work? Lewin’s approach was not just to understand the housewives’ attitudes but to engage them in the investigation and the solution: to change attitudes and behaviour. Lewin is credited with coining a couple of important slogans within action research that hold resonance with the many action researchers that practise today. The first is ‘nothing is as practical as a good theory’ and the second is ‘the best way to try to understand something is to change it’. In action research it is believed that the way to ‘prove’ a theory is to show how it provides an in-depth and thorough understanding of social structures – understanding gained through planned attempts to invoke change in particular directions. The appropriate changes are in the proof. Lewin’s work was a fundamental building block of what today is called action research. He set the stage for knowledge production based on solving real-life problems. From the outset, he created a new role for researchers and redefined criteria for judging the quality of the enquiry process. Lewin shifted the researcher’s role from being a distant observer to involvement in concrete problem solving. The quality criteria he developed for judging a theory to be good focused on its ability to support practical problem solving in real-life situations.61 From Lewin’s work has developed a rich and thriving group of researchers who have developed and applied his ideas throughout the world. In management research, the study of organisational change with the understanding and empowerment of different managers and workers has utilised action research to great effect. There has been comparatively little application of action research in marketing research, though that is changing. Researchers and marketing decision makers alike are learning of the nature of action research, the means of implementing it and the benefits it can bestow. In an era where marketers, designers (of brands, products, communications and a whole array of consumer experiences) and consumers in co-creation projects are working more closely together, action research holds many rich possibilities.

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Approach The term ‘action research’ includes a whole range of approaches and practices, each grounded in different traditions, in different philosophical and psychological assumptions, sometimes pursuing different political commitments. Sometimes it is used to describe a positivist approach in a ‘field’ context, or where there is a trade-off between the theoretical interests of researchers and the practical interests of organisation members. Sometimes it is used to describe relatively uncritical consultancy based on information gathering and feedback.62 It is beyond the scope of this text to develop these different traditions, so the following describes an approach that is grounded in the Lewin foundations of the approach, and, like his work, is applicable to marketing. Action research is a team research process, facilitated by one or more professional researchers linking with decision makers and other stakeholders, such as customers, who together wish to change or improve particular situations. Together, the researcher and decision makers or stakeholders define the problems to be examined, generate relevant knowledge about the problems, learn and execute research techniques, take actions and interpret the results of actions based on what they have learned.63 There are many iterations of problem definition, generating knowledge, taking action and learning from those actions. The whole process of iteration evolves in a direction that is agreed by the team. Action researchers accept no a priori limits on the kinds of research techniques they use. Surveys, secondary data analyses, interviews, focus groups, ethnographies and life histories are all acceptable, if the reason for deploying them has been agreed by the action research collaborators and if they are used in a way that does not oppress participants. Action research is composed of a balance of three elements. If any one of the three is absent, then the process is not action research: 1 Research. Research based on any quantitative or qualitative techniques, or combination of them, generates data, and in the analyses and interpretation of the data there is shared knowledge. 2 Participation. Action research involves trained researchers who serve as facilitators and ‘teachers’ to team members. As these individuals set their action research agenda, they generate the knowledge necessary to transform the situation and put the results to work. Action research is a participatory process in which everyone involved takes some responsibility. 3 Action. Action research aims to alter the initial situation of the organisation in the direction of a more self-managed and more rewarding state for all parties. An example of an action research team in marketing terms could include: •

•

Researchers. Trained in a variety of qualitative and quantitative research techniques, and with experience of diagnosing marketing and research problems. Strategic marketing managers. Decision makers who work at a strategic level in the organisation and have worked with researchers, as well as those who have no experience of negotiating with researchers. Operational marketing managers. Decision makers who have to implement marketing activities. These may be the individuals who meet customers on a day-to-day basis and who really feel the impact and success of marketing ideas. Advertising agency representatives. Agents who have worked with strategic decision makers. They may have been involved in the development of communication campaigns to generate responses from target groups of consumers. Customers. Existing customers who may be loyal and have had many years of experience of the company (initiating and funding the action research), its products and perhaps even its personnel. Target customers. Potential customers who may be brand switchers or even loyal customers to competitive companies.

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Figure 6.364 illustrates how action research may be applied. This model of action research is taken from the subject area of the management of change, which is relevant to many of the problems faced by marketing decision makers. The process aims to create a learning community in a team such as that above. The team develops an understanding of issues to the extent that it makes sound judgements and takes effective action to implement the changes it wishes to make.

Figure 6.3 The action research approach

Diagnosis

Evaluation

Analysis Learning process

Action

Feedback

The process in Figure 6.3 can be described as follows: •

•

Diagnosis. The present state of affairs would be set out, including the perceived barriers to change and an initial broad statement of desired direction for the organisation. Diagnosis would include documenting the change process and all data-gathering activities, such as secondary data gathering, surveys, interviews or observations. Analysis. An initial interpretation of data gathered would be made. From this the issues to be tackled would be identified. Summary findings and the development of a framework, with set tasks for team members in subsequent data gathering, would be drawn up. Feedback. Data analyses would be fed back for examination and discussion in the team. ‘Ownership’ of the diagnosis would be developed to formulate a commitment to action. Action. Individual courses of action and the development of broader strategies would be formulated. Evaluation. There would be an ongoing review of methods and outcomes. The effectiveness of any action would be evaluated against agreed criteria and critical success factors.

All of these stages are interrelated, so there is no definitive path that the team would take. In subsequent iterations of activities, the team could move around the stages in any order that suits its needs. The process is illustrated in the following example, where action research was used in the development process of a new product. The detail of the case is limited, but there is sufficient to see action research being successfully practised in a manner that brings together a team with diverse forms of thinking and expertise.

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Real research

The dissolution of the demarcation lines between clients, researchers and consumers65 To obtain an optimum number of results usable for the development process of a new product, a joint research approach was chosen by Deutsche Telekom Laboratories (www.laboratories.telekom.com). The idea was to combine ‘the best of three worlds’ by forming one team of researchers experienced in the field of consumer segmentation and qualitative research methods (members of Sinus Sociovision, www.sinus-institut.de) and one team of experts in the field of consumer behaviour and needs (members of Deutsche Telekom Laboratories and Berlin University of Technology). In addition, five experts from the field of innovation development with a background in psychology, speech recognition and engineering were invited to join the research preparations and to provide a broader view on the technology landscape. The task of the researchers was to formulate an approach by which the everyday life of information and communications technology (ICT) users could be explored. For Deutsche Telekom Laboratories the most important issue was to find out about ICT rituals and the situations in which ICT was used. Issues such as ‘fears’ and ‘barriers’ were also of interest, especially for the development of appropriate applications and services in the future. In order to attain these results, the researchers had to dive deep into the world of the Deutsche Telekom Laboratories and to learn about their ideas, problems attitudes, and cognitive structures, decision-making processes and organisational structures. Via meetings and workshops prior to the project/study, research experts were enabled to think like the developers and Deutsche Telekom Laboratories specialists. A first round of interviewing was applied, and additional rounds of expert interviews were conducted to understand the client. They installed feedback loops in order to discuss changes in the team during the research process and to include possible new issues in the interviews or observations. Among the researchers, a continuous learning process was observable since many participants developed their own ideas about how they integrate ICT into their everyday lives. The findings from this research were summarised in an additional feedback loop in order to coach the ICT specialists working for the client.

Summary

Qualitative and quantitative research should be viewed as complementary. Unfortunately, many researchers and decision makers do not see this, taking dogmatic positions in favour of one or the other. The defence of qualitative approaches for a particular marketing research problem, through the positive benefits it bestows and through explaining the negative alternatives of a quantitative approach, should be seen as healthy, as should the defence of quantitative approaches. Decision makers use both approaches and will continue to need both. Qualitative and quantitative approaches to marketing research are underpinned by two broad philosophical schools, namely positivism and interpretivism. The central belief of a positivist position is a view that the study of consumers and marketing phenomena should be ‘scientific’ in the manner of the natural sciences. Researchers of this persuasion adopt a framework for investigation akin to that of the natural scientist. The interpretivist researcher does not set out to test hypotheses in the manner

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of the positivist researcher. Their aim is primarily to explore and understand the nature and interrelationships of marketing phenomena. The focus of investigation is a detailed examination of a small number of cases rather than a large sample. The data collected are analysed through an explicit interpretation of the meanings and functions of consumer actions. The product of these analyses takes the form of verbal descriptions and explanations, with quantification and statistical analysis playing a subordinate role. In examining qualitative approaches, ethnography as a general term includes observation and interviewing and is growing in use through the use of social media observations and interactions. Ethnography is used to describe a range of methods that require researchers to spend a large amount of time observing a particular group of people, by sharing or immersing themselves in their way of life. The ethnographer is expected to analyse critically the situations observed. The critique and the analysis can be guided by theory but, in essence, the researcher develops a curiosity, thinks in an abstract manner and at times steps back to reflect and see how emerging ideas connect. By reacting to the events, narrative, images and other forms of participants and by drawing out what they see as important, ethnographers have the ability to create new explanations and understandings of consumers. Some ethnographers may be criticised in their attempts at developing theory. In response, the grounded theorist follows a set of systematic procedures for collecting and analysing data. A distinctive feature of a grounded theory approach is that the collection of data and their analysis take place simultaneously, with the aim of developing general concepts, to organise data and integrate these into a more general, formal set of categories. Ethnographic techniques and a grounded theory approach can be applied in an action research framework. Action research is a team research process, facilitated by one or more professional researchers, linking with decision makers and other stakeholders who together wish to improve particular situations. Together, the researcher and decision makers or stakeholders define the problems to be examined, generate relevant knowledge about the problems, learn and execute research techniques, take actions and interpret the results of actions based on what they have learned. There are many iterations of problem definition, generating knowledge, taking action and learning from those actions. The whole process of iteration evolves in a direction that is agreed by the team. When conducting qualitative research, the researcher and the client must respect participants. This should include protecting the anonymity of participants, honouring all statements and promises used to ensure participation and conducting research in such a way as not to embarrass or harm the participants. With the emergence of techniques that use social media, such as ethnography using electronic communities, maintaining an ethical relationship with participants is becoming far more challenging. The internet and the growth in social media and the use of mobile devices present huge opportunities for the qualitative researcher. Online versions of traditional forms of qualitative research, such as focus groups, semi-structured or in-depth interviews and ethnographic techniques, have been developed to great effect. New qualitative techniques have been developed that add further consumer insights. These developments have the potential to present research to participants as meaningful and enjoyable engagements.

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Questions

Exercises

1 What criticisms do qualitative researchers make of the approaches adopted by quantitative researchers, and vice versa? 2 Why is it not always possible or desirable to use quantitative marketing research techniques? 3 Evaluate the differences between a European and an American approach to qualitative research. 4 Describe the characteristics of positivist and interpretivist researchers. 5 In what ways may the positivist and the interpretivist view potential research participants? 6 What role does theory play in the approaches adopted by positivist and interpretivist researchers? 7 What does ethnographic research aim to achieve in the study of consumers? 8 What is netnography? What additional consumer insights can netnography deliver? 9 Why may marketing decision makers wish to understand the context of consumption? 10 Describe and illustrate two research techniques that may be utilised in ethnographic research. 11 What stages are involved in the application of a grounded theory approach? 12 Is it possible for researchers to be objective? 13 What does ‘listening’ mean for the qualitative researcher? How may researchers ‘listen’ to consumers? 14 Describe the key elements to be balanced in the application of action research. 15 What do you see as the key advantages and challenges of conducting qualitative research online?

1 An advertising agency has selected three pieces of music that it could use in a new advertising campaign. It has come to you as a researcher to help in making the case for selecting the right piece of music for the campaign. What would be the case for using qualitative techniques for this task? 2 Would a 12-year-old schoolchild who has not been exposed to any academic theories about ‘service delivery quality’ be more creative and open-minded, and thus better suited to conduct a grounded theory approach, compared with a 22-year-old business studies graduate? Would your view change in any way if the study were about a game or toy that was specifically targeted at 12 year olds? 3 You are a brand manager for Microsoft’s Xbox division. You wish to invest in an ethnographic study (that could include netnography techniques) of young gamers who regularly play multi-player online games. Ask another student to play the role of marketing director. What case would you make to the marketing director about the value of investing in an ethnographic study? 4 In the above case of an ethnographic study of young gamers for Microsoft, what would you feel to be appropriate contexts or circumstances to conduct this work? 5 In a small group, discuss the following issues: ‘Quantitative research is more important than qualitative research because it generates conclusive findings’ and ‘Qualitative research should always be followed by quantitative research to confirm the qualitative findings’.

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Notes 1. Methner, T. and Frank, D., ‘Welcome to the house of research: Achieving new insights and better brand knowledge through courageous ways of collaboration in what is usually a competitive environment’, ESOMAR Congress Odyssey, Athens (September 2010). 2. You, J.S. and Kaltenback, E., ‘Living with your customers’, Research World (November 2005), 40. 3. Murphy, D., ‘Feeding inspiration’, Research World (April 2006), 14–15. 4. Ford, J., Carlson, L. and Kover, A.J., ‘Comments – the quant-qual debate: Where are we in advertising?’, International Journal of Advertising 27 (4) (2008), 659–69; Alioto, M.F. and Gillespie, D., ‘The complex customer: Applying qualitative methods in automotive NPD’, ESOMAR Qualitative Research, Athens (October 2006). 5. Cooper, P., ‘We’ve come a long way’, Research World (November 2007), 8–11; Cooper, P., ‘Consumer understanding, change and qualitative research’, Journal of the Market Research Society 41 (1) (January 1999), 3. 6. Bowman, J., ‘Sounding off’, Research World (July/ August 2006), 36–7. 7. Kenway, J., ‘Keep on moving’, Research (November 2005), 36. 8. Cooper, P., ‘In search of excellence: The evolution and future of qualitative research’, ESOMAR Annual Congress, Berlin (September 2007).

Interpreting Qualitative Data: Methods for Analysing Talk, Text and Interaction (London: Sage, 2006), 9. 16. Hunt, S.D., Modern Marketing Theory (Cincinnati, OH: South Western Publishing, 1991); Hunt, S., Marketing Theory: The Philosophy of Marketing Science (Homewood, IL: Irwin, 1983), 2. 17. Tasgal, A., ‘“All because …”: From command and control to cascades and contexts’, Market Research Society, Annual Conference (2005). 18. Djourvo, D., ‘A global method, a local approach: How the Japanese group can gain focus’, ESOMAR Asia Pacific Conference, Singapore (April 2008). 19. Cooper, P., ‘The evolution of qualitative research: From imperialism to synthesis’, ESOMAR, Qualitative Research Singapore (1997); Broadbent, K., ‘When East meets West, quite what does “qualitative” mean?’, ResearchPlus (March 1997), 14. 20. Goodyear, M., ‘Divided by a common language: Diversity and deception in the world of global marketing’, Journal of the Market Research Society 38 (2) (April 1996), 105. 21. Cooper, P., ‘In search of excellence: The evolution and future of qualitative research’, ESOMAR Annual Congress, Berlin (September 2007). 22. Hussey, J. and Hussey, R., Business Research (Basingstoke: Macmillan Business, 1997).

11. Bowman, J., ‘Real people for real data’, Research World (January 2007), 40.

23. For a comprehensive review of the philosophy of social sciences, see Jarvie, I.C. and Zamora-Bonilla, J. (eds), The SAGE Handbook of the Philosophy of Social Sciences (London: Sage, 2011); in addition see Nicolai, A. and Seidl, D., ‘That’s relevant! Different forms of practical relevance in management science’, Organization Studies 31 (9–10) (2010), 1257–85; Healy, M. and Perry, C., ‘Comprehensive criteria to judge validity and reliability of qualitative research within the realism paradigm’, Qualitative Market Research: An International Journal 3 (3) (2000), 118–26.

12. Truong, Y., ‘Personal aspirations and the consumption of luxury goods’, International Journal of Market Research 52 (5) (2010), 655–73.

24. Channon, C., ‘What do we know about how research works?’, Journal of the Market Research Society 24 (4) (1982), 305–15.

13. Verhaeghe, A., den Bergh, J.V. and Colin, V., ‘Me, myself and I: Studying youngsters’ identity by combining visual ethnography & netnography’, ESOMAR Qualitative Research, Istanbul (November 2008).

25. Hamlin, R.P., ‘Forum – small business market research: Examining the human factor’, International Journal of Market Research 49 (5) (2007), 551–71; Ali, H. and Birley, S., ‘Integrating deductive and inductive approaches in a study of new ventures and customer perceived risk’, Qualitative Market Research: An International Journal 2 (2) (1999), 103–10.

9. Sykes, W., ‘Validity and reliability in qualitative market research: A review of the literature’, Journal of the Market Research Society 32 (3) (1990), 289; De Groot, G., ‘Qualitative research: Deeply dangerous or just plain dotty?’, European Research 14 (3) (1986), 136–41. 10. ESOMAR, ‘Global Market Research’, ESOMAR Industry Report (2010), 16.

14. Branthwaite, A. and Patterson S., ‘The vitality of qualitative research in the era of blogs and tweeting: An anatomy of contemporary research methods’, ESOMAR, Qualitative, Barcelona (November 2010). 15. It is recognised that this topic is treated in a superficial manner and is really a basic introduction to the key ideas. Students who are interested in developing these ideas further should see Harrison, R.L. and Reilly, T.M., ‘Mixed methods designs in marketing research’, Qualitative Market Research: An International Journal 14 (1) (2011), 7–26; Rod, M., ‘Marketing: Philosophy of science and “epistobabble warfare”’, Qualitative Market Research: An International Journal 12 (2) (2009), 120–9; Heath, R. and Feldwick, P., ‘Fifty years using the wrong model of advertising’, International Journal of Market Research 50 (1) (2008), 29–59; Silverman, D.,

26. Bryman, A., Quantity and Quality in Social Research (London: Unwin Hyman, 1988). 27. Magee, B., Fontana Modern Masters – Popper (London: Fontana, 2010); St Aubyn, G., The Art of Argument (London: Christophers, 1956), 61–75. 28. Angrosino, M., Doing Ethnographic and Observational Research (London: Sage, 2007); Travers, M., Qualitative Research through Case Studies (London: Sage, 2001), 4. 29. Schensul, J.J., Designing and Conducting Ethnographic Research: An Introduction, 2nd edn (Lanham, MD: AltaMira Press, 2010); Fetterman, D.M., Ethnography: Step by Step (Thousand Oaks, CA: Sage, 1998), 1.

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30. Metcalf, P., A Borneo Journey into Death: Berawan Eschatology From its Rituals (Kuala Lumpur: Abdul Majeed, 1991). 31. Silverman, D., Interpreting Qualitative Data: Methods for Analysing Talk, Text and Interaction, 2nd edn (London: Sage, 2001), 45. 32. Gnädig, A. and Schieleit, O., ‘The death of depth: Skimming the surface’, Research World (January 2006), 44–5. 33. Stewart, A., The Ethnographer’s Method (Thousand Oaks, CA: Sage, 1998), 5. 34. Mariampolski, H., ‘The power of ethnography’, Journal of the Market Research Society 41 (1) (January 1999), 79. 35. Bilgram, V., Bartl, M. and Biel, S., ‘Successful consumer co-creation: The case of Nivea Body Care’, Market Research Society, Annual Conference (2010). 36. Kozinets, R.V., ‘Click to connect: Netnography and tribal advertising’, Journal of Advertising Research 46 (3) (2006) 279–88. 37. Poynter, R., ‘A taxonomy of new MR’, Market Research Society, Annual Conference (2010). 38. http://johnbell.typepad.com/weblog/2006/09/3_ways_ lego_lea.html, accessed 8 February 2011. 39. Anon., ‘Co-creation’, WARC Exclusive (November 2010). 40. Mariampolski, H., ‘The power of ethnography’, Journal of the Market Research Society 41 (1) (January 1999), 82. 41. Ibid., p. 81. 42. Mariampolski, H., Qualitative Marketing Research: A Comprehensive Guide (Thousand Oaks, CA: Sage, 2001), 52. 43. Wiesenfeld, D., Bush, K. and Sikdar, R., ‘The value of listening: Heeding the call of the snuggie’, Journal of Advertising Research 50 (1) (2010), 16–20. 44. Rappaport, S.D., ‘Putting listening to work: The essentials of listening’, Journal of Advertising Research 50 (1) (2010), 30–41. 45. Glaser, B. and Strauss, A., The Discovery of Grounded Theory (Chicago: Aldine, 1967). 46. Blumer, H., ‘Sociological analysis and the variable’, in Blumer, H., Symbolic Interactionism: Perspective and Method (Berkeley, CA: University of California Press, 1969), 127–39. 47. Travers, M., Qualitative Research Through Case Studies (London: Sage, 2001). 48. Glaser, B. and Strauss, A., The Discovery of Grounded Theory (Chicago: Aldine, 1967), 3. 49. Strauss, A., Fagerhaugh, S., Suczek, B. and Wiener, C., The Social Organisation of Medical Work (Chicago: University of Chicago Press, 1985). 50. Locke, K., Grounded Theory in Management Research (London: Sage, 2001), 33.

51. Ibid., p. 34. 52. This outline summarises a quite detailed procedure. For a definitive practical guideline to performing grounded theory see Corbin, J. and Strauss, A., Basics of Qualitative Research: Techniques and Procedures for Developing Grounded Theory (Thousand Oaks, CA: Sage, 2008); Goulding, C., Grounded Theory: A Practical Guide for Management, Business and Market Researchers (London: Sage, 2002); Strauss, A. and Corbin, J.M., Basics of Qualitative Research: Techniques and Procedures for Developing Grounded Theory, 2nd edn (London: Sage, 1998). 53. Nyilasy, G. and Reid, L.N., ‘Agency practitioners’ meta-theories of advertising’, International Journal of Advertising 28 (4) (2009), 639–68. 54. Strauss, A. and Corbin, J.M., Basics of Qualitative Research: Techniques and Procedures for Developing Grounded Theory, 2nd edn (London: Sage, 1998), 53. 55. Bresler, L., ‘Ethical issues in qualitative research methodology’, Bulletin of the Council for Research in Music Education 126 (1995), 29–41; Cheek, J., ‘Taking a view: Qualitative research as representation’, Qualitative Health Research 6 (1996), 492–505. 56. Strauss, A. and Corbin, J.M., Basics of Qualitative Research: Techniques and Procedures for Developing Grounded Theory, 2nd edn (London: Sage, 1998), 46–7. 57. Sandelowski, M., ‘Theory unmasked: The uses and guises of theory in qualitative research’, Research in Nursing and Health 16 (1993), 213–18. 58. Greenwood, D.J. and Levin, M., Introduction to Action Research: Social Research for Social Change (Thousand Oaks, CA: Sage, 1998), 17. 59. Lewin, K., ‘Forces behind food habits and methods of change’, Bulletin of the National Research Council 108 (1943), 35–65. 60. Tripe – the first and second divisions of cow stomachs, but could also be sheep or goat. 61. Greenwood, D.J. and Levin, M., Introduction to Action Research: Social Research for Social Change (Thousand Oaks, CA: Sage, 1998), 19. 62. Reason, P. and Bradbury, H., Handbook of Action Research (London: Sage, 2002), xxiv. 63. Greenwood, D.J. and Levin, M., Introduction to Action Research: Social Research for Social Change (Thousand Oaks, CA: Sage, 1998), 4. 64. Bate, S.P., ‘Changing the culture of a hospital: From hierarchy to network’, Public Administration 78 (3) (2000), 487. 65. Dörflinger, T., Gutknecht, S., Klär, K. and Tabino, O., ‘Digital divorce or digital love affair – understanding consumer needs by breaking down frontiers’, ESOMAR Annual Congress, Montreal (September 2008).

7 Stage 1

Problem definition

Stage 2 Research approach developed

Stage 3 Research design developed

Stage 4 Fieldwork or data collection

Stage 5 Data integrity and analysis

Stage 6 Communicating research findings

Qualitative research: focus group discussions The best moderators of focus groups are those that create aspirit of spontaneity and a passion for the issues under discussion.

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Objectives After reading this chapter, you should be able to: 1 understand why the focus group is defined as a direct qualitative research technique; 2 describe focus groups in detail, with an emphasis on planning and conducting focus groups; 3 evaluate the advantages and disadvantages of focus groups; 4 understand the myths that are associated with the application of focus groups; 5 describe alternative ways of conducting qualitative research in group settings; 6 understand the differences between online and traditional focus groups.

Overview In this chapter, we start by presenting a means of classifying qualitative research techniques and we examine the implications of such classification. The characteristics of the focus group are presented, along with their advantages and disadvantages. The manner in which focus groups should be planned and conducted is then presented. Running successful focus groups depends upon the skills of a moderator, i.e. the person who manages the group, and the ensuing discussion. We present the qualities needed in moderators to get the most out of focus group discussions. There are variations on the main theme of running a focus group; these are described, as well as other qualitative group activities. Some of the misconceptions of focus groups are examined, with a reminder of the qualities that make group techniques work well. In Chapter 6 we contrasted the purpose and different ways of running focus groups in the USA and in Europe; this contrast is developed and illustrated further in examining international marketing research issues. The relative advantages and disadvantages of running online focus groups is compared with ‘offline’ or face-to-face groups. We also evaluate many new group-based techniques that are emerging through social media research. The following examples illustrate how using focus groups helps researchers and decision makers to understand the issues faced by consumers. The three examples represent major variations of the focus group in terms of a traditional focus group, an online focus group and an online bulletin board. In all the examples, the issues being researched are expressed in consumers’ own words and sometimes in ways that words cannot convey. The examples also illustrate that researchers and decision makers may think that they know of all the issues they should be questioning, but once an exploration starts, participants can reveal new issues that they perceive to be of more importance, and these issues can drive very innovative marketing decisions.

Real research

Chinese views of chicken tastes1 How is it possible to encapsulate flavour experiences and enable improved flavour innovations for Chinese consumers? The producer of flavours and fragrances, Givaudan (www. givaudan.com), sponsored a study that was executed by Labbrand (www.labbrand.com). Out of the five senses, taste may be considered the most abstract, and therefore the most difficult to describe. In China there was a huge amount of information that could be considered in flavour creation for roast chicken. There were more than 30 variations of cooking methods for chicken, the most famous being ‘roast’ and ‘fry’, and with very specific flavour characteristics such as the ‘Gong Bao Ji Ding’ or the ‘Beggar’s Chicken’. Before discussing flavours with consumers, preliminary research was conducted on the variety of dishes, flavours and brands in order to understand cultural references. This research

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helped in the planning of focus groups directed at Chinese consumers to understand their flavour experiences. From the discussions of over 12 groups held in different Chinese cities, three categorical distinctions were apparent when a food experience was described: emotions and sensations – ‘generous’ or ‘smoky’ (general and conceptual, not linked to a specific context); practical experience – ‘at McDonald’s’, ‘with friends’ or ‘at a picnic’ (when, where, with whom, how); and rules, etiquette and common beliefs – ‘eating the bones clean makes me feel I am full’ or ‘white meat with friends can be embarrassing because it can get stuck between the teeth’. One issue faced when conducting research on taste experience, expectations and needs was that participants mixed these three dimensions of discourse. An additional complexity was that flavour experience is multidimensional. To describe a certain flavour, the participant may give a description in terms of taste (sweet, sour, bitter, salty and savoury – the basic tastes) and in terms of smell (fresh, burned, smoked, fruity) and/or texture. Because describing flavours was so complex, the role and expertise of the focus group moderator was crucial. The group setting was also crucial, so that participants could build on each other’s responses to arrive at more complete descriptions.

Real research

How does Philips execute its online bulletin boards?2 Online bulletin boards at Philips have used several studies at critical time points in the corporate strategic planning process. Initial studies differed in their particular aims, and in the sub-audiences targeted, but they generally took the following form. For a reasonable fee, senior influencers including executives, journalists, senior physicians, senior hospital administrators, urban planners and lighting designers agreed to join an online discussion. They logged on at their own convenience for a minimum specified number of minutes per day, over a period of two or three days. Three separate influencer panels were recruited to participate in a series of six one- or two-day online bulletin board sessions. Individuals were not always able to participate in all six sessions, but on average at least 75% participated each time. (Rare) panel dropouts were replaced with new members. Logging in and out whenever convenient to them, panel members interacted across multiple time zones and/or countries that shared a common language. Since Philips is a global company with worldwide reach, influencers were recognised across a wide range of geographies. Allowing senior individuals to interact with their transatlantic peers was engaging for participants, as well as valuable in yielding cross-cultural insight. The issue of audience heterogeneity was addressed by running several online bulletin boards concurrently, with the different sub-audiences each interacting at peer group level while discussing a mixture of topics – some that were common across all audiences and others that were specific to the sub-audience concerned. The flexible format enabled ongoing discussion guide development throughout a given fielding period, and incorporated a wide variety of visual aids and modes of enquiry. The studies for Philips included pre-seeded discussion, questionnaire rating scales and evaluation of print ads, multimedia clips and websites in development.

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Classifying qualitative research techniques A classification of qualitative research techniques is presented in Figure 7.1.

Figure 7.1

Qualitative research procedures

A classification of qualitative research techniques Direct (non-disguised)

Group interviews

Direct approach A type of qualitative research in which the purposes of the project are disclosed to the participant, or are obvious given the nature of the interview.

Indirect approach A type of qualitative research in which the purposes of the project are disguised from the participants.

In-depth interviews

Indirect (disguised)

Observation techniques

Projective techniques

These techniques are classified as either direct or indirect, based on whether the true purpose of the project is known to the participants. A direct approach is not disguised. The purpose of the project is disclosed to the participants or is otherwise obvious to them from the questions asked. Focus groups and in-depth interviews are the major direct techniques. Even though the purpose of the project is disclosed, the extent to which the purpose of the research is revealed at the start of a focus group or in-depth group may vary. Suppose that the researcher wanted to understand how participants felt about the Prada brand, what their views were of Prada advertising campaigns, the style and quality of Prada clothes, how ‘cool’ the brand was, the importance of its being an Italian company – to name but a few issues that could be tackled. Rather than stating these objectives, or even that the study was for Prada right at the start, the researcher may initially hide these issues. If revealed at the start, participants might focus straight onto these issues and not the surrounding contextual issues that may reveal the ‘relative’ impact of the Prada brand. Thus the researcher may initially reveal that the discussion is going to be about ‘what clothes mean to you’. The researcher may explore what participants feel to be good and poor examples of clothing advertisements and why – what types of clothing and accessories do participants see as stylish, how important is it to wear stylish clothes, how important is it to wear ‘cool’ clothes – drawing out examples of brands to illustrate these views. Italy as a country could be explored in terms of characteristics of Italians, or Italian design and style. If participants bring up Prada in the discussion, the researcher can then focus upon specific questions about the brand, contrast it with other brands and clearly see which subjects generated positive or negative views of Prada. Participants may deduce that the study is being conducted for Prada as the discussion proceeds, which may be apparent by the end of the discussion, or the researcher may clarify this point and explain why it was not revealed at the beginning.3 In using focus groups or in-depth interviews, the researcher employs a direct approach but has control over how much ‘directness’ to reveal at the start of the discussion. The researcher must consider what ‘frame of mind’ participants should be in at the start of the discussion, as too narrow or set a focus at the start can impede the thought processes and creativity of the participants and the success of the discussion. In contrast, research that takes an indirect approach totally disguises the purpose of the project. In an indirect approach, the researcher wants participants to behave as naturally as possible without any impediment of research purposes. In observation or ethnographic techniques,

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consumers may be seen shopping, choosing products, using products and interacting with other people and objects, hopefully in a natural environment and a natural manner. The ‘participants’ may not know that they are being observed or, if they do and have agreed to be observed, may not really know why. The purpose of using projective techniques (presented in Chapter 8) is to discover underlying motivations, beliefs, attitudes or feelings regarding consumer behaviour. The techniques allow indirect questioning to enable participants to discover novel ways to think about and express their feelings, where direct questioning would fail. Figure 7.1 presents a useful way to remember which qualitative techniques tend towards directness and indirectness. Another way of thinking about these issues would be to visualise a continuum, with ‘totally direct’ at one extreme and ‘totally indirect’ at the other. Qualitative techniques may then be positioned on this continuum and the implications of that position addressed. The implications for the researcher are as follows: •

•

Ethical. What are the ethical issues concerning revealing what a study is about? Would participants get involved in the study if they knew what it was really about? Would participants feel cheated or abused by not being told the purpose or finding it out as they go along? Data richness. If participants know what a study is about, to what extent does this ‘close’ their minds or destroy their creativity? Qualitative techniques aim to draw out deeply held views, issues that may be difficult to conceive or express. Researchers need to be able to get participants in the right frame of mind to be able to elicit these rich data. To what extent does revealing the purpose of a study impede this process?

Researchers cannot resolve this issue by stating, for example, that ‘they will only use direct techniques’ to resolve the ethical issues. Successful focus groups and in-depth interviews can utilise certain observation techniques. As an example, consider recording a simple answer of ‘no’ to a question. This ‘no’ may be interpreted in different ways, depending upon facial expressions (‘was the participant smiling?’), the tone of the participant’s voice (‘was it sharp and direct?’), the participants’ posture and body language (‘were they hunched and hiding their faces?’), or their positioning and reactions to others around them (‘were they seeking support from others of the same view, by gestures directed towards those participants?’). The researcher can use and manipulate scenarios to observe participants as a means of interpreting the answers they give to questions. The same can be said of projective techniques, all of which can be used to great effect in focus groups and in-depth interviews.4 The researcher ultimately has to work out the extent of directness or indirectness of the chosen qualitative techniques and address the ethical and data richness issues before setting out the detail of how to administer the qualitative techniques. These issues may be unique in each investigation, depending upon the nature of participants being studied and the questions they face. In practice, the qualitative researcher may resolve the best means to administer a technique by experimenting and adapting; these issues are tackled later in this chapter.

Focus group discussion Focus group A discussion conducted by a trained moderator among a small group of participants in an unstructured and natural manner.

Moderator An individual who conducts a focus group interview, by setting the purpose of the interview, questioning, probing and handling the process of discussion.

A focus group is a discussion conducted by a trained moderator in a non-structured and natural manner with a small group of participants. A moderator leads and develops the discussion. The main purpose of focus groups is to gain insights by creating a forum where participants feel sufficiently comfortable and relaxed. In such a forum, it is hoped that participants can reflect and portray their feelings and behaviour, at their pace and using their language, means of expression and logic. It has been argued that the single most compelling purpose of the focus group is to bridge social and cultural differences between researchers and their target participants.5 The value of the technique and its role in bridging social and cultural differences lie in discovering unexpected findings, often obtained from a free- flowing discussion that is respectful and not condescending to participants. 6 Focus groups are the most frequently used qualitative marketing research procedure, accounting for 9% of

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all global marketing research expenditure in 2010.7 They are used extensively in new product development, advertising development and image studies. They are so popular that many marketing research practitioners consider this technique synonymous with qualitative research.8 Given their importance and popularity, we describe the salient characteristics of focus groups in detail.9

Characteristics The major characteristics of a focus group are summarised in Table 7.1. One of the main characteristics and key benefits lies in the amount of creative discussion and other activities that may be generated. Group members have the time to reflect upon the discussion and range of stimuli that may be presented to them. The stimuli may come from other group members and/or from the moderator. Using their intuition and imagination, group members can explain how they feel or behave, in words or other forms of expression that they are comfortable with and using logic that is meaningful to them. The key drawback lies in how intimidating the group scenario may be to certain individuals. Many individuals may be self-conscious in expressing their ideas, feeling they may be ridiculed by others, or they may be shy and unable to express themselves freely in a group. A focus group is generally made up of 6 to 10 members. Groups of fewer than six are unlikely to generate the momentum and group dynamics necessary for a successful session. Likewise, groups of more than 10 may be too crowded and may not be conducive to a cohesive and natural discussion.10 Large groups have a tendency to splinter into subgroups as group members compete to get their views across. Table 7.1

Characteristics of focus groups

Key benefit

Group members ‘feed’ off each other and creatively reveal ideas that the researcher may not have thought of or dared to tackle

Key drawback

Group members may feel intimidated or shy and may not reveal anything of significance

Group size

6–10

Group composition

Homogeneous, participants pre-screened by questionnaire or through known characteristics

Physical setting

Relaxed, informal atmosphere, ‘comfortable’ from the perspective of the participants

Stimulating discussion

Use of storyboards, mood boards, products, advertisements, films, music, websites, brochures

Time duration

1.5 to 6 hours

Recording

Use of audiocassettes, videotapes and notes from observations

Moderator

Observational, interpersonal and communication skills

A focus group generally should be homogeneous in terms of demographic and socioeconomic characteristics. Commonality among group members avoids interactions and conflicts among group members on side issues. 11 An amount of conflict may draw out issues or get participants to rationalise and defend their views in a number of ways; it can also mean that the discussion does not get stale with everybody agreeing with each other and setting a scenario where genuine disagreement gets stifled. However, major conflicts should and can be avoided by the careful selection of participants. Thus, for many topics, a

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women’s group should not combine married homemakers with small children, young unmarried working women and elderly divorced or widowed women, because their lifestyles may be substantially different. Participants should be carefully screened to meet stated criteria. These criteria are set by the researcher to ensure that participants have had adequate experience with the object or issue being discussed. The most fundamental basis screening of participants is through demographic classification. Common demographic characteristics for determining group composition are: gender, race or ethnicity, age, household location, education level, occupation, income and marital status or family composition. Selecting participants using these characteristics can help increase compatibility but does not guarantee it; their backgrounds should be carefully balanced with their experiences.12 Participants who have already taken part in numerous focus groups should not be included. These so-called ‘professional’ participants are atypical, and their participation leads to serious validity problems.13 The physical setting for the focus group is also important. A relaxed, informal atmosphere helps group members to forget they are being questioned and observed. What is meant by a relaxed, informal atmosphere may change depending upon the type of participant and the subject being tackled. Examples of what ‘relaxed and informal’ means can include the home of a friend within a particular community, a works canteen, a village hall, a room in a leisure centre, a meeting room in a hotel or a purpose-built discussion group room. The poor acoustics and hard seats of a works canteen may not seem relaxed and informal. To group participants, however, it may be the place where they are happy to talk and willing to open up to a moderator. An example of this could be using part of a furniture store to discuss issues around house decoration, furnishings and cleaning or maintaining the home. Such a setting may set a very strong frame of reference to start the focus group and provide lots of stimuli. This example does not mean that all research needs to be conducted in situ, but that the technique can be designed to allow the findings from the real and the research environments to inform the overall recommendations.14 Light refreshments should be served before the session and made available throughout; these become part of the context of relaxation. The nature of these refreshments largely depends upon how long the discussion lasts, the nature of tasks faced by the participants and the ethical viewpoint of the researcher. Although a focus group may last from one to six hours, a duration of one and a half to two hours is typical. When a focus group lasts up to six hours, participants may be performing a series of projective techniques such as building ‘mood boards’ or ‘role playing’. Participants can also be given additional stimuli to discuss, such as advertising storyboards and products (existing, new, competitors’) to handle and examine. A focus group that lasts for up to six hours will invariably require a break for a meal, but in all circumstances a flow of drinks and snacks should be made available – noting special dietary requirements such as vegan food and drinks. The lengthy period of discussion in a focus group is needed to establish rapport with the participants, to get them to relax and be in the right frame of mind and to explore in depth their beliefs, feelings, ideas, attitudes and insights regarding the topics of concern. Focus group discussions are invariably recorded, mostly using audiotape but often on video, for subsequent replay, transcription and analysis. Video recording has the advantage of capturing facial expressions and body movements, but it can increase the costs significantly. Frequently, where focus groups are conducted in purpose-built studios, decision makers as ‘clients’ observe the session from an adjacent room using a two-way mirror or through video transmission. However, the existence of the mirror can impact upon everyone’s perceptions of what is happening in the discussion. The idea of invisible and unknown people sitting on the other side of the glass can be daunting and inhibiting to participants. Who are they? Why are they there? What are they doing? What are they going to think of me? Participants may not divulge private thoughts, confess to indulgent practices or generally open up if they feel intimidated by the interview process.15 The ‘City Hunter and ‘Philips’ examples at the start of this chapter illustrated how clients or decision makers are able to observe and even

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Probing A motivational technique used when asking questions to induce the participants to enlarge on, clarify or explain their answers.

influence the development of group discussions. This issue will be developed in this chapter when we compare the relative advantages and disadvantages of face-to-face discussions and online focus groups. In the physical setting of the focus group, care must be taken with both audio and video recording of participants. A judgement must be made of how comfortable participants are with being recorded and what effects recorders have on how much they relax and honestly portray how they feel. Many moderators can give rich examples of how the most interesting points to emerge from a focus group occur when recorders are switched off at the end of the discussion. This happens when a group of participants have really become involved in the subject of discussion and have enjoyed talking to their fellow participants. Even when the moderator has finished the discussion, some participants carry on discussing the issues between themselves as they put their coats on, leave the room and even perhaps as they walk to their cars. Moderators can hear issues discussed in this informal manner that they wish had been tackled with the full group. The moderator plays a vital role in the success of a focus group. The moderator must establish rapport with the participants and keep the discussion flowing, including the p robing of participants to elicit insights. Typically, probing differs from questioning in that the probes and the nature of probing are more spontaneous, and involve comments such as:16 • • • • • • • •

Would you explain further? Can you give me an example of what you mean? Would you say more? Is there anything else? Please describe what you mean. I don’t understand. Tell me more about that. How does that work?

Sometimes the moderator may put a probe question to the whole group, such as: • • • •

Who else has something? What about the rest of you? I see people nodding their heads; tell me about it. We want to hear all the different points of view. Who else has something that might be a bit different?

It is seen as good practice to probe early in the discussion in order to communicate the importance of precision or a developed explanation, and to use probes sparingly in later discussion. In addition, the moderator may have a central role in the analysis and interpretation of the data. Therefore, the moderator should possess skill, experience, knowledge of the discussion topic and an understanding of the nature of group dynamics.

Advantages and disadvantages of focus groups Focus groups offer several advantages over other data-collection techniques. These may be summarised by the 10 Ss:17 1 Synergy. Putting a group of people together will produce a wider range of information, insight and ideas than will individual responses secured privately. 2 Snowballing. A bandwagon effect often operates in a group discussion in that one person’s comment triggers a chain reaction from the other participants. This process facilitates a very creative process where new ideas can be developed, justified and critically examined.

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3 Stimulation. Usually after a brief introductory period, the participants want to express their ideas and expose their feelings as the general level of excitement over the topic increases in the group. 4 Security. Because the participants’ feelings may be similar to those of other group members, they feel comfortable and are therefore willing to ‘open up’ and reveal thoughts where they may have been reluctant if they were on their own. 5 Spontaneity. Because participants are not required to answer specific questions, their responses can be spontaneous and unconventional and should therefore provide an accurate idea of their views. 6 Serendipity. Ideas are more likely to arise unexpectedly in a group than in an individual interview. There may be issues that the moderator had not thought of. The dynamics of the group can allow these issues to develop and be discussed. Group members, to great effect, may clearly and forcibly ask questions that the moderator may be reluctant to ask. 7 Specialisation. Because a number of participants are involved simultaneously, the use of a highly trained, but expensive, interviewer is justified. 8 Scientific scrutiny. The group discussion allows close scrutiny of the data-collection process in that observers can witness the session and it can be recorded for later analysis. Many individuals can be involved in the validation and interpretation of the collected data, and the whole process can be very transparent. 9 Structure. The group discussion allows for flexibility in the topics covered and the depth with which they are treated. The structure can match the logical structure of issues from the participants’ perspective as well as the language and expressions they are comfortable with. 10 Speed. Since a number of individuals are being interviewed at the same time, data collection and analysis can proceed relatively quickly. This advantage has become even more pronounced with the development of online focus groups. Disadvantages of focus groups may be summarised by the five Ms: 1 Misjudgement. Focus group results can be more easily misjudged than the results of other data-collection techniques. As a qualitative technique focus groups can evolve through a line of questioning and probing (as discussed in Chapter 6). The specific direction of questioning and the ultimate interpretation of findings can be susceptible to the bias of the moderator and other researchers working on a project. 2 Moderation. As well as being great fun to moderate, focus groups can be difficult to moderate. Much depends upon the ‘chemistry’ of the group in terms of how group members get on with each other and draw ideas and explanations from each other. Even moderators with many years of experience may not connect with particular groups of participants or topics and can get into difficulty with group members who disrupt the discussion. The quality of the results depends upon how well the discussion is managed and, ultimately, on the skills of the moderator. 3 Messiness. The unstructured nature of the responses makes coding, analysis and interpretation difficult in comparison with the far more structured approach of quantitative techniques. Focus group data tend to be messy and need either strong theoretical support or the discipline of a grounded theory approach to ensure that decision makers can rely upon the analyses and interpretations. 4 Misrepresentation. Focus group results concentrate on evaluating distinct target groups, describing them and contrasting them to other groups or types of participant. Trying to generalise to much wider groups, in the same manner as with a quantitative survey based on a representative sample, can be very misleading.

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5 Meeting. There are many problems in getting potential participants to agree to take part in a focus group discussion. Even when they have agreed to participate, there are problems in getting focus group participants together at the same time. Running online focus groups has helped to resolve these problems to a great extent and is one of the main factors in the growth of this approach. For some participants a ‘virtual meeting’ is still not a solution. An example is in conducting business research with managers as participants. Given the amount of travel and tight schedules that many managers have, getting them together at the same time is very difficult. With many managers reluctant to reveal their company’s behaviour and plans in front of other managers, one can see that the focus group may be very difficult to administer in getting managers to meet up and discuss issues.

Planning and conducting focus groups

Topic guide A list of topics, questions and probes that are used by a moderator to help manage a focus group discussion.

The procedure for planning and conducting focus groups is described in Figure 7.2. Planning begins with an examination of the marketing research problem(s) and objectives. In most instances, the problem has been defined by this stage, but it is vital to ensure that the whole process is founded upon a clear awareness of the gaps in the knowledge of marketing decision makers. Given the problem definition, the objectives of using focus groups should be clarified. There should be a clear understanding of what information can be elicited and what the limitations of the technique are. The next step is to develop a list of issues, or topic guide, that are to be tackled in the focus groups. This list may be a series of specific questions but is more likely to be a set

Figure 7.2 Clarify marketing research problem(s) and objectives

Planning and conducting focus groups

Clarify the role of focus groups in fulfilling those objectives

Specify the issues to be developed in the focus groups

Specify the types of target respondents to make up groups

Specify the location(s) in which to conduct the focus groups

Recruit group members

Run an experimental group

Conduct the focus groups

Analyse data and present findings

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of broad issues that can be developed into questions or probes as the focus group actually takes place. Specific questions may be of help to the moderator who feels that a consistent set of points needs to be presented to different groups in order to allow clear comparisons to be made. Specific questions also act as a ‘prop’ when the discussion is failing; indeed, some group participants may initially feel that their role is to react to specific questions. However, treating the whole discussion as a means to present set questions may stifle the creativity and spontaneity that are the hallmarks of successful focus groups. The moderator should open the discussion with a general introductory question to make participants comfortable with the subject and the purpose of the research. This question should encourage conversation and interaction among the participants. It should not be threatening and it may even question in the third person – i.e. not asking participants what they do or think, and as such it may not be critical to the analysis, though there can be much revealed at this point. The discussion moves on to one or two transition questions, which move the discussion towards the key questions and issues. Transition questions help participants to envision the topic in a broader scope. Through these questions, participants become more aware of their fellow participants. Transition questions can ask participants to go into more depth about their experiences and uses of a product, making the connection between the participant and the topic under investigation.18 The moderator can then move on to the key questions, developing specific questions, issues and probes that can advance as the moderator tunes into the dynamics of the group. There may be additional, new issues that develop and, indeed, issues that group members do not see as being appropriate, and these can be discussed. The emphasis should be upon an evolution and learning process rather than administering a consistent set of questions. The types of group members to take part in the discussions are then specified. From this specification, a questionnaire to screen potential participants is prepared. Typical information obtained from the questionnaire includes product familiarity and knowledge, usage behaviour, attitudes towards and participation in focus groups and standard demographic characteristics. With the types of participants specified, consideration must be taken of what would make them relaxed and comfortable, balanced in both a physical and psychological sense. Having decided on the location of the focus groups, the actual recruitment of group members progresses. This is one of the most difficult tasks, as potential group members may be sceptical of what may happen at the group, sometimes fearing that they are exposing themselves to a hard-sell campaign of time-share holidays or home improvements! If individuals have attended a focus group beforehand, the process of recruitment is easier, but getting the right types of participant together at the right place and time can prove difficult. With the screening questionnaire, recruitment may take place on a face-to-face basis through street interviews or through database details by phone or email. One traditional approach is to give the specification of group members to an individual in whose home the discussions are to take place. That individual then recruits participants who fit that specification from the local community. The advantage of this approach is the individual’s ability to persuade participants that the process is a bona fide research process and is going to be rewarding in many ways; ultimately the individual makes sure that potential participants actually attend. The big disadvantage is ensuring that those recruited match the screening questionnaire requirements. Whichever method of recruiting participants is used, even when individuals have said that they will participate in the group, a follow-up is necessary to remind and motivate group members. Group participants have to be rewarded for their attendance. Usually they enjoy the experience immensely once they are there, but that does not ensure that they attend in the first place. Attendance can be rewarded with cash, a donation to charity or a gift. The following example illustrates the difficulties involved in recruitment and a researcher’s creative solution to the problem.

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Real research

So how do you upstage a Ferrari owner?19 Researching a high-net worth, socially active audience is difficult at the best of times. The target can be opinionated, demanding, often resistant to research and almost impossible to reach. So, when we got the brief to conduct focus groups among Ferrari, Porsche, top Mercedes and other exotic sports-car owners, we were tempted to panic. We knew we could find them, but how could we persuade them to participate? We realised the one thing that would link our target, who were also defined as keen drivers, not just poseurs, was their love of cars and desire to know the latest news about new models (and to try them out if possible). That’s why we decided to offer the carrot of a drive around a race and proving track and the opportunity to meet the design and management team at our famous sports car maker. If anything might motivate people who clearly already had sufficient money to indulge a very expensive taste, it should be this package. It worked like a dream, and we had great success getting the right people to come and, more importantly, to participate.

Experimental group An initial focus group, run to test the setting of the interview, the opening question, the topic guide and the mix of participants that make up the group.

The first focus group to be run should be seen as an experimental group. All aspects of running the group should be evaluated. Were the group members relaxed and comfortable in the chosen location, i.e. did the context work as intended? How did they react to the audio recorder, video or two-way mirror, i.e. at what point did they seem to relax and forget that they were being recorded? What types of member interacted well or not, and what issues helped or hindered interaction? How did the introductory and transition questions work in opening up and developing the discussion? How did the topic guide work; were there issues missing or issues that individuals would not tackle? How comfortable was the moderator in handling the topics; did they have to interject to liven the discussion? How much did the moderator have to know about the subject to have credibility with the participants? With reflection on these issues, any necessary alterations can be made to the way that the remaining focus groups are administered. There may be very useful information that emerges from the experimental group that can be included in the main analysis. However, if the group does not work well, the information gleaned may be of little use, but the lessons learned are invaluable in running the remaining groups. Finally, the focus groups can be run. The question arises here of how many groups should be run. Beyond the first experimental group, the number of groups needed can vary. The extent to which comparisons are sought in analyses can determine how many groups are needed. Seeking comparisons means recruiting participants with different backgrounds or experiences. If there are a great variety of types of individual that make up a target market, then many homogeneous groups may be needed to reflect the variety of types, e.g. a group of 18–25-year-old single-male car owners compared with groups of women or groups of older males, married men or non-car owners. The definition of these distinct target groups to question is entirely bound by the nature of the research problem. A confounding factor in the definition of these groups is the extent to which different types of participant will mix together in a single group. In an experimental focus group that explored attitudes and behaviour related to sports activities in the English city of Bath, distinct target groups of participants did not work well together. Older participants who participated in more ‘gentle’ sports activities did not particularly appreciate, listen to or respect the views of younger participants. In addition, there was a gender split in that male participants showed very little respect for the views of female participants. The older male

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participants were particularly patronising to younger females. As a result it was decided to run groups that separated younger and older participants and males and females. This meant an increase in the total number of focus groups conducted, but also meant that the remaining focus groups worked well and that the views of distinct target groups were clearly presented. If target participants are geographically widespread, then many groups may be needed to represent this diversity. Focus groups may be needed to represent each country. Further analyses of two distinct target groups were also needed. Thus, a minimum of two groups per country, i.e. eight groups plus an experimental group, would be needed, which would be doubled if it were subsequently felt to be important to run exclusively male and female groups. Another factor to be considered in determining the number of focus groups to conduct relates to whether the researcher is using focus groups as part of a grounded theory approach. With such an approach (as described in Chapter 6, and further developed in Chapter 9), theoretical sampling is adopted whereby further examples or instances are sought that may contradict the nature of the emerging grounded theory. The complexity of the developing grounded theory and the extent to which the qualitative researcher makes sense of the issues being explored will ultimately determine the number of discussions needed. This can be contrasted to focus groups conducted from a positivist perspective, focusing upon generating an understanding of issues to be confirmed in a subsequent survey. In the latter scenario, the researcher may not need to continue to search for more contradictory perspectives. Whichever paradigm underpins the application of focus groups, resources permitting, one should conduct additional discussion groups until the moderator can anticipate what will be said. The last sentence is a reminder of the final factor determining the number of discussions – the time and money afforded by the client. In summary, the number of focus groups that should be conducted on a single subject depends on the following factors:

Mood board A collage created in a focus group setting. Focus group participants are asked to snip words and pictures from magazines that they see as representing the values a particular brand is perceived to have. In some circumstances, collages can also be made up from audio and videotapes.

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The extent to which comparisons between different types of participants are sought.

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The types of participant to be targeted and how well they interact in a discussion.

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The geographic spread of participants.

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The paradigm that underpins the planning, administration and analysis of the focus group.

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The time and budget available.

Another dimension of running the groups, beyond the actual number of groups, is the nature of stimuli that the moderator chooses to input. At certain times, examples of particular products or brands may be introduced for participants to examine, to taste, touch, smell or sample if the nature of the product permits. Advertising material such as brochures, posters or even video recordings of TV or cinema adverts can be shown and a response generated. One of the most frequently used forms of stimuli is the mood board. The ‘mood board’ is really the creation of a collage, though in some discussions, preprepared collages are given to participants.20 Focus group participants are given a pile of magazines and asked to snip words and pictures from them. The direction they are given is to select images and words that they think represent characteristics of a brand, a consumer type or lifestyle, or whatever issue the researcher wishes to be illustrated in this manner. The resultant collage can then be used to stimulate discussion and to help draw together ideas and connect them. Creative marketing decision makers in copywriting or advertisement development may develop many ideas directly from the collages or mood boards, as illustrated in the following examples.

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Real research

Y bother with insurance21 Suncorp (www.suncorp.com.au) wished to launch a new under-25 ‘Family Discount’ insurance offer. In order to make this work, Suncorp wanted to engage with parents and their children simultaneously. A team of young researchers was recruited to have frank discussions with the youth market. Suncorp wanted to know what their relationship with their parents was like. Suncorp wanted to see if there was any common ground between them and their parents it could use, and what issues it should avoid. Focus groups using mood board exercises produced surprising results: Generation Y were not ‘trapped’ at home, they ‘share’ with their parents, the more liberal of whom have no objection to boy/girlfriends staying over. Parties within reason. No curfews. It could be seen in their fashions: the boho chic of Gen Y girls was not too different from their baby boomer mothers’ youthful fashions. They talked of wardrobe sharing and recycling. The fundamental values of the two generations were far more aligned than the angry Generation X and their parents, or the baby boomers and their depression-era parents. While this understanding may seem fairly obvious to anyone actually living this situation, very little of this was obvious in marketers’ approaches to Generation Y.

Real research

Becoming a brand22 The Turkish white-goods company Arçelik (www.arcelik.com.tr) commissioned focus group research to ask consumers how they perceived Arçelik at present and how they would like to see the brand in the future. The findings were revealing. Some of the clipart visuals used by the consumers in their collages to depict Arçelik included: traditional family; a bit aged; military; Hamamizade Ishak Efendi (an historical music composer); old TV sets; managers in black and white photos; black and white photos of past Miss Turkey winners; the British Royal Family; an old lady with back pain; a wooden bridge; a classical painting; old shots from Turkish TV authority broadcasts and Turkish carpets. The same groups said they would like to see Arçelik in the future as: ‘smiling; smiling youngsters; young women; motor sports; cute babies; luxury cars; happy families; family values; portable shelves; astronauts and computers.’

The mood board has two main functions: 1 Reference point. The moderator can use the mood board to reflect upon the discussion, in which case issues can emerge that were not so apparent in the heat of a discussion. 2 Enabling device. The mood board gets participants to loosen up and talk more freely. The focus group is not to get participants to talk rationally but to display what ‘feels right’ to

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them. The collage can help to express feelings they may not be able to put into words, or enable those words to have more clarity. This can happen by questioning what is included in a mood board, as well as what is omitted.23 The mood board and the creation of collages can develop beyond two-dimensional images. Given the growth of social media, individuals have become far more adept at expressing their personalities, their likes and dislikes through music and videos. The growth and engagement with sources such as Facebook, YouTube and SecondLife demonstrates an array of ways that consumers wish to express themselves and the skills they have developed to form expressions.24 As a result, there are many examples of participants producing video and audio collages in both group and individual settings. The final stage in planning and conducting focus groups involves the analysis of data. (Chapter 9 discusses qualitative data analysis in more detail.) There are two essential points to note: 1 Evolving analysis. Focus groups can change and develop in terms of the issues discussed and the stimuli used to draw out views from participants. The changes are made as the moderator generates and develops new ideas as each focus group progresses. The moderator makes observations and notes to help as the discussion progresses, and also for when it is over. The moderator may also interact with the client as the discussion progresses and/or when individual groups are completed. These observations and notes are part of the total analysis in that they decide which issues to probe, which issues to drop and the form of summarising issues that may be presented to groups at certain stages of the discussion. 2 Not just the narrative. If the discussion is recorded then transcripts can be produced, which can be analysed with proprietary software. These transcripts form a major part of the analysis procedure but the accumulation and reflection upon observations and notes forms a key part of the analysis.

The moderator Throughout this chapter we have referred to the moderator as an individual who conducts a focus group discussion, by setting the purpose of the discussion, questioning, probing and handling the process of discussion. This individual may also be the researcher handling the project. More likely it will be someone who specialises in the technique, or, given the number of groups to run and the time allowed to complete them, a number of specialist moderators will be employed. Whoever is to undertake the task of ‘moderating’ will require the following qualities:25 •

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Kindness with firmness. The moderator must quickly develop an empathy with group members. From this the moderator should show kindness to make participants feel welcome, combined with a firmness to stop particular individuals taking over the discussion. Permissiveness. The moderator must be permissive, allowing the flow of discussion to develop as the group sees fit. However, the moderator must be alert to signs that the group’s cordiality or purpose is disintegrating. Involvement. The moderator must encourage and stimulate intense personal involvement. In certain circumstances, this may mean becoming involved in the actual discussion itself. This can happen if a tendency for ‘group speak’ emerges. ‘Group speak’ happens when little debate or creativity in ideas develops, as particular individuals may not wish to be seen as going against a perceived group norm. Incomplete understanding. The moderator must encourage participants to be more specific about generalised comments by exhibiting a feigned naïvety or incomplete understanding.

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• •

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Encouragement. The moderator must encourage unresponsive members to participate. Flexibility. The moderator must be able to improvise and alter the planned outline amid the distractions of the group process. Sensitivity. The moderator must be sensitive enough to guide the group discussion at an intellectual as well as emotional level. The moderator must also be attuned to mood changes and issues that fire up enthusiastic responses or, conversely, cause the discussion to dry up. Sensitivity can also encompass the subtle nuances in the manner that they are viewed by participants, e.g. their dress, speech and manner, language and forms of expression used by participants and cultural references and context of these references as expressed in the discussion. Observation. As the group progresses, notes must be made of ideas or questions to come back to, interpretations of particular silences or bouts of laughter, and how group members are interacting with each other. These observations help the group discussion to progress well and the interpretation of the discussion to have greater meaning.

Other variations of focus groups Many developments have occurred in the format of group discussions. An illustration of one development was set out in the Philips example at the start of the chapter in the use of online bulletin boards for group discussions. As with the Philips example, most developments have been facilitated by the growth of online technologies and will be discussed later in the context of social media (Chapter 17) and mobile research (Chapter 18). However, in examining how moderators may adapt and change their role in order to engage and elicit more from participants, it is worth examining several variations of the standard focus group procedure. These include: •

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Two-way focus group. This allows one target group to listen to and learn from a related group. In one application, physicians viewed a focus group of arthritis patients discussing the treatment they desired. A focus group of these physicians was then held to determine their reactions. Dual-moderator group. This is a focus group discussion conducted by two moderators. One moderator is responsible for the smooth flow of the session, and the other ensures that specific issues are discussed. Duelling-moderator group. Here also there are two moderators, but they deliberately take opposite positions on the issues to be discussed. This allows the researcher to explore both sides of controversial issues. It also encourages participants who may support a particular perspective to express their views without fear that they will be ‘attacked’ by the rest of the group. Participant–moderator group. In this type of focus group, the moderator asks selected participants to play the role of moderator temporarily to improve group dynamics. Client–participant group. Client personnel are identified and made part of the discussion group. Their primary role is to offer clarifications that will make the group process more effective. Mini group. These groups consist of a moderator and only four or five participants. They are used when the issues of interest require more extensive probing than is possible in the standard group of 6–10. Telephone focus groups. These are conducted using a telephone conferencing system with the same number of participants as conventional focus groups, but typically within a narrower time frame, no more than an hour. These can work well in gaining access to widely dispersed experts in a range of professions or specialists. They would not be cost effective with ‘average’ consumers, except perhaps in cases where follow-up from survey participants is desired.26

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Other types of qualitative group discussions Brainstorming Traditional brainstorming has been used for several decades, especially in the context of management or marketing issues.27 Whether formal or informal, the process is the same: think of as many ideas as you can and say them out loud; leave the evaluation until later; build on and combine others’ ideas; be as imaginative as possible, the wilder the ideas the better. The group moderator seeks to nurture an atmosphere of creativity, tapping into the intuition of participants, generating novel ideas and connections between ideas. When it works well, ideas flow freely from an interplay that may never have occurred if the group had not brainstormed together. Two problems plague traditional brainstorming: production blocking and evaluation apprehension: •

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Production blocking. Occurs when a group member has an idea, but someone else is talking. When it is finally his or her turn they have forgotten the idea, or think it is redundant or not that good. If the group is large or dominated by talkative people, such members lose interest and do not say what they think. Evaluation apprehension. Occurs when participants become anxious about what others think of their thoughts. Ideas may be censored, as there is a fear of being labelled as odd. When participants feel this apprehension they do not produce as many new and potentially useful ideas but keep themselves to themselves, and therefore defeat the purpose of brainstorming.

As with traditional focus groups, online developments have generated a large variety of new approaches to brainstorming and generating ideas. These can include the use of research communities, Twitter and games.28 The following example illustrates a comparison of traditional versus online approaches to brainstorming.

Real research

BrainJuicer online brainstorming29 The research agency BrainJuicer (www.brainjuicer.com) has created a four-stage approach to online brainstorming: (1) identify ‘creative consumers’ via an online creativity test; (2) brief 50 creative consumers online to create 500 new ideas for a certain product/category and collect the new ideas digitally; (3) categorise the output, select the most promising 50 ideas from the total; (4) after this the client team focuses on what it is good at: harvesting, articulating sound and appealing concepts. Harvesting can be done in a joint workshop to create commitment to the ideas. Using this process BrainJuicer was asked to generate new-product ideas for Unilever Deodorants, both for men (e.g. Axe) and for women (e.g. Rexona). Halfway through the process it was decided to feed the ideas from the creative consumers into a brainstorming workshop and then invite some of them to participate in the workshop. After the workshop, a total of 40 ideas, 21 originally from Unilever resources (generated using traditional brainstorming techniques) and 19 originally from the BrainJuicer process, were selected by Unilever to be evaluated head to head in BrainJuicer’s screening tool, the Predictive Market™. The Predictive Market uses a large diverse crowd to decide on

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ideas with the most potential in the marketplace. Participants get virtual shares in all ideas tested. They need to maximise their own wealth by selecting one idea that they think will be a big failure in the market and one idea that they feel will be most successful in the market. For each idea, they assessed how often it had been selected ‘to sell’ and how often it had been selected ‘to double shares in’. Among the deodorant ideas for men, the two winning ideas were inspired by the BrainJuicer process. Five out of six ‘question marks’ (often polarising ideas with niche potential) were inspired by the process. From the Unilever Deodorant results it was clear that the traditional brainstorming approach was less successful in generating fresh potent ideas than the group of creative consumers working individually online.

Misconceptions about focus groups There has been much debate about the use and value of focus group discussions. Much of the debate has been misinformed through the development of myths and misconceptions built around the technique. Misconceptions about focus groups have emerged from assumptions made by researchers or the users of focus group findings, or even journalists. Their assumptions may have been useful at one time, in a particular context, or when tackling a certain subject. The assumptions may well apply to specific contexts but may not be applicable to focus groups in general. Working through the misconceptions can help researchers make decisions about when and how to use focus groups, and even whether they should be using them at all.30 The misconceptions about focus groups can be summarised by the five Es: 1 Economical – they are low cost and quick. The idea that focus groups are low cost and quick has emerged through comparison with other research methods. In comparison with survey research, focus groups (and especially online focus groups) may be conducted with a smaller budget and more quickly. This is not a fair comparison given the sample sizes that the techniques work with and the type of data they generate. In comparison with other qualitative methods, focus groups are often more expensive than observation and individual interviewing, primarily due to more expensive recruiting methods. The biggest resource involved in the technique, however, is that of the researcher in the careful planning, execution and analysis of focus groups. The analysis of the data generated can be ‘cheap and quick’ if it is a case of decision makers taking away their own conclusions from focus groups they have observed. Analysis can be far more expensive and time consuming if the careful planning and execution is followed up by the assembly of data, reflective diaries and memos and the full immersion into those data of the researcher (as detailed in Chapter 9). 2 Experts – they require professional moderators. The qualities of a good moderator were detailed above. A professional moderator, with experience of tackling different subjects, questioning and probing different types of participant and working in a variety of contexts, undoubtedly has much to offer any project. However, in many instances it is not the amount of experience that matters most in moderating. Sometimes a less-experienced moderator, who has more contact with the issues under question, more contact with the participants and is perhaps more comfortable in the interview location, can elicit better data. This is especially true when working with distinctive ethnic, linguistic or cultural groups. For example, an undergraduate student working on a project for a leading deodorant brand was about to enter the room to conduct a focus group. Looking at the 18–20 year olds before he entered the room, he realised that he was wearing the ‘wrong’ logo. With a quick change of his shirt, he continued with the discussion to great effect. Upon

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reflection, he revealed that the logo he was wearing, and indeed the colour of his sweatshirt, would have said things about him to the group that would have affected his credibility with the assembled participants. He felt that he would not have been able to engage with the group and get it to reveal so much had he been in his original clothing. His acute sensitivity to this cultural nuance made this focus group particularly effective; an older and more experienced moderator may not have picked this up. The best moderators are not necessarily those with the most experience. Rather it is the individual that can best engage with, listen to and draw out the best of target participants. 3 Easily upset – they do not work for sensitive topics. Focus groups are regularly used in projects related to sexual behaviour, substance abuse and stressful life events, which have marketing or other social implications. This misconception is based upon what may be deemed as socially acceptable in conversations, perhaps around the dinner table. However, focus groups present an atypical setting for discussion. The moderator is encouraging everyone in the group to share values and experiences that they all have an interest in. There may be little consequence to what they say, especially if they are meeting with strangers whom they may never meet again. Handled with caution, the moderator can encourage participants to reveal things they would normally keep to themselves. Researchers and moderators working with sensitive issues must make plans to encourage appropriate self-disclosures, and to cope with disclosures that go beyond the boundaries of the project. These plans go beyond the wording of the questions and probes into the atmosphere the researchers wish to create at the discussion, the nature of the location being particularly important here. 4 Endorsement – they must be validated by other research methods. This is part of the general misconception that all qualitative techniques play a preliminary role that prepares the way for a conclusive technique. Focus groups can serve a useful role as the first stage of developing questionnaires or experiments, but that is not their sole purpose. Focus groups can illuminate and indeed help to validate many of the statistical findings that emerge from surveys, e.g. helping to understand and describe findings from factor and cluster analyses. They can be used in isolation to produce the kind of in-depth understanding of an issue that no other technique can provide: for example, the use of a particular celebrity in an advertisement can generate a series of emotional responses that could impact upon the brand values – and those values are compounded by the particular use of music and who is playing that music. To uncover what is happening to the viewers and how their values may have changed, the focus group may well be the most efficient and effective technique, of all qualitative or quantitative options. 5 Exposure – they reveal how consumers will behave. Focus groups, in-depth interviews and surveys all depend upon verbal reporting. They depend upon a belief in what participants say about how they intend to behave. In many circumstances, even when it comes down to it, the most sincere participants can change their minds. In focus groups, participants may talk about their likely behaviour in many hypothetical scenarios, moderators can watch other participants nod their heads in agreement and the evidence is compelling. It must be recognised that the data generated are attitudinal, and trying to predict behaviour from attitudes is most problematic. The rise in customer databases and ethnographic methods has helped researchers to predict consumer behaviour and validate the findings of focus groups and surveys. The focus group, like every research technique, is never foolproof or perfect. To get the most from focus groups, the following thinking should be encouraged.31 First, the quality of moderating is crucial to the success of the discussion. The quality of the findings is directly related to the talents, preparation and attentiveness of the moderator. Second, teamwork is vital. As well as star moderators, there must be quality recruiters, note-takers, analysts and reporters. Third, this team has always something to learn from the participants. For a short period of time, the participants open their lives and share their experiences, preferences and

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beliefs. The most destructive thing a researcher can do in a focus group is to display arrogance, condescension or superiority. It is much better to sit back and let participants tell you everything you wanted to know, and more! Finally, there are many ways to conduct successful focus groups. Given the nature of the topic under investigation and the nature of the target participants, there are many options to choose for the best context and approach to draw out the best from participants. Focus groups vary enormously in how they are planned, administered and analysed, from the very structured interview in a studio bristling with technology, through to a passionate dialogue conducted globally online, to a riotous exchange on a tropical beach. Experimentation with new ways of conducting focus groups should be positively encouraged rather than being bound by the thought that there is one ideal way to conduct them.

Real research

Becoming a brand32 Young focus group participants are different creatures from adults, and this calls for some adaptations to the way researchers approach their work. Young people can be deeply self-conscious and lack confidence in revealing and articulating their views in front of others. A forum that seeks to source this information from them can therefore be an uncomfortable one. If they are involved in focus groups, it is like asking them to attend an event that can look like a school scenario. If it is not differentiated, this can result in an uncooperative or unmanageable group, as giggles take over and the moderator loses control. Generating comfort, and thus confidence, is crucial. It is worth adding a question to the recruitment screening about their possible ‘subcultural’ or ‘tribal’ leanings. With little else to use in self-definition, these visual distinctions can be allimportant. Sworn enemies on the local high street, emo/indie/goth kids and ‘townie’ or ‘hoodie’ youths do not make easy group partners. In a group setting, girls tend to open up and share together fairly quickly. Boys need more time because their group dynamics are based on clear-cut roles. It can be worth asking them to arrive 30 minutes early and leave them to play games together or complete a task before the group kicks off. This will give them time to form some sense of group structure. Alternatively, start the group with some smaller team tasks before bringing them back together to talk as a whole. Where possible, it is worth trying to work with young people’s existing friendship groups. As well as providing a young person with security and familiarity, it offers a much more authentic understanding of brand adoption behaviours. By working with a set of friends, it can be possible to see how deliberations and decisions are played out and negotiated. What brought them to group consensus? What, or who, was the all-important lever in that consideration process?

Online focus groups Throughout the chapter we have referred to and illustrated the use and value of online focus groups. The fundamental principles of why focus groups are conducted, their management and the data analysis challenges are similar between traditional offline focus groups and online focus groups, sometimes known as e-groups. Before examining their relative strengths and weaknesses it is worth considering a general description of online focus groups. As in the case of traditional focus groups, online focus group participation is by invitation only. The participants are pre-recruited and generally come from lists of individuals who have expressed an interest in particular products, services or issues. An example of such a list could be the use of access panels (detailed in Chapter 4), such as (www.researchnow.com).

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A screening questionnaire can be administered online to qualify participants, even if access panel members have already been profiled. Those who qualify are invited to participate in the online focus group and given clear benefits and a reward for their participation. They receive a time, a URL, a room name and a password via email. Before the focus group begins, participants receive information about the discussion that covers such things as how to express emotions when typing. Electronic emotion indicators are produced using keyboard characters and are standard in their use on the internet. Obvious examples include :-) and :-( for happy and sad faces. The emotions are usually inserted in the text at the point at which the emotion is felt. Emotions can also be expressed using a different font or colour. There are a wide range of emotions to choose from, expressed such as: I’m frowning, I’m laughing to myself, I’m embarrassed, I’m mad now, I’m responding passionately now. These are then followed by responses. Participants can also preview information about the discussion topic by visiting a given website and reading information, or downloading and viewing visuals such as TV advertisements. Then, just before the focus group begins, participants visit a website where they log on and get some last-minute instructions. When it is time for the discussion, participants move into a web-based chat room. In the chat room, the moderator and participants type to each other in real time. The general practice is for moderators always to pose their questions in capital letters and participants use upper and lower case. Participants are asked always to start their response with the question or issue number, so the moderator can quickly tie the response to the proper question. This makes it fast and easy to transcribe a discussion. A raw transcript is available as soon as the discussion is completed and a formatted transcript can be available within 48 hours (the form of data used depends upon whether the transcript is to be input into qualitative analysis software and is to be built up as the groups progress, and/or is to be read by the client). The whole process of conducting the discussions and uploading transcripts for analysis is much faster than in traditional focus groups. New forms of online focus groups continue to emerge. For example, online bulletin boards, such as the Philips example outlined at the start, involve the moderator and participants over an extended period of time, from a few days to a few weeks. Questions and challenges can be slowly fed out over time, allowing the researcher to reflect upon responses that have been received and adapt subsequent questions. Participants can reflect in more depth and respond at their own convenience. Participants may also be given tasks such as collecting and posting visuals and music or offering web links to illustrate ideas and issues. Such an approach can enable an in-depth discussion among 25 or more participants. The extended time period allows participants to react to and build upon each other’s ideas in a way that is often not possible during a traditional focus group that lasts even up to six hours. The following example illustrates a demonstration of how online focus groups could work for a design challenge faced by a bank. Of particular note is the value of input and observations made by the client – a topic discussed earlier in the chapter.

Real research

Online focus group vs. traditional focus group experiment33 A leading high-street bank set iCD Research (www.icd-research.com), nqual (www. nqual.com) and The ID Factor (www.theidfactor.com) a challenge: to demonstrate that an online focus group would match the findings from traditional qualitative research. The objectives of the project were centred on a new credit card proposition. To demonstrate the capabilities, a two-stage online focus group was proposed to be conducted at 8 p.m. on a Tuesday and Wednesday night. Utilising existing data within The iD Factor financial panel, participants were selected on their consideration to switch credit-card providers within the next 12 months. A recruitment email validated this consideration, with the invitation to attend the night sessions. This information, as well as a demographic

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and attitudinal profile of each participant, was sent to the client prior to the session. A main moderator was based in London and a secondary moderator, based in Australia, was also present. At 7.55 p.m., a total of nine participants were active within the session, with an additional 18 observers across five companies/subsidiaries and three continents watching. The approach adopted within ‘online focus group 1’ was consistent with an offline topic guide, but adopted techniques that could be integrated into focus groups without risking participant focus or the trust in the moderation. The structure of the session followed what might be considered a ‘traditional’ qualitative format, including evaluation of a proposition as well as the incorporation of participant-suggested improvements. The use of client observers and a second moderator allowed the client proposition to be adapted ‘live’ based on initial and user-generated comments and ‘built’ by the second moderator, uploaded into the session and evaluated. Client participation was crucial as it allowed participant-generated queries to be addressed and answered correctly, as well as assisting the moderator in steering the conversation in a way that could deliver against the set objectives. At 10 p.m. nqual delivered the discussion transcript to iCD Australia moderators. The Melbourne office was then able to take their observations, transcript and start the analysis process at 9 a.m. Australian EST. By 8 a.m. UK time the following morning, a summary report with proposition and stimulusrecommended changes was delivered to the UK team, who by 9 a.m. had delivered a report to the client and worked with the client to make changes for ‘online focus group2’. A fresh, but matched demographic and behavioural sample of participants was recruited for the second focus group. This followed a similar structure to ‘online focus group’ 1, with the revised stimulus and proposition. With the Australian office co-moderating and observing again, summary and analysis was again conducted overnight, which included quantitative recommendations. In response to this an online survey was launched on the Friday, completed by the Sunday and fed back on the Monday. The combined qualitative and quantitative project was commissioned, recruited and delivered within a seven-day period. When comparing the trial of focus groups with the previously commissioned research, the key themes, initial feedback and suggested user improvements were completely consistent for both approaches. Nevertheless, the client viewed the online approach more positively because it was faster, and was able to refine the proposition in real time and actively contribute to the session.

Advantages of online focus groups Participants from all over the country or even the world can take part, and with mobile technology advances they can physically be anywhere that they are comfortable. Likewise, the client or decision maker can observe and comment on the discussion from anywhere. Geographical constraints are removed and time constraints can be lessened. Unlike traditional groups, there is the opportunity to contact participants again at a later date, to revisit issues, or introduce them to modifications in material presented in the original focus group. The internet and the use of profiled consumers via access panels enable the researcher to reach segments that are usually hard to interview: doctors, lawyers, professionals, working mothers and others who are leading busy lives and not interested in taking part in traditional focus groups. Moderators may also be able to carry on side conversations with individual participants, probing deeper into interesting areas. Participants may be less inhibited in their responses and can be more likely to express their thoughts fully, especially if they have the facility to reflect and upload images, music or other forms of expression. Many online focus groups go well past their allotted time as so many responses are expressed as participants become

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engaged in the discussion. Finally, as there is no travel, video-recording or facilities to arrange, the cost is much lower than traditional groups. Firms are able to keep costs between one-fifth and one-half the cost of traditional groups.34

Disadvantages of online focus groups Only individuals who have access to and know how to use a computer (desktop or mobile) can participate in online groups. The global growth and access to computers means that internet access may seem ubiquitous, but there remain significant numbers that cannot, particularly among older age groups. Since the name of a participant is often private, actually verifying who the participant is and thus whether they fit a target profile is difficult. To overcome this limitation, other traditional methods such as telephone calls are used for the recruitment and verification of participants. This is an area where the use of a well-managed access panel can help in ensuring the profile of a participant is correct for a particular study. Body language, facial expressions, silences and the tone of voice cannot be observed and electronic emotions cannot capture as full a breadth of emotion as video-recording. Another factor that must be considered is the general lack of control over the participant’s environment and potential exposure to distracting external stimuli. Since online focus groups could potentially have participants scattered all over the world, researchers and moderators have no idea what else participants may be doing during the discussion. This has to be balanced against the comfort that may be felt by the participants in being able to conduct the discussion in a context where they feel comfortable. Only audio and visual stimuli can be tested. Products cannot be touched (e.g. clothing) or smelled (e.g. perfumes). It may be more difficult to get clients or decision makers involved in online groups than in observing traditional groups. It is hard to replicate the compelling views of consumers, expressing themselves in an uninhibited manner, on what they feel about a product or service. Table 7.2 presents a summary comparison of online and traditional focus groups.35

Table 7.2

Online versus traditional focus groups

Characteristic

Online focus groups

Traditional focus groups

Group size

4 to 8 participants

6 to 10 participants

Group composition

Anywhere in the world

Drawn from a targeted location

Time duration

1 to 1.5 hours – though can last over a week as participants are given tasks and come back to the discussion

1.5 to 6 hours

Physical setting

Researcher has little control – but the participants can be in a place that is comfortable to them, especially with the use of mobile technology

Under the control of the researcher

Participant identity

In some circumstances can be difficult to verify

Can be easily verified

Participant attentiveness

Participants can engage in other tasks – not seen by the moderator

Attentiveness can be monitored

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Table 7.2

Continued

Characteristic

Online focus groups

Traditional focus groups

Participant recruitment

Easier can be recruited online, by email, by access panel, or by traditional means

Recruited by traditional means (telephone, mail, mail panel)

Group dynamics

Limited

Synergistic, snowballing (bandwagon effect)

Openness of participants

Participants can be candid – may be more open with identities hidden to some extent

Participants can be candid as they build up trust of each other Difficult with sensitive topics

Non-verbal communication

Body language and facial expressions cannot be observed

Easy to observe body language and facial expressions

Some emotions can be expressed

Expression of emotions easier to monitor

Use of physical stimuli

Limited to those that can be displayed online – unless specific engagement tasks given to participants

A variety of stimuli (products, advertising, demonstrations) can be used

Transcripts

Available immediately

Time-consuming and expensive to obtain

Observers’ communication with moderator

Observers can communicate with the moderator on a split screen

Observers can send messages to the moderator from behind two-way mirrors

Unique moderator skills

Software familiarity, awareness of chat-room slang

Observational

Turnaround time

Can be set up and completed in a few days

Takes many days to organise, administer and analyse

Client travel costs

None

Can be expensive

Client involvement

Limited

High

Basic focus group cost

Much less expensive

More expensive due to facility rental, refreshments, video/audio taping and transcript preparation

Summary

In direct qualitative methods participants are able to discern the true purpose of the research, whereas indirect methods disguise the purpose of the research to some extent. Focus groups can be a completely direct qualitative method, though by the use of observational and projective techniques elements of indirectness can be introduced. In deciding how ‘direct’ a focus group should be, researchers have to face ethical issues and questions related to the richness of data that they can draw from participants. Focus group discussions are the most widely used qualitative research method. Focus groups are conducted by a moderator in a relaxed and informal manner with a small group of participants. The moderator leads and develops the discussion. In a focus group, participants can portray their feelings and behaviour, using their own

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language and logic. The value of the technique lies in the unexpected findings that emerge when participants are allowed to express what they really feel, especially as different sensory experiences are explored. An experimental focus group should always be run at the start of any series of discussions. The researcher needs to understand how comfortable target participants feel in the chosen location for discussion, how the opening question works, the topic guide, the probes, the mix of participants and the refreshments, including any alcoholic drinks. In a nutshell, one could argue that one should continue running focus groups until nothing new is learned from target participants. This perspective oversimplifies how diverse and spread out different participants may be and how well they mix together in a group situation. The time and budget available will also mean that a cut-off point has to be drawn and the strongest analysis and interpretation has to be made at that point. Online technical and technique developments have seen online focus emerge as a means to engage with geographically dispersed participants. Such engagement can be conducted in a speedier and cheaper manner than traditional focus groups. Traditional focus groups allow for richer observations of participants and more creative sensory experiences to be evaluated. There is no one absolute correct method to administer a focus group; the researchers should understand the factors that will make the technique work for their particular research problem and the type of participants they have to work with. Researchers face challenges in planning, administrating and analysing focus groups when set in international contexts. It is vital that researchers do not impose their norms of running focus groups in different cultures but learn from indigenous researchers. This learning is vital in making cross-cultural comparisons. A key element of ensuring that the focus group works well lies in the ethical issues of how much is revealed to participants before they get involved, and during the discussion. Getting participants to relax and be open may involve the use of alcoholic drinks, which for many researchers creates no problems but for some creates ethical and practical issues. With the growth of online focus groups, the ethical challenge of understanding who is actually engaged in a discussion is paramount. This is particularly relevant in researching children, where ESOMAR guidelines have to keep up with emerging technologies and practices. Social media developments have resulted in the emergence and growth of Marketing Research Online Communities (MROCs). These communities are being adopted by many brands to engage with their existing and potential customers. Online focus groups can be conducted in the context of MROCs, but the development of communities as a potentially richer and cheaper data source will impact upon decision makers’ views of the use and value of focus groups.

Questions

1 Why may researchers not wish to fully reveal the purpose of a focus group discussion with participants before it starts? 2 What are the key benefits and drawbacks of conducting focus group discussions? 3 What are the difficulties in conducting focus groups with managers or professionals? 4 What determines the questions, issues and probes used in a focus group?

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5 Evaluate the purpose of running an experimental focus group discussion. 6 What does a ‘comfortable setting’ mean in the context of running a focus group? 7 To what extent can a moderator achieve an ‘objective detachment’ from a focus group discussion? 8 Why is the focus group moderator so important to the success of a focus group discussion? 9 What are the relative advantages and disadvantages of being able to observe covertly a focus group discussion? 10 What can the researcher do to make potential participants want to take part in a focus group? 11 What determines the number of focus groups that should be undertaken in any research project? 12 Describe the purpose and benefits of using stimulus material in a focus group. 13 What is an online focus group? What are the distinct advantages and disadvantages of running online compared with traditional focus groups? 14 Describe the opportunities and difficulties that may occur if alcoholic drinks are served during focus group discussions. 15 What is a Marketing Research Online Community (MROC)? How can an MROC be viewed as a group-based qualitative research technique?

Exercises

1 Following the methods outlined in this chapter, develop a plan for conducting a focus group study to determine consumers’ attitudes towards organic foods. Specify the objectives for the groups, write a screening questionnaire, list potential props or physical stimuli that you could use in the discussion and develop a moderator’s outline. 2 Your campus sports centre is trying to recruit more members from the local non-student community. In achieving this aim, evaluate the marketing decisions that could be supported by focus groups, either as a technique in its own right or as validated with other techniques. 3 You are a brand manager for Red Bull energy drinks. You wish to invest in an online focus group study of energy-drink buyers. Explain how you would identify and recruit such participants from across the globe. What incentive(s) would you offer potential participants? 4 Visit the website of the Association of Qualitative Research Practitioners (www. aqr.org.uk). Examine the reports and views of contributing practitioners (look in the news and inspiration section) and write a report on what you feel are the latest developments and/or opportunities in the use of focus groups. 5 In a small group discuss the following issues: ‘The dress, appearance and speech of the moderator create biases in group discussions that cannot be evaluated’ and ‘Mood boards created in focus groups are more useful to marketing decision makers compared with a formal written analysis of the discussions’.

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Notes 1. Djurovic, V. and Depeux, V., ‘Semiotics of taste: Application in China for international (and local) food and flavor industries’, ESOMAR Qualitative, Barcelona (November 2010). 2. Mesure, P., McGouran, O. and Feehan, M., ‘Using online bulletin boards to develop high value corporate strategy’, ESOMAR Congress Odyssey, Athens (September 2010). 3. To understand more of how a luxury brand may be researched using qualitative techniques, see Healy, M.J., Beverland, H.O. and Sands, S., ‘Understanding retail experiences – the case for ethnography’, International Journal of Market Research 49 (6) (2007), 751–78. 4. For an excellent discussion on the problems of interpreting ‘silence’ in interviews, see Prasad, S., ‘Listening to the sounds of silence’, ESOMAR Asia Pacific, Kuala Lumpur (April 2010). 5. Ewing, T., ‘Confessions of a moderator: How web communities fail and how marketers can stop that happening’, Market Research Society: Annual Conference (2008); Morgan, D.L., ‘Focus group interviewing’, in Gubrium, J.F. and Holstein, J.A. (eds), Handbook of Interview Research: Context and Method (Thousand Oaks, CA: Sage, 2002), 141–59. 6. Morrison, D.E., ‘Focus group research: A misunderstood history’, ESOMAR Qualitative Research, Venice (November 2003); Morgan, D.L. and Krueger, R.A., ‘When to use focus groups and why’, in Morgan, D.L. (ed.), Successful Focus Groups: Advancing the State of the Art (Newbury Park, CA: Sage, 1993), 3–19. 7. ESOMAR, ‘Global Market Research’, ESOMAR Industry Report (2010), 16. 8. Bloor, M., Frankland, J., Thomas, M. and Robson, K., Focus Groups in Social Research (Thousand Oaks, CA: Sage, 2001). 9. Kreuger, R.A. and Casey, M.A., Focus Groups: A Practical Guide for Applied Research, 3rd edn (Thousand Oaks, CA: Sage, 2000); Drayton, J. and Tynan, C., ‘Conducting focus groups – a guide for first-time users’, Marketing Intelligence and Planning 6 (1) (1988), 5–9. 10. For more discussion, see Dexter, A. and Ngoc Hieu An, B., ‘From Bricolage to Pho – Vietnam as a model for global influences and assimilations at meal times’, ESOMAR Asia Pacific, Beijing (April 2009); Andrews, M. and Langmaid, R., ‘Theory and practice in the large group’, Market Research Society, Annual Conference (2003); Morgan, D.L., Planning Focus Groups (Thousand Oaks, CA: Sage, 1998), 71–6. 11. Forrest, C., ‘Research with a laugh track’, Marketing News 36 (5) (4 March 2002), 48; Mazella, G.F., ‘Show-and-tell focus groups reveal core bloomer values’, Marketing News 31 (12) (9 June 1997), H8. 12. Morgan, D.L., Planning Focus Groups (Thousand Oaks, CA: Sage, 1998), 71–6. 13. MacDougall, C., ‘Planning and recruiting the sample for focus groups and in-depth interviews’, Qualitative Health Research 11 (1) (January 2001), 117–26; Kahn, H., ‘A professional opinion’, American Demographics (Tools Supplement) (October 1996), 14–19. 14. Gordon, W., ‘New life for group discussions’, ResearchPlus (July 1993), 1.

15. Baskin, M., ‘Observing groups’, WARC Best Practice (November 2010). 16. McPhee, N., ‘Is there a future for “real” qualitative market research interviewing in the digital age?’, ESOMAR Congress Odyssey, Athens (September 2010); Krueger, R.A., Moderating Focus Groups (Thousand Oaks, CA: Sage, 1998), 30. 17. Stokes, D. and Bergin, R., ‘Methodology or “methodolatry”? An evaluation of focus groups and depth interviews’, Qualitative Market Research: An International Journal 9 (1) (2006), 26–37; Goldsmith, R.E., ‘The focus group research handbook’, The Services Industries Journal 20 (3) (July 2000), 214–15; Greenbaum, T.L., The Handbook for Focus Group Research (Newbury Park, CA: Sage, 1997). 18. Krueger, R.A., Developing Questions for Focus Groups (Thousand Oaks, CA: Sage, 1998), 25. 19. Ellis, R., ‘So how do you upstage a Ferrari owner?’, ResearchPlus (November 1994), 10. 20. Toiati, L., ‘How do you call collages in Asia?’, ESOMAR Asia Pacific Conference, Singapore (December 2002), 1–20. 21. Jowell, C. and Barber, A., ‘Suncorp – “Family Discount” campaign: Y bother with insurance?’, Account Planning Group (Australia), Finalist, Creative Planning Awards (2006). 22. Vardar, N., ‘Arçelik: From “a passion for manufacturing” towards “becoming a brand”’, Turkish Foundation of Advertising: ‘Turk Markalari-2’, Turkish Foundation of Advertising Publications (2008). 23. Croft, M., ‘Art of the matter’, Marketing Week (9 October 1997), 71. 24. Jalboukh, T. and Chaudhry, A., ‘Reality YOUTH research – the Arabian YOU (TH) Tube!’, ESOMAR Consumer Insights, Dubai (February 2009). 25. Sharma, A. and Pugh, G., ‘Serpents with tails in their mouths: a reflexive look at qualitative research’, ESOMAR Qualitative Research, Paris (November 2007); Katcher, B.L., ‘Getting answers from the focus group’, Folio: The Magazine for Magazine Management (Special Sourcebook Issue for 1997 Supplement) 25 (18) (1997), 222; and an adaptation from Chase, D.A., ‘The intensive group interviewing in marketing’, MRA Viewpoints (1973). 26. Mariampolski, H., Qualitative Marketing Research: A Comprehensive Guide (Thousand Oaks, CA: Sage, 2001), 47. 27. Gallupe, R.B. and Cooper, W.H., ‘Brainstorming electronically’, Sloan Management Review 35 (1) (Fall 1993), 27. 28. Cierpicki, S., Davis, C., Eddy, C., Lorch, J., Phillips, K., Poynter, R., York, S. and Zuo, B., ‘From clipboards to online research communities: A cross-cultural review of respondents’ perceptions’, ESOMAR Congress Odyssey, Athens (September 2010); Poynter, R., Vieira, S., Alexander-Head, D., Coulter, A., Zuo, B. and Gao, A., ‘Will Twitter change the way that market researchers communicate?’, ESOMAR Asia Pacific, Kuala Lumpur (April 2010); Verbrugge, J., Geels, A., Verbiest, S. and Fletcher, A., ‘Gaming 0.0 – a research game as an innovative “offline” research tool’, ESOMAR Congress, Montreux (September 2009).

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29. Johnston, C., ‘Getting over the courtesy bias’, Research World (July 2007), 29. 30. McCracken, G. and Morgan, D.L., The Long Interview + Focus Groups as Qualitative Research (Thousand Oaks, CA: Sage, 2009). 31. Morgan, D.L., The Focus Group Guidebook (Thousand Oaks, CA: Sage, 1998), 52–4. 32. Macdonald, N., ‘Unlocking response from young people’, Admap 504 (April 2009), 12–13. 33. Hamilton, J. and Dixon, P., ‘Real-time global research – a qual revolution’, Market Research Society: Annual Conference (2009). 34. Reid, D.J. and Reid, F.J., ‘Online focus groups’, International Journal of Market Research 47 (2) (2005),

131–62; O’Connor, H. and Madge, C., ‘Focus groups in cyberspace: Using the internet for qualitative research’, Qualitative Market Research 6 (2) (2003), 133–43; Kozinets, R.V., ‘The field behind the screen: Using netnography for marketing research online communities’, Journal of Marketing Research 39 (1) (February 2002), 61–72. 35. Cheng, C.C., Krumwiede, D. and Sheu, C., ‘Online audio group discussions: A comparison with face-to-face methods’, International Journal of Market Research 51 (2) (2009), 219–41; Brüggen, E. and Willems, P., ‘A critical comparison of offline focus groups, online focus groups and e-Delphi’, International Journal of Market Research 51 (3) (2009), 363–81.

8 Stage 1

Problem definition

Stage 2 Research approach developed

Stage 3 Research design developed

Stage 4 Fieldwork or data collection

Stage 5 Data integrity and analysis

Stage 6 Communicating research findings

Qualitative research: in-depth interviewing and projective techniques With no social pressure to conform to group responses, participants can be questioned in depth in a context that allows them to really express how they feel.

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Objectives After reading this chapter, you should be able to: 1 understand why the in-depth interview is defined as a direct qualitative research technique and observation and projective techniques are defined as indirect techniques; 2 describe in-depth interview techniques in detail, citing their advantages, disadvantages and applications; 3 explain how theory may be used to create structure to questioning and analysis in in-depth interviewing by reference to the laddering technique and the repertory grid technique; 4 describe projective techniques in detail and compare association, completion, construction and expressive techniques; 5 understand the context of interviewing and language problems that should be considered by qualitative researchers operating across different countries and cultures; 6 appreciate how technology is shaping the manner in which in-depth interviews and projective techniques are managed.

Overview Having discussed qualitative research in terms of its nature and approach and evaluated focus groups, we now move on to describe and evaluate other qualitative techniques. We start by describing and evaluating what is meant by an in-depth interview and the procedure of in-depth interviewing. The role of the in-depth interviewer is described and the advantages and disadvantages of the technique are summarised. In the process of conducting in-depth interviews, the techniques of ‘laddering’ and ‘repertory grid’ can be applied to help to structure the elicitation and analysis process. Laddering and repertory grid techniques will be described and illustrated. The indirect qualitative association, completion, construction and expressive projective techniques are described and illustrated. The applications of these techniques are detailed, followed by an evaluation of their advantages and disadvantages. This is developed into an overall summary of the relative strengths and weaknesses of qualitative techniques under the headings of ‘focus groups’, ‘in-depth interviews’, ‘projective techniques’ and ‘ethnographic techniques’. The following example illustrates a subject that for many individuals would be difficult to articulate: how fragrances appeal to them and their fragrance experiences. The subject requires a qualitative technique to generate data of a kind that will support creative product design, packaging and advertising decisions. The subject matter, however, is ideal for the application of in-depth interviews and projective techniques, where time can be spent building trust and rapport between the interviewer and participant. In-depth interviews allow participants talking about fragrances the time and space to express ideas about everyday events that normally they just get on with and do not have to explain or rationalise to anyone!

Real research

In-depth interviews and fragrances1 Christian Dior and the research agency Repères (www.reperes.eu) developed a research approach that tested consumer reactions to new fragrances and the context in which they are used. This work was particularly aimed at supporting decisions made in the launch of new fragrances. The researchers’ exploration was built upon the use of

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etaphors and an individual qualitative approach through in-depth interviews. They felt m there were limitations in how consumers could talk about fragrances and so chose metaphors as a way of describing an object, using words other than those that consumers may usually employ. A library of images was built that encompassed the broadest array possible of meanings and feelings. Why in-depth interviews? The researchers felt that individual interviews enabled them to go beyond initial reactions and explore the emotional unconscious. This enabled them to explore the whole emotional and imaginary chain underlying the perception of a fragrance. They felt that group discussions would never go as far into perceptions because participants could be restricted in their emotional reactions by the perceptions of other participants. One-to-one in-depth interviews allowed them to analyse the perceptions of different participants, identifying issues common to all (or to a particular target) vs. those specific to the characteristics of each participant. Participants were recruited with a specifically designed recruitment questionnaire that ensured that all had a minimum level of creativity and were able to articulate their thoughts. The room and the moderator were prepared to be as neutral as possible and ensure that a certain level of sensory deprivation was in place, so that the fragrance under study was the ‘star’ of the experience. The moderator avoided wearing perfume so as not to ‘pollute’ the air. The participants, however, were not asked to attend unscented. This was because this would not be true to life. If the participants wore a specific scent on a daily basis they may not feel comfortable being deprived of this olfactory enhancement. They were asked to place the tested fragrance on their skin as they were needed to ‘claim ownership’ of the fragrance. It was key to let the fragrance ‘live’ and develop on the participant.

In-depth interviews The meaning of ‘in-depth’ In-depth interview An unstructured, direct, personal interview in which a single participant is probed by an experienced interviewer touncover underlying motivations, beliefs, attitudes and feelings on atopic.

An in-depth interview is an unstructured, direct, personal interview in which a single participant is probed by an experienced interviewer to uncover underlying motivations, beliefs, attitudes and feelings on a topic.2 It is a qualitative interview and, as such, is based upon conversation, with the emphasis on researchers asking questions and listening, and participants answering.3 The purpose of most qualitative interviews is to derive meaning through interpretations, not necessarily ‘facts’ from participant talk. The emphasis should be upon a full interaction to understand the meaning of the participant’s experiences and life worlds.4 In order to tap into these experiences and life worlds, in-depth interviewing involves a certain style of social and interpersonal interaction. In order to be effective and useful, in-depth interviews develop and build upon intimacy; in this respect, they resemble the forms of talking one finds among close friends. They can resemble friendship, and may even lead to longterm friendship. They are also very different from the nature of talking one finds between friends, mainly because the interviewer seeks to use the information obtained in the interaction for some other purpose.5 As the name implies, in-depth interviewing seeks ‘deep’ information and understanding. The word ‘deep’ has four meanings in this context.6 These meanings will be illustrated with the scenario of a researcher trying to understand the eBay (www.eBay.com) shopping experience: 1 Everyday events. Deep understandings are held by the participants in some everyday activity, event or place. The interviewer seeks to achieve the same deep level of knowledge or understanding as the participants. For example, if the interviewer has never used

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eBay to buy or sell goods and this experience is what is being investigated, in-depth interviewing can be used as a way to learn the meanings of participants’ actions. In this respect, the participant acts as a kind of teacher and the interviewer a student, one interested in learning the ropes. 2 Context. Deep understandings go beyond common-sense explanations of some cultural form, activity, event, place or artefact. In-depth interviewing aims to explore contextual boundaries to uncover what is usually hidden from ordinary view and to penetrate the more reflexive understandings about the nature of that experience. In an eBay investigation, the interviewer can explore the meanings of different shopping experiences, the thrill of ‘winning’ a deal and the ‘joy’ of owning a particular artefact, and the ‘disappointment’ felt when a beautiful pair of shoes that look perfect on the screen are slightly shoddy when they arrive, to name but a few contextual boundaries. 3 Multi-faceted. Deep understandings allow multiple views and perspectives on the meanings of some activity, event, place or cultural object. The researcher may wish to explore the many perspectives of eBay buyers and sellers, family members who ‘enjoy’ or ‘suffer’ eBay transactions in their household, executives who manage eBay, eBay competitors and high-street retailers, again to name but a few facets of the total experience. 4 Interviewer reflection. Deep understandings can help to reveal the interviewer’s commonsense assumptions, practices, ways of talking and self-interests. (This issue will be developed in Chapter 9.) In this example, however, if the interviewer traditionally buys goods from the high street, wanting to examine the goods before buying, or has not conducted an internet transaction, what will the interviewer ‘see’ or ‘hear’ in a particular in-depth interview? This situation mirrors children–parent relationships. Children do not learn what their parents tell them, but what they are prepared and ready to hear. The same holds for in-depth interviewers: researchers do not necessarily ‘hear’ what their informants tell them, but only what their own intellectual, social, cultural and ethical development has prepared them to hear. Going deep into the minds of consumers is a learning process. Researchers make mistakes; they sometimes say the wrong things or upset participants in some way. They learn that their race, age, gender, social class, appearance or voice makes one kind of difference with some participants and another kind of difference with other informants.7 The lesson from this is that there is no ‘ideal’ means to conduct the in-depth interview. Researchers learn from their experiences, discovering strengths and playing to them, realising weaknesses and understanding how to compensate for them. In this spirit of experimentation and learning we present a procedure that encapsulates how a researcher may approach the in-depth interview.

Procedure To illustrate the technique, a scenario is set whereby the researcher is interviewing the marketing director of a soap brand that has successfully sponsored a major athletics event. The sponsorship has resulted in many industry awards, increased sales and better employee– employer relations. The researcher wishes to understand why the soap manufacturer became involved in the sponsorship and how it achieved such success. The in-depth interview with this busy executive may take from 30 minutes to well over an hour. It may occur on a one-off basis or it may unfold over a number of meetings as more understanding is developed. Once the interviewer has gained access to the marketing director (which can be very problematic; why should they give up valuable time and share commercial knowledge?), the interviewer should begin by explaining the purpose of the interview, showing what both will get out of taking part in the interview and

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explaining what the process will be like. Beyond the introduction, the interviewer may ask the marketing director a general introductory question such as ‘what impacts have the industry awards had upon your business?’. The interviewer would be expected to have done their homework to know what the awards were, what they were awarded for and who the brand was competing against. This is a very positive feature of the sponsorship experience, and it would be hoped to boost the ego of the marketing director and encourage them to talk freely about the different impacts of the awards. The impact of sponsorship could be upon existing and potential new customers, employees and suppliers. The discussion could then flow into any of these areas. After asking the initial question, the interviewer uses an unstructured format, guided by a topic guide as a reminder of important subject areas to cover. The subsequent direction of the interview is determined by the participant’s initial reply, the interviewer’s probes for elaboration and the participant’s answers. As with the focus group topic guide and the moderator managing that guide, spontaneity ensures that the process is creative and meaningful to the participant. Suppose that the participant replies to the initial question by saying: The award for the ‘best use of sponsorship’ in the launch of a new product gave us the most satisfaction. It has made us review how we execute all of our new-product launches and integrate our different marketing agencies, our employees and supply chains. The interviewer might then pose a question such as ‘was it the award that initiated the review or would you have done that anyway?’. If the answer is not very revealing, e.g. ‘we may have’, the interviewer may ask a probing question, such as ‘what did the award tell you about how you worked as a team?’. This question could open up a whole series of issues such as ‘trust’, ‘relationship development’ or ‘technical support’, to name a few. Such an exchange of questions and answers could emerge from a heading of ‘Integrating sponsorship with other marketing communications’ on the topic guide. The interviewer will keep an eye on the topic guide to ensure that all the important issues are tackled, but the specific wording of the questions and the order in which they are asked is influenced by the participant’s replies. Probing is of critical importance in obtaining meaningful responses and uncovering hidden issues. Probing can be done by asking general questions such as ‘why do you say that?’, ‘that’s interesting, can you tell me more?’ or ‘would you like to add anything else?’.8 Probing can search for general issues but also be more specific, an example in the above scenario being ‘what does good teamwork mean to you?’. One of the main success factors of specific probing is that the researcher understands something about the nature of the subject being researched. This means the researcher appreciates the significance of particular revelations, understands the language (even technical language and jargon in certain areas, like the soap industry) and has credibility with the participant, which encourages them to open up to the interviewer. The interviewer must be alert to the issues to go through, but also the issues that the participant is willing to talk about, and must listen carefully to and observe which issues fire enthusiasm in the participant. The questions and probes the interviewer puts to participants should follow the interest and logic of the participants, making them feel motivated to respond in a manner that suits them. As with a focus group discussion, the participants should feel comfortable and relaxed, which could mean holding the interview in their office, their home, a bar or a sports club. There have even been experiments using a ‘research taxi’, in which participants are taken to their destination while they participate in an interview conducted by the researcher–driver, and shadowings (observations and interviews) with subway passengers during their home–work commute.9 In these examples any context in which participants feel at ease can result in a willingness to be more reflective, honest and open. Answering in a manner that suits the participant helps to make the interview more

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comfortable and relaxed. For a great amount of business research, the in-depth interview is the best way to gain access and to talk to managers. Much of the interviewing takes place in their office at a time that is convenient to them. Researchers can also observe characteristics of the manager in their office environment that can be of help in their analyses. Examples of this could be levels of formality in the workplace, reports and books that the manager has for reference, the manager’s use of technology, or the tidiness of the workplace. In the example above, where a manager has received a sponsorship award, it could be how that and other awards are displayed, photographs from advertisements or displays of new products. These observations would be entirely based upon the purpose of the study, but the context of the office can be of help to the manager and the researcher. In order to make the above process work, the interviewer should: 1 Do their utmost to develop an empathy with the participant. 2 Make sure the participant is relaxed and comfortable. 3 Be personable, to encourage and motivate participants. 4 Note issues that interest the participant and develop questions around these issues. 5 Not be happy to accept brief ‘yes’ or ‘no’ answers. 6 Note where participants have not explained clearly enough issues that need probing. In marketing research that focuses upon managers or professionals, as illustrated above, the context of the in-depth interview helps to set the frame of mind of the participant. The context should also help the participant and interviewer to relax, engendering an atmosphere to explore and develop issues that they feel to be relevant. The following arguments help to focus on the issues faced by the interviewer coping with managers and professionals, trying to find the right context to allow these participants to express how they really feel.10 The indepth interview helps to overcome: 1 Hectic schedules. The best participants tend also to be the busiest and most successful people. They can make time for an interview, but are rarely able to spare the much greater time needed for them to come to a group discussion at some location away from their office. So groups exclude the best participants. 2 Heterogeneity. Whereas mothers evaluating nappy advertisements, or beer drinkers the latest lager, have only their personal preferences to consider, it is very different for executives evaluating copiers, airline advertisements or computer software. This is because their reactions are complicated by the type of job they do and who they work for. The group discussion is dependent on the group’s composition being fairly homogeneous; the job backgrounds of business people make them too varied to be entirely comfortable in a group. 3 Live context. A lot of information comes from seeing the participant at their desk, which is missed in a group discussion. Work schedules pinned to the wall, the working atmosphere, artefacts placed on the desk, family photographs, the way coffee is served – all help to fill out the picture. 4 Interviewer reflection. Groups do not allow the researcher enough thinking time. Two groups, each taking an hour and a half over successive evenings, do not even begin to compare with two or three full days of non-stop interviewing. Individual interviews give much more scope for experimentation. If one way does not work it is only one participant, not a whole group, that is affected. The following example illustrates the types of professionals or experts that may be targeted to participate in individual in-depth interviews.

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Connecting with experts11 Unilever’s Axe men’s range of toiletries was inspired by an unconventional approach to consumer research. The research approach started with in-depth interviews with a group of individuals identified as experts in ‘understanding men’ and what drives them. The experts included a professor of evolutionary psychology, sex psychologists, adult film directors, a ‘burlesque’ dancer, a game developer and a senior writer on Loaded magazine. They were all interviewed in their own working environments, either by Unilever’s Consumer Insight Manager or using researchers from the international qualitative and youth research company Firefish (www.firefish.ltd.uk).

Another major application of in-depth interviews, where the context of the interview plays a major part, is in the interviewing of children.12 Researchers into children and teenagers spend considerable time working out the best research approach. Debates proliferate on the most appropriate research designs and interviewing techniques: in-depth interviews versus group, mini groups versus standard groups, friendship pairs versus stranger groups, association projective techniques versus expressive ones, and of digital media-based techniques.13 These debates make researchers focus on the implications of how research is conducted and which technique provides the best results. One vital element is often overlooked, and that is the issue of context: in other words, the need to ensure that the situation in which children are interviewed is relevant to the research needs. Like adults, children have multi-faceted personalities. The same teenager can be sullen at home, obstructive in the classroom, but the life and soul of the peer group. The essential difference between children and adults, however, is the extent to which different aspects of the persona can be accessed on one occasion and in one situation, the research setting. Adults have insight into the different roles and behaviour, which they adopt in different contexts, and can project other aspects of themselves, which they bring into the research situation. Children and young teenagers, on the other hand, react to the moment and thus project only one aspect of themselves. They lack the maturity, experience and self-knowledge to draw on other parts of themselves and therefore find it almost impossible to know, let alone admit or explore, how they might behave in another circumstance.14 The above evaluation of the importance of context also shows that question formulation, the very heart of marketing research, can be more important in interviewing children than when dealing with adults. A straightforward ‘what do you think about X?’ may throw children into confusion. A formulation such as ‘if you were to call your friends about this, what would you tell them?’ would be more likely to produce illuminating responses. An innovative approach to interviewing children is illustrated in the following example.

Real research

Quantifying the emotional aspects of advertising15 In order to understand how to ‘talk’ to children we need to find ways to connect to them, and hence explore what it is like to be a 10 year old. The way Optimisa (www.optimisaresearch.com) goes about researching children taps into the very areas where they are not adults. It is about how we as adults adapt to who they are, finding a way to engage with every child and building a bridge to help us reach their world. A good starting point is often an awareness of the skills they have developed in school, using these as the building blocks for the technique. So, rather than asking a child a direct question, which more often than not will result in a long blank look, we can ask children to draw a picture, or select a photograph, or even write a story that simply relates to the question we are

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trying to ask. Children react well to this approach and find the prop easy to talk around, often giving the researchers more than they hoped for. On a project for Cartoon Network, a child depicted in a picture one of the pressures of the fierce consumer society we live in. The picture was about exclusion and showed a group of boys; outside the group, another boy was crying. On closer inspection it was not the fact that boy was crying that told the story, but why he was doing so. A Nike tick was distinctly missing from his trainers.

Friendship pair A technique used to interview children as two friends or classmates together.

An effective technique when working with children is the use of friendship pairs – i nterviewing two friends or classmates together. This helps to cut out lying because children are not alone with strangers and because, if one tells a lie, the other ‘tells’ on that one. The ingrained honesty of children arguably makes them easier to research than adults, who of course are far more accomplished exponents of deception.

Advantages and challenges of in-depth interviews In-depth interviews have the following advantages. They can: •

•

Uncover a greater depth of insights than focus groups. This can happen through concentrating and developing an issue with the individual. In the group scenario, interesting and knowledgeable individuals cannot be solely concentrated upon. Attribute the responses directly to the participant, unlike focus groups where it is often difficult to determine which participant made a particular response. Result in a free exchange of information that may not be possible in focus groups because, alone, there is no social pressure to conform to group response. This makes in-depth interviews ideally suited to sensitive issues, especially commercially sensitive issues. Be easier to arrange than the focus group as there are not so many individuals to coordinate and the interviewer can travel to the participant.

The following are not necessarily disadvantages, but rather the challenges that researchers face when using this valuable technique: •

•

The lack of structure makes the results susceptible to the interviewer’s influence, and the quality and completeness of the results depend heavily on the interviewer’s skills. As with all qualitative techniques, the interviewer needs to develop an awareness of the factors that make them ‘see’ in a particular way. The length of the interview, combined with high costs, means that the number of in-depth interviews in a project tends to be few. If few in-depth interviews can be managed, the researcher should focus upon the quality of the whole research experience. ‘Quality’ in this context means the qualities that the participant possesses in terms of richness of experience and how relevant the experiences are to the study; the quality of drawing out and getting participants to express themselves clearly and honestly; and the quality of analysis in terms of interpretation of individual participants and individual issues evaluated across all the interviews conducted. The data obtained can be difficult to analyse and interpret. Many responses may not be taken at face value; there can be many hidden messages and interpretations in how participants express themselves. The researcher needs a strong theoretical awareness to make sense of the data, or the technical means to develop theory if using a grounded theory approach. As well as the transcripts of the interview, additional observations add to the richness and multi-faceted analyses and potential interpretations.

The use of the laddering technique in the next example illustrates how a theoretical awareness can help to develop structure, elicit or draw more out of participants and help to make

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sense of the data they generate. It is an illustration of how the three challenges outlined above can be overcome. Balance what may be seen as the advantages and disadvantages of in-depth interviews in evaluating this example. Implementing the following discussion guide would be challenging, but would also generate many unique consumer insights. It illustrates that the in-depth interview is not a fixed and formulaic approach. This builds upon the Christian Dior example at the start of this chapter. The use of ‘laddering techniques’ will be further explained and illustrated in the next section.

Real research

Christian Dior in-depth interview discussion guide16 The in-depth interview approach developed by Christian Dior and the research company Repères broadly followed these stages, allied to a laddering technique: 1 Gather initial sensations and emotions that come up instantly after a first sniff: a Evocations and imagery were explored: (i) Association, imaginary place/scene, Chinese portrait, a photofit of the fragrance. 2 Gather new sensations a few minutes after the first sniff, once the fragrance had developed, and then re-evaluate the different sensations mentioned to obtain: a A detailed description of each sensation (e.g. if sensation of warmth, is it warmth from a chimney fire, from the noon sun, from a duvet, human warmth) and where it operates (on the body, on the mood, on the nerves, on the mind/state of mind). b The source of this sensation: what note, what scent (if concrete description pos sible) or what ‘sort’ of odour (if analogous description) produced this sensation. 3 Analyse the olfactory journey or construction of the fragrance, its mechanism (it goes from what sensation/effect to what sensation?). 4 Identify the resulting personality of the fragrance: descriptors, values, objectives/ mission/role of the juice, image, distinctive specificity. a The projected target: what is the likely female (male) profile for the fragrance? 5 Image assessment using visual stimuli (varied photos from the picture library: different colours, shapes, materials, places, characters, scenes from life) to expose hidden or unconscious perceptions: a First, ask for a justified choice of six photos, each one representative of a perceived aspect or dimension of the fragrance. b Then force associations as the moderator selects six photos at random and not chosen at the beginning by the participant, asking what matches/does not match the fragrance under scrutiny. 6 Then close up with a critical assessment of the potential and risks/limitations of the fragrance.

The laddering technique The in-depth interview can be driven by a topic guide, made up of just a few topics covering a very broad range of issues. From these few topics, the nature of questions, the order of questions and the nature of probes can be driven by the interviewer’s perception of what will

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Laddering A technique for conducting in-depth interviews in which a line of questioning proceeds from product characteristics to user characteristics.

draw the best out of participants. Alternatively, an in-depth interview can be semi-structured, where parts of the interview use consistent and highly structured questions, with set response categories, interspersed with open-ended questions involving probes that again suit the nature of the participant. There are other variations on the technique that can help the interviewer and participant to apply useful structure to issues that can be very ‘messy’ and unstructured. One of the most popular techniques to apply structure is called laddering. Laddering requires interviewers to be trained in specific probing techniques in order to develop a meaningful ‘mental map’ of the consumer’s view towards a particular product. The ultimate goal is to combine mental maps of consumers who are similar, which lead to the reasons why consumers purchase particular products. The laddering technique is made up of a linking, or ladder, of elements that represent the link between products and the consumer’s perception process. It enables an understanding of how consumers translate product attributes, through personal meanings associated with them.17 Theories of consumer behaviour act as a foundation to this approach, based on the contention that consumption acts produce consequences for the consumer. Consumers learn to associate these consequences with specific product attributes. These associations are reinforced through consumers’ buying behaviour and, as a result, they learn to choose products that have certain attributes in order to obtain the consequences they desire. There are two features of this theory that the researcher using the laddering technique will focus upon: 1 Motivation. The laddering technique focuses upon generating insight into the motives behind the consumption of certain products. It represents a more contemporary approach to classical motivation research.18 The technique aims to stimulate participants to reflect upon their buying behaviour in a way unconnected from their usual behaviour. 2 Cognitive structure. This feature is also a development of theory, in this case means–end– chain (MEC), developed by Gutman.19 MEC starts from a point of consumer motivation. It contends that motivation leading towards a form of behaviour is derived from the connection between tangible product attributes and more abstract cognitive structures that involve the physical and emotional consequences derived from these attributes. At a more abstract level, the consequences lead to values held by the consumer. The laddering technique is therefore designed to identify and follow the chain of attributes S consequences S values (A−C−V) The in-depth interview using the laddering technique is based on comparisons of the consumer’s choice alternatives. These can include, for example, different products used for the same purpose, such as an electric toothbrush and a conventional toothbrush, and/or varieties in a product line such as full-fat and skimmed milk, and/or product brands such as Heineken and Amstel beer, and/or kinds of packaging such as wine in bottles and in cartons. Other elements that can affect consumer choices can be added to the above list. In making the comparisons, the interviewer poses a question that hopes to encourage the participants to put aside their established rationale and reflect upon their consumption behaviour, in ways that they would not normally do. In other words, questions are posed that make participants think about consumption from other points of view to try to release participants from fixed attitudes, perceptions and values. The interviewer’s role is to build up a rapport with participants and get them to relax and feel comfortable to respond with whatever comes to mind. The interview revolves around three basic questions based on the A–C–V chain. The questions posed would be: 1 Attributes. What is different about these alternatives? (e.g. low calories) 2 Consequences. What does this difference mean? (e.g. not fattening) 3 Values. How important is this for you? (e.g. health)

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From the attribute of ‘low calories’ in comparing different product varieties in a product line such as full-fat and skimmed milk, a further and negative consequence of ‘watery taste’ could be elicited, followed by the values of ‘unnatural’. The interviewer aims to build spontaneously a great repertoire of chains through these levels, choosing the right comparisons to draw out the next link in the chain. The resulting responses are analysed to establish possible categories of attributes, consequences and values. The categories are then organised according to the qualitative comments made between the relationship of an attribute, its consequence and value. The result is an association matrix that graphically displays the categories and the connections that have emerged. Laddering requires an interviewer with experience of in-depth interviewing, with a realisation of what will relax participants and get them in a frame of mind to ‘play’ with the associations sought. The interviewer needs to appreciate the theoretical foundations of the technique,20 not only to help determine what should be elicited from participants, but also to help generate sound and meaningful analyses. Laddering sets out to unravel ‘how consumers translate product attributes, through personal meanings associated with them’ to provide a motivational and cognitive structure to purchase decisions in a given market. In essence, the technique looks at a brand in terms of the attributes that make it different from other brands, the consequences of this for the individual (what does the difference mean?) and the value the difference has (how important is it?).21 The following example illustrates the consumer insights and marketing implications that emerged through the use of laddering.

Real research

AUTO BILD – understanding the connected barometer22 The AUTO BILD market barometer is an annual study carried out by Europe’s biggest car magazine. A recent study explored the concept of connectivity. A mixed-methods approach was used involving a quantitative survey with 1,403 drivers, two separate online communities involving 60 participants and face-to-face interviews with selected members of the online community. A laddering technique was applied to further analyse the research participant views that were expressed in the community. The key laddering insights among younger consumer groups included: • •

•

Smartphones are replacing cars as an object of identification. Consumers are developing a new unemotional relationship to cars; they are becoming more similar to consumables. Digital lifestyles are an emotional driving force. The physical presence of ‘being there’ that a car enables has become less important.

The insights generated helped to identify and build a better understanding of the ways in which consumers understand cars.

The repertory grid technique Another widely used technique that applies structure to qualitative in-depth interviewing is the repertory grid technique (RGT). This technique was originally developed by George Kelly in 195523 to explore the meanings that people attach to the world around them, which they find particularly hard to articulate. As with the laddering technique, there is a theoretical underpinning – a personal construct psychology.24 The repertory grid technique is rooted in a grounded theory perspective. The categories used in the findings emerge from the data rather than being introduced by the researchers. It is a technique that grounds the data in the

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culture of the participants, if they choose both the elements and the constructs, and it is clearly useful where there is a need to explore the personal worlds of participants. The repertory grid has gained status in management research because of its distinctive strengths. It helps researchers to explore the unarticulated concepts and constructs that underlie people’s responses to the world. Moreover, it is a technique that may reduce the problem of interviewer bias in in-depth interviews. A particular strength of the repertory grid technique is that it can help to access the underlying realities in situations where the cultural or people issues are particularly strong, and where participants might otherwise feel constrained to try to answer in the way they think they should, as opposed to how they really think.25 There are a number of variations of the technique, and arguments about whether it should be implemented and analysed in a positivist or interpretivist manner,26 but in essence the stages involved in the repertory grid technique are:27 1 Element selection 2 Construct elicitation 3 Element comparisons 4 Data analysis. 1 Element selection. The elements selected will depend upon the nature of consumer behaviour that the interviewer wishes to examine. In a study that wished to understand broad-based patterns of consumer behaviour28 the elements chosen included 30 generic products and services such as newspapers, holidays, chocolate bars, eggs, alcoholic drinks, shoes, toothpaste, savings accounts, restaurant meals and shampoo. In another study that wished to understand the process of effective new product development29 the elements chosen included 30 successful new products and services, such as Slim Fast, Pull Ups, Loed Tea, Ultraglide, Baby Jogger, Gourmet Coffee, Zantac, Paragliders, MTV and Carmen Soft. These elements should be chosen by the participants, not just chosen and presented by the interviewer. There should be some homogeneity in the elements in the sense that the participant sees the elements relating to and being representative of the behaviour being studied. 2 Construct elicitation. Having selected elements that the participant believes to encapsulate the behaviour being studied, the interviewer now seeks to understand what connects them together. The first stage of this involves the interviewer selecting three of the chosen elements at random and then presenting to the participant small cards with a summary of these elements. The participant is then asked to describe how they see two of the three to be alike and how the third may be different. The researcher selects different ‘triads’, to the point where all the elements have been contrasted or the participant cannot describe further ‘similarities’ or ‘differences’. Construct elicitation therefore draws out the participant’s perspective of the important features that encapsulate a particular form of consumer behaviour. 3 Element comparisons. The constructs elicited from participants are now turned into bipolar descriptions in a manner similar to the semantic differential scale described and illustrated in Chapter 12. For example, suppose that in a study of the process of effective new product development, three elements were compared: MTV, Gourmet Coffee and Paragliders. The participant may say that MTV and Gourmet Coffee are alike in that there are many similar competitive products that they can be compared with, whereas Paragliders is different in that there are few competitive ‘personal’ means to fly long distances. Whether this is factually correct or whether the interviewer agrees with this is immaterial; it is how the participant sees it that is important. Such a belief could be turned into a bipolar scale, as illustrated below:

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No other products like this in the market

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Lots of competitive products

Other scales would be constructed to cover the ways that participants compared the chosen elements, i.e. the constructs elicited would be turned into a series of bipolar scales. Participants would then be expected to evaluate all the original elements using these scales. If they felt that Gourmet Coffee has many competitors, they could tick a line at the (6) or (7) point. So, if there were 30 elements that encapsulate the behaviour under study and 20constructs elicited to evaluate these elements, a total of 30 * 20, or 600, ratings would need to be performed. 4 Data analysis. A grid can be assembled for each participant to represent, in the above example, the 30 * 20 ratings. Again, an illustration of this comes from a small extract of the process of effective new product development study. The following represents an extract of the total response from one participant:

Construct Market newness Company newness Technology newness

MTV

Gourmet Coffee

Paragliders

6 3 2

6 7 4

2 1 6

With a number of these completed grids, factor analysis (Chapter 24) can be performed to discover the important underlying factors or dimensions that encapsulate a particular form of behaviour.30 The analysis can continue by performing cluster analysis (Chapter 25) to explore patterns of similarity or dissimilarity in different types of participant, i.e. to discover and describe groups of participants who may view particular forms of behaviour in similar ways. The above process can take a great deal of time to select the elements, to elicit the means to compare the elements and to evaluate them. It requires an amount of rapport between the interviewer and the participant and patience in working through the stages. All of the stages may not be completed in one interview. It may require the interviewer to return to the participant to develop the next stage, especially in transferring the elicited elements to bipolar descriptions to allow all the elements to be evaluated.

The Zaltman metaphor elicitation technique Another technique that creates a ‘mental map’ of the consumer’s view towards a particular product is the Zaltman metaphor elicitation technique (ZMET). It is a qualitative in-depth technique that is used by companies such as Procter & Gamble, AT&T, Kodak, Ford and General Motors. It was developed at the Harvard Business School by Professor Jerry Z altman and is patented in the USA. In a ZMET study, before coming in for an in-depth interview, participants are asked to gather pictures that reflect their thoughts and feelings about an advertisement and brand.31 The technique uses images and metaphors to reveal how consumers think and feel about brands, issues or other research topics. It does not ask consumers ‘what they think about the things researchers think about’. Instead, it lets participants’ own frames of reference shape the in-depth interview, without losing sight of the research aims. The technique, its application and the power of visual metaphors are illustrated in the following examples.

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Real research

Diving for pearls32 ZMET allows the participant to define the frame of reference for an interview. The use of metaphor is extremely effective in revealing submerged thoughts and feelings, and specifically in allowing access to the emotional domain. Participants are given a question a few days before their actual interview, and asked to source (non-literal) images reflecting their feelings. For example, in a study of looking at how people choose which financial products to buy and which suppliers to use, one participant brought in a picture of two dogs, a fully grown Saint Bernard towering over a tiny Chihuahua, to express his feeling of being intimidated by large companies. This period of reflection brings tacit knowledge to the surface. At an indepth interview, participants explain the significance of each image and how it relates to the question. Probing for clarification, cause and consequence reveals the meaning behind each idea and the connections between ideas. The results reveal the consumers’ mindset: the issues most salient to them and the thoughts and feelings they attach to each issue. The result is a consensus map of ‘the mind of the market’. Although product performance remains central to this map, the process also allows highly emotional outcomes, such as confidence, joy, fear and alienation, to emerge.

Real research

Using metaphor33 Metaphors seem to express emotions more vividly than literal language because they evoke an emotional response directly. Memories that have emotional significance seem to have the greatest resonance; metaphors that link directly to emotions are the most powerful. The scales we use to measure consumer views of brands and brand communications are language based and literal, not visual or metaphorical. Participants need to consider their response before answering, but by consideration they get further away from emotions. The emotion may still be present but it becomes blended with thinking and is more prone to post-rationalisation. The Conquest Metaphorix (www. metaphorixuk.com) approach incorporates visual metaphorical scales based on primary metaphors linked with emotional states, such as love, affection and intimacy, which have particular relevance to brand engagement. These online scales use a range of engaging visual devices to represent metaphors associated with different emotional states, using visual depictions of (for example) proximity/closeness and warmth.

ZMET aims to understand the images and associations that underpin both spoken and tacit thoughts and feelings through the elicitation of both rational and emotional thinking. The process especially allows the emotional aspects of products and their use to become apparent. The resultant analysis creates a graphical visualisation of the ‘mind of the market’. This visualisation creates a link between consumer perceptions and those involved in creative activities of product design and marketing communications. Such an approach accelerates

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the creative process and helps design and advertising agencies to add more emotional value to their work.

Applications of in-depth interviews Applying in-depth interviews, with high or low levels of structure, with a strong theoretical foundation such as laddering, the repertory grid technique or ZMET, or with the desire to generate grounded theory, presents challenges but also many rewards. There are many marketing decisions that can be made with support from researchers using the broad array of techniques under the heading of ‘in-depth interviews’. The following summarises the applications:34 1 Interviews with professional people (e.g. finance directors using banking services). 2 Interviews with children (e.g. attitudes towards a theme park). 3 Interviews with elite individuals (e.g. wealthy individuals involved in large philanthropic ventures). 4 Detailed probing of the participant (e.g. new-product development for cars). 5 Discussion of confidential, sensitive or embarrassing topics (e.g. personal hygiene issues). 6 Situations where strong social norms exist and where the participant may be easily swayed by group response (e.g. attitudes of university students towards sports). 7 Detailed understanding of habitual or tacit behaviour (e.g. the ‘rituals’ an individual may go through when preparing to get ready for an evening out). 8 Detailed understanding of complicated behaviour (e.g. the purchase of fashion or ‘high-status’ goods). 9 Interviews with competitors who are unlikely to reveal the information in a group setting (e.g. travel agents’ perceptions of airline travel packages). 10 Situations where the product consumption experience is sensory in nature, affecting mood states and emotions (e.g. perfumes, bath soap). In the application of in-depth interviews, the researcher can use other techniques to help maintain the interest of participants, to make the experience more enjoyable for the participants and the researcher alike and ultimately to draw out the true feelings of participants. A set of techniques that help to achieve all this, and that have been applied with great success over many years, is the body of indirect techniques called ‘projective techniques’.

Projective techniques Projective technique An unstructured and indirect form of questioning that encourages participants to project their underlying motivations, beliefs, attitudes or feelings regarding the issues of concern.

Projective techniques are a category of exercises designed to provoke imagination and creativity that can be used in in-depth interviews. Projective techniques are subject-oriented, non-verbal and indirect self-reporting techniques that have the ability to capture responses from participants in a less structured and more imaginative way than direct questioning. They get beyond the rational replies participants often make in interview situations, encouraging them to project their underlying motivations, beliefs, attitudes or feelings regarding the issues of concern.35 They are useful techniques for drawing out emotional values, exploring issues in a non-linear manner or for bypassing participants’ rational controls. They also help participants to verbalise unframed, subconscious, low-salience or lowinvolvement attitudes. 36 Viewed as ‘face-saving’ techniques, projection provides

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participants with the facility to project their thoughts and feelings onto another person or object (e.g. via completion tests). Fundamentally, projective techniques can enable research participants to express feelings and thoughts they would otherwise find difficult to articulate.37 In projective techniques, participants are asked to interpret the behaviour of others rather than to describe their own behaviour. In interpreting the behaviour of others, it is contended that participants indirectly project their own motivations, beliefs, attitudes or feelings onto the situation. Thus, the participants’ attitudes are uncovered by analysing their responses to scenarios that are deliberately unstructured, vague and ambiguous. The more ambiguous the situation, the more participants project their emotions, needs, motives, attitudes and values, as demonstrated by work in clinical psychology (on which projective techniques are based).38 The following example illustrates a use of projective techniques as part of the process of pre-testing advertisements.

Real research

Pre-testing mould-breaking advertisements39 In an environment where consumers value originality, communications that really ‘break the mould’ offer advertisers rewards in terms of increased relevance. In a study for Sony, TNS (www.tnsglobal.com) felt that qualitative projective questioning techniques could be used alongside quantitative pre-testing techniques on mould-breaking advertisements. TNS felt that projective techniques could help participants reveal how mould-breaking advertisements work at a deeper, emotional level. Its NeedScope™ technique used photosets representing different personality types. The Sony Bravia Television (www.sony.co.uk/ electronics/bravia) ‘Paint’ commercial was chosen to apply the technique. The exploding ‘paint-fest’, set on a Glasgow council estate, was an unexpected way to advertise a new TV. There were no lists of features, no voice-over describing the benefits, no happy family sitting around their new TV and not even a glamorous tropical location. Sony’s website stated: When you’re introducing the next generation of television, you want to make an impact– but that doesn’t mean you have to be predictable. To announce the arrival of the new Bravia LCD and SXRD range, we want to get across a simple message – that the colour you will see on these screens will be like no other. For a clear majority of participants, the brand represented a carefree, lively, bold personality. In terms of brand image, the strongest attributes were ‘vibrant colour’, ‘lively’, ‘outgoing’, ‘dynamic’ and ‘cool/trendy’ – very much where the Sony Bravia communication strategy wanted to be. The results from projective questioning were examined holistically with the results from other questions on likeability, recall and branding. Given the recognised importance of emotions in brand communications and engagement, projective techniques have a lot to offer in pre-testing advertisements.

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As in psychology, these projective techniques are classified as association, completion, construction and expressive. Each of these classifications is discussed below.40

Association techniques Association technique A type of projective technique in which participants are presented with a stimulus and are asked to respond with the first thing that comes to mind.

Word association A projective technique in which participants are presented with a list of words, one at a time. After each word, they are asked to give the first word that comes to mind.

In association techniques, an individual is presented with a stimulus and asked to respond with the first thing that comes to mind. Word association is the best known of these techniques. In word association, participants are presented with a list of words, one at a time, and encouraged to respond without deliberation to each with the first word that comes to mind. The words of interest, called test words, are interspersed throughout the list, which also contains some neutral, or filler, words to disguise the purpose of the study. The participant’s response to each word is recorded verbatim and responses are timed so that participants who hesitate or reason out (defined as taking longer than three seconds to reply) can be identified. The interviewer, not the participant, records the responses. The underlying assumption of this technique is that association allows participants to reveal their inner feelings about the topic of interest. Responses are analysed by calculating: 1 The frequency with which any word is given as a response. 2 The amount of time that elapses before a response is given. 3 The number of participants who do not respond at all to a test word within a reasonable period. Those who do not respond at all are judged to have an emotional involvement so high that it blocks a response. It is often possible to classify the associations as favourable, unfavourable or neutral. An individual’s pattern of responses and the details of the response are used to determine the person’s underlying attitudes or feelings on the topic of interest, as shown in the following example.

Real research

Dealing with dirt41 Word association was used to study womens’ attitudes towards detergents. Below is a list of stimulus words used and the responses of two women of similar age and household status. The sets of responses are quite different, suggesting that the women differ in personality and in their attitudes towards housekeeping. Ms M’s associations suggest that she is resigned to dirt. She sees dirt as inevitable and does not do much about it. She does not do hard cleaning, nor does she get much pleasure from her family. Ms C sees dirt too, but is energetic, factual-minded and less emotional. She is actively ready to combat dirt, and she uses soap and water as her weapons. Stimulus

Ms M

Ms C

Washday Fresh Pure Scrub Filth Bubbles Family Towels

Everyday And sweet Air Does not; husband does This neighbourhood Bath Squabbles Dirty

Ironing Clean Soiled Clean Dirt Soap and water Children Wash

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These findings suggest that the market for detergents could be segmented based on attitudes. Firms (such as Procter & Gamble) that market several different brands of washing powders and detergents could benefit from positioning different brands for different attitudinal segments.

There are several variations to the standard word association procedure illustrated here. Participants may be asked to give the first two, three or four words that come to mind rather than only the first word. This technique can also be used in controlled tests, as contrasted with free association. In controlled tests, participants might be asked ‘what Formula One teams come to mind first when I mention “boring”?. More detailed information can be obtained from completion techniques, which are a natural extension association techniques.

Completion techniques Completion technique A projective technique that requires participants to complete an incomplete stimulus situation.

Sentence completion A projective technique in which participants are presented with a number of incomplete sentences and are asked to complete them.

Story completion A projective technique in which participants are provided with part of a story and are required to give the conclusion in their own words.

In completion techniques, participants are asked to complete an incomplete stimulus situation. Common completion techniques in marketing research are sentence completion and story completion.42 Sentence completion is similar to word association. Participants are given incomplete sentences and are asked to complete them. Generally, they are asked to use the first word or phrase that comes to mind, as illustrated in the Formula 1 example below. This example illustrates one advantage of sentence completion over word association: participants can be provided with a more directed stimulus. Sentence completion may provide more information about the subjects’ feelings than word association. Sentence completion is not as disguised as word association, however, and many participants may be able to guess the purpose of the study. A variation of sentence completion is paragraph completion, in which the participant completes a paragraph beginning with the stimulus phrase. A further expanded version of sentence completion and paragraph completion is story completion. In story completion, participants are given part of a story – enough to direct attention to a particular topic but not to hint at the ending. They are required to give the conclusion in their own words; for example, a sentence-completion example in the case of Formula 1 motorsport might look like the following:

Sentence completion A Formula One fan that supports a team rather than a driver is ________________ __________________________________________________________________ A sponsor who selects drivers based on how competitive they are is ____________ __________________________________________________________________ The Ferrari team is most preferred by ____________________________________ __________________________________________________________________ When I think of watching Formula One on television, I ______________________ Construction technique A projective technique in which participants are required to construct a response in the form of a story, dialogue or description.

Construction techniques Construction techniques are closely related to completion techniques. Construction techniques require the participants to construct a response in the form of a story, dialogue or description. In a construction technique, the researcher provides less initial structure for the

Chapter 8 Qualitative research: in-depth interviewing and projective techniques

Picture response technique A projective technique in which participants are shown a picture and are asked to tell a story describing it.

Cartoon tests Cartoon characters are shown in a specific situation related to the problem. Participants are asked to indicate the dialogue that one cartoon character might make in response to the comment(s) of another character.

Expressive technique A projective technique in which participants are presented with a verbal or visual situation and are asked to relate the feelings and attitudes of other people to the situation.

Role playing Participants are asked to assume the behaviour of someone else or a specific object.

Third-person technique A projective technique in which participants are presented with a verbal or visual situation and are asked to relate the beliefs and attitudes of a third person in that situation.

Personification technique Participants are asked to imagine that the brand is a person and then describe characteristics of that person.

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participants than in a completion technique. The two main construction techniques are picture response techniques and cartoon tests. The roots of picture response techniques can be traced to the thematic apperception test (TAT), which consists of a series of pictures of ordinary as well as unusual events. In some of these pictures the persons or objects are clearly depicted, while in others they are relatively vague. The participant is asked to tell stories about these pictures. The participant’s interpretation of the pictures gives indications of that individual’s personality. For example, an individual may be characterised as impulsive, creative, unimaginative and so on. The term ‘thematic apperception test’ is used because themes are elicited based on the subject’s perceptual interpretation (apperception) of pictures. In cartoon tests, cartoon characters are shown in a specific situation related to the problem. Participants are asked to indicate what one cartoon character might say in response to the comments of another character. The responses indicate the participants’ feelings, beliefs and attitudes towards the situation. Cartoon tests are simpler to administer and analyse than picture response techniques.

Expressive techniques In expressive techniques, participants are presented with a verbal or visual situation and asked to relate the feelings and attitudes of other people to the situation. The participants express not their own feelings or attitudes, but those of others. The main expressive techniques are role playing, the third-person technique and personification. In role playing, participants are asked to play the role or to assume the behaviour of someone else. Participants are asked to speak as though they were someone else, such as another household member with whom they would share a decision or an authority figure. For example, ‘Bernard, you are a 15-year-old boy; Eva, you play Bernard’s mother; George, you play Bernard’s father. Imagine you are at home deciding which summer holiday you would like this year as a family.’ The discussion that emerges is likely to reveal unspoken objections as well as those of overcoming resistance to features of the holiday, locations and ways of travelling there that may be favoured by Bernard but not his parents, or even his mother and not by the two males. The researcher assumes that the participants will project their own feelings into the role.43 In the third-person technique, participants are presented with a verbal or visual situation and are asked to relate the beliefs and attitudes of a third person, rather than directly expressing personal beliefs and attitudes. This third person may be a friend, a neighbour, a colleague, or any person that the researcher chooses. Again, the researcher assumes that the participants will reveal personal beliefs and attitudes while describing the reactions of a third party. Asking an individual to respond in the third person reduces the social pressure to give an acceptable answer. In the personification technique, participants imagine that the brand is a person and then describe characteristics of that person, e.g. their lifestyle, status, demographics, home(s). They can build up layers of this description using words and images from a variety of sources. These descriptions help to uncover and develop the perceived nature of a brand’s personality. The following example shows why the brand personality is of importance to the marketer and how an understanding of personality may be used in advertising.

Coors – Coors Light44 Brand personality The most common definition states that brand personality is ‘the set of human characteristics associated with a brand’. Consumers find it natural to imbue brands with

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ersonality characteristics, such as ‘honest’, ‘cheerful’, ‘charming’ or ‘tough’. Moreover, p the personality traits associated with a brand, as with those associated with an individual, tend to be relatively enduring and distinct.45 Coors Light was a brand at a crossroads. Since its launch in 1984 it had become the best-selling light beer in Canada. In 2002 a superficial analysis of Coors Light would reveal a strong brand. It was growing in share and volume and had carved out a strong position. This came from the brand’s history. It had capitalised on lifestyle trends such as health, fitness and lower calorific intake. Creatively, it had leveraged its Rocky Mountain heritage to communicate a healthy, active, fun lifestyle. However, Coors Light loyal drinkers were getting older and they were lighter drinkers. At one time a young man in a focus group said that he had tried the beer ‘once with an uncle at a funeral’ – ouch! Coors Light was not relevant to their lifestyle. Coors wished to develop a new brand personality that would drive all elements of marketing and business strategy. For a brand to become a leader, Coors did not believe it should mimic the attitude and personality of its target drinkers. It needed to develop a brand personality and a voice that ‘earned a right to be a part of the party’. Coors’ qualitative research projected ‘young adult-oriented brands’ generally falling into two camps. There were ‘skateboarding monkey’ brands, which inserted themselves into a scenario and tried to earn consumer affinity through proximity; these brands usually ended up looking as if they were wearing their younger brother’s clothes, and young adults were able to see through this approach. Then there were brands that became a part of the culture they were looking to infiltrate. They weren’t just using the words. They understood their meaning and believed in the core values of the target group. These brands earned a lasting and enduring affinity.

Brand personality can also be uncovered using role play.46 In a group discussion scenario, participants may be asked to play out the personality of a brand. In the Coors example, the setting could be a sports bar after work on a Friday evening, with individuals acting out what they see as the personas of the brands Coors, Guinness, Becks, Stella Artois and Heineken. What the individuals as a brand do, what they say, how they interact with each other in the bar, all allow an expression of personality that straight questioning may not reveal. Video recording of the event, played back to the group, acts as a means to discuss and elicit further meaning of a brand’s personality, highlighting any positive and negative associations of the brand.

Advantages and disadvantages of projective techniques The major advantage of projective techniques is that they may elicit responses that participants would be unwilling or unable to give if they knew the purpose of the study. At times, in direct questioning, the participant may intentionally or unintentionally misunderstand, misinterpret or mislead the researcher. Personal accounts can be more self-conscious and self-justifying than the actions themselves, because they represent the way an individual would like to be judged.47 This is one of the values of projective techniques, which frame the actions as those of ‘someone else’. Projective techniques can increase the validity of responses by disguising the purpose. This is particularly true when the issues to be addressed are personal, sensitive or subject to strong social norms. Projective techniques are also helpful when underlying motivations, beliefs and attitudes are operating at a subconscious level.48 Projective techniques suffer from many of the disadvantages of unstructured direct techniques, but to a greater extent. These techniques generally require personal interviews with

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individuals who are experienced interviewers and interpreters; hence they tend to be expensive. Furthermore, as in all qualitative techniques, there can be a risk of interpretation bias. With the exception of word association, all are open-ended techniques, making the analysis and interpretation more problematic. Some projective techniques, such as role playing, require participants to engage in what may seem to be unusual behaviour. Certain participants may not have the self-confidence or the ability to express themselves fully with these techniques. In role playing, for example, the skills of acting may make some participants more articulate at expressing their feelings compared with others. The same may be said of techniques where pictures and cartoons are put together and interpreted, in that distinctive skills may make certain participants more adept and comfortable in expressing themselves. To counter this, one could argue that there is a great amount of skill required in articulating ideas and feelings in an open-ended in-depth interview. One could point to fiction writers or poets who are able to encapsulate particular feelings most clearly and succinctly, which, again, is enormously skilful. With such skill requirements, the disadvantage of the technique lies in the nature of the participants who agree to participate, and how characteristic they may be of distinct target markets.

Applications of projective techniques Projective techniques are used less frequently than unstructured direct methods (focus groups and in-depth interviews). A possible exception may be word association, which is commonly used to test brand names and occasionally to measure attitudes about particular products, brands, packages or advertisements. As the examples have shown, projective techniques can be used in a variety of situations.49 The usefulness of these techniques is enhanced when the following guidelines are observed. Projective techniques should be used: 1 Because the required information cannot be accurately obtained by direct questioning. 2 In an exploratory manner to elicit issues that participants find difficult to conceive and express. 3 To engage participants in the subject, by having fun in expressing themselves in interesting and novel ways.

Comparison between qualitative techniques To summarise comparisons between qualitative techniques, Table 8.1 gives a relative comparison of focus groups, in-depth interviews, projective techniques and ethnographic approaches (qualitative observation). The nature of qualitative research is such that, within the broad categories above, there are numerous variations of the techniques with distinct strengths and weaknesses in eliciting and representing consumer feelings. Really, it is not possible to say that one technique is better or worse than the other. Faced with a given problem, it would seem to be the case of deciding which technique is the most appropriate to represent or understand consumers.50 What may affect this choice is the confidence that marketing decision makers may have in particular techniques. Thus, for example, any number of arguments may be made for the use of a projective technique as being the best way to tackle a sensitive issue indirectly. However, if the marketer who has to use the research findings does not believe it to be a trustworthy technique, then other, perhaps less appropriate, techniques may have to be used.

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Table 8.1

A comparison of focus groups, in-depth interviews, projective techniques and ethnographic techniques

Criteria

Focus groups

In-depth interviews

Projective techniques

Ethnographic techniques

Degree of structure

Can vary from highly to loosely structured

Tends to be loosely structured

Loosely structured though can have a framework to guide observation

Probing of individual participants

Low

High

Medium

None when used in isolation and in a covert manner

Moderator bias

Medium

Relatively high

Low to high

None when used in isolation and in a covert manner

Uncovering subcon sciousinformation

Low

Medium to high

High

Discovering innovative information

High

Medium

Low

Medium

Obtaining sensitive information

Low

Medium

High

Involving unusual behaviour or questioning

To a limited extent

Yes

Perhaps on the part of the observer

Summary

The qualitative techniques of in-depth interviewing allow researchers to focus upon individuals with the qualities they deem to be important to their research objectives. With a ‘quality individual’ the researcher can question and probe to great depth and elicit a quality understanding of that individual’s behaviour or feelings. The technique is well suited to tackling commercially and personally sensitive issues. It is also well suited to interviewing children. There are many types of interview that can be applied under the term ‘in-depth interview’. They can range from the very open and unstructured to semistructured exchanges. The application of structure in an in-depth interview can be founded on a theoretical underpinning of how individuals should be questioned and probed. Three relevant and widely used examples of interviews using a theoretical underpinning are laddering, repertory grid techniques and the Zaltman metaphor elicitation technique (ZMET). Laddering seeks to reveal chains of attributes, consequences and values that participants associate with products. The repertory grid seeks to elicit the underlying elements and the connection of those elements, related to a particular form of consumer behaviour. ZMET seeks to understand the images and associations that underpin both spoken and tacit thoughts and feelings through the elicitation of both rational and emotional thinking. Indirect projective techniques aim to project the participant’s motivations, beliefs, attitudes and feelings onto ambiguous situations. Projective techniques may be classified as association (word association), completion (sentence completion, story completion), construction (picture response, cartoon tests) and expressive (role playing,

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third-person personification) techniques. Projective techniques are particularly useful when participants are unwilling or unable to provide the required information by direct methods. The qualitative researcher needs to develop an understanding of the interplay between characteristics of the target participants, the issues they will be questioned about and the context in which they will be questioned. The context can be broken down into the physical location of the interview and the protocol of starting, running and terminating the interview. Building up this understanding is vital to the success of conducting in-depth interviews and projective techniques in international markets. The marketing research industry is concerned about how qualitative research participants are handled in interviews and observations. More consumers are being questioned in both domestic and business scenarios. If they are to ‘open up’ and reveal deeply held feelings, perhaps in front of a group of strangers, or if they are to take part in projective techniques that they may see as being unorthodox, they have to be reassured of how the data captured will be used. Technology has opened up many possibilities to conduct in-depth interviews and use projective techniques on a global basis. A rich dialogue and engagement between an interviewer and a participant can be developed and recorded with much lower cost and time demands when compared with meeting face to face. The loss of subtle eye contact and body language may be a price to pay for the savings afforded by online research.

Questions

1 What is an in-depth interview? Summarise the process of administering an in-depth interview. 2 What are the major advantages of in-depth interviews? 3 What are the requirements of the researcher undertaking in-depth interviews? Why are these requirements particularly important when conducting interviews with managers? 4 Why may a structure be applied to the in-depth interview in the form of laddering or the repertory grid technique? 5 Describe the process of administering the repertory grid technique. 6 Evaluate the context and timing requirements that you think would be needed to make the repertory grid technique work. 7 Choose any particular application of an in-depth interview and present a case for why you think the technique may work much better than a focus group. 8 What are projective techniques? In what circumstances should projective techniques be used? 9 Describe the ‘word association’ technique. Give an example of a situation in which this technique is especially useful. 10 Describe the ‘story completion’ technique. Give an example of the type of participant and the context in which such a technique would work. 11 Describe the criteria by which researchers may evaluate the relative worth of qualitative techniques. 12 Why is the context of questioning particularly important when conducting in-depth interviews in international marketing research?

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13 Why may in-depth interviews or projective techniques upset or disturb participants? 14 Describe a projective technique that you feel would work particularly well online – without the use of webcams. 15 What limitations are there to conducting in-depth interviews online, compared with meeting participants face to face?

Exercises

1 Could an in-depth interview about the phenomenon of online casinos be conducted online? Present a case for how you would conduct such interviews and set out what you see as the advantages and disadvantages of this approach. 2 Baileys Irish Cream wishes to better understand customer experiences of serving and enjoying its drink. Develop a cartoon test for this purpose. 3 A cosmetics firm would like to increase its penetration of the student market through a new range of organic and ‘ethical’ products. Conduct two experimental in-depth interviews with a male and female student. Write a report setting out plans for any subsequent form of in-depth interviews and associated techniques, showing how the experimental interviews have impacted upon these plans. 4 Jeffery West shoes (www.jeffery-west.co.uk) wishes to develop an understanding of its brand personality. Design a role-playing scenario that will help to achieve this aim. Who would you invite to the sessions? Where would you run the sessions? What roles would you ask the participants to play? 5 In a small group discuss the following issues: ‘Are there any dangers (for researchers and participants) in conducting in-depth studies on issues that participants hardly reflect upon on a day-to-day basis?’ and ‘Projective techniques cannot work well with shy and introverted participants.’

Video case exercise: Acme Whistles Acme wishes to conduct in-depth interviews with b2b buyers who purchase (orcould purchase) its whistles for sports-related applications. How would you recommend Acme conducts such interviews with participants spread across the globe? Create a topic guide that would help you to question participants about their purchasing behaviour. How could you use these interviews to support the development of new products?

Notes 1. Rédier, E. and McClure, S., ‘Let the product talk’, ESOMAR Fragrance Conference, Paris (November 2007). 2. Supphellen, M., ‘Understanding core brand equity: Guidelines for in-depth elicitation of brand associations’, International Journal of Market Research 42 (3) (2000), 319–42; Harris, L.M., ‘Expanding horizons’, Marketing

Research: A Magazine of Management and Application 8 (2) (Summer 1996), 12. 3. Kvale, S., Interviews: An Introduction to Qualitative Research Interviewing (Thousand Oaks, CA: Sage, 1996); Rubin, H.J. and Rubin, I.S., Qualitative Interviewing: The Art of Hearing Data (Thousand Oaks, CA: Sage, 1995).

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4. Warren, C.A.B., ‘Qualitative interviewing’, in Gubrium, J.F. and Holstein, J.A. (eds), Handbook of Interview Research: Context and Method (Thousand Oaks, CA: Sage, 2002), 83–101. 5. Johnson, J.M., ‘In-depth Interviewing’, in Gubrium, J.F. and Holstein, J.A. (eds), Handbook of Interview Research: Context and Method (Thousand Oaks, CA: Sage, 2002), 104. 6. Ibid., pp. 106–7. 7. Schwalbe, M.L. and Wolkomir, M., ‘Interviewing men’, in Gubrium, J.F. and Holstein, J.A. (eds), Handbook of Interview Research: Context and Method (Thousand Oaks, CA: Sage, 2002), 203–20. 8. Schnee, R.K., ‘Uncovering consumers’ deepest feelings using psychologically probing qualitative research techniques’, Advertising Research Foundation Workshops, ‘Consumer Insights Workshop’ (October 2000); ‘Looking for a deeper meaning’, Marketing (Market Research Top 75 Supplement) (17 July 1997), 16–17. 9. Arnal, L. and Holguin, R., ‘Taxis, vans and subways: Capturing insights while commuting’, ESOMAR Qualitative Research, Paris (November 2007). 10. Bloom, N., ‘In-depth research? A bit controversial!’, ResearchPlus (June 1993), 12. 11. Bowman, J., ‘When everything Clicks into place’, Research World (December 2006), 31. 12. Baxter, S., ‘It’s not kids’ play! Reflecting on the child-orientated research experience’, International Journal of Market Research 53 (1) (2011), 63–74. 13. Clarke, B., Goodchild, M. and Harrison, A., ‘The digital world of children and young adolescents: Children’s emotional engagement with digital media’, ESOMAR Congress Odyssey, Athens (September 2010). 14. Parke, A., ‘When not to rely on the young imagination’, ResearchPlus (March 1997), 14. 15. Milling, A., ‘Don’t supersize me’, Research (November 2005), 38–9. 16. Rédier, E. and McClure, S., ‘Let the product talk’, ESOMAR Fragrance Conference, Paris (November 2007). 17. Bakken, D.G. and Breglio, V.J., ‘Cultural differences in consumer decision-making – Asian consumers, western research methods: What we’ve learned’, ESOMAR Asia Pacific Conference, Tokyo (March 2005); De Andrade Marseilles Reis, A.H.M., ‘Laddering: An efficient tool for the formation of product positioning strategies and ways of communication’, The Dynamics of Change in Latin America, ESOMAR Conference, Rio de Janeiro (1997). 18. Dichter, E., The Strategy of Desire (New York: Doubleday, 1960). 19. Reynolds, T., Gutman, J. and Craddock, A., ‘The MECCAS framework to advertising strategy’, Brand Management Models (2006), 230–1; Gutman, J., ‘Laddering: Extending the repertory grid methodology to construct attribute-consequence-value hierarchies’, in Heath, D.C. (ed.), Personal Values and Consumer Psychology (Lanham, MD: Lexington Books, 1984). 20. For example, Grunert, G.K. and Grunert, S.C., ‘Measuring subjective meaning structures by the laddering method: Theoretical considerations and methodological problems’, International Journal of Research in Marketing 12 (1995) 209–25.

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38. Zaichowsky, J.L., ‘The why of consumption: Contemporary perspectives and consumer motives, goals, and desires’, Academy of Marketing Science 30 (2) (Spring 2002), 179; Levy, S.J., ‘Interpreting consumer mythology: Structural approach to consumer behaviour focuses on story telling’, Marketing Management 2 (4) (1994), 4–9. 39. Burden, S., ‘Case study: Pre-testing mould breaking ads’, Admap Magazine, 485 (July/August 2007), 48–9. 40. Catterall, M., ‘Using projective techniques in education research’, British Educational Research Journal 26 (2) (April 2000), 245–56; Kennedy, M.M., ‘So how’m I doing?’, Across the Board 34 (6) (June 1997), 53–4; Lindzey, G., ‘On the classification of projective techniques’, Psychological Bulletin (1959), 158–68. 41. Byron, E., ‘How P&G led also ran to sweet smell of success’, Wall Street Journal (4 September, 2007), B2; Walsh, K., ‘Soaps and detergents’, Chemical Week 164 (3) (23 January 2002), 24–6; ‘Interpretation is the essence of projective research techniques’, Marketing News (28 September 1984), 20. 42. Grimes, A. and Kitchen, P., ‘Researching mere exposure effects to advertising – theoretical foundations and methodological implications’, International Journal of Market Research 49 (2) (2007), 191–219. 43. Clarke, B., ‘If this child were a car, what sort of car would it be? The global child: Using appropriate projective techniques to view the world through their eyes’, ESOMAR Qualitative Research, Cannes (November 2004); Suprenant, C., Churchill, G.A. and Kinnear, T.C. (eds), ‘Can role playing be substituted for actual consumption?’, Advances in Consumer Research (Provo, UT: Association for Consumer Research, 1984), 122–6. 44. Anon., ‘Coors – Coors Light’, Institute of Communication Agencies, Silver, Canadian Advertising Success Stories (2007).

45. Maehle, N. and Supphellen, M., ‘In search of the sources of brand personality’, International Journal of Market Research 53 (1) (2011), 95–114. 46. Strachan, J. and Pavie-Latour, V., ‘Forum – food for thought: Shouldn’t we actually target food advertising more towards kids and not less?’, International Journal of Market Research 50 (1) (2008), 13–27. 47. Branthwaite, A. and Patterson, S., ‘The vitality of qualitative research in the era of blogs and tweeting: An anatomy of contemporary research methods’, ESOMAR Qualitative, Barcelona (November 2010). 48. McPhee, N. and Chrystal, G., ‘Who’s eaten my porridge? Discovering brand image differences’, ESOMAR Healthcare Conference, Rome (February 2008); Gill, J., and Johnson, P., Research Methods for Managers, 3rd edn (Thousand Oaks, CA: Sage, 2002); Varki, S., Cooil, B. and Rust, R.T., ‘Modeling fuzzy data in qualitative marketing research’, Journal of Marketing Research 37 (4) (November 2000), 480–9. 49. For more on projective techniques, see Burden, S., ‘Emotional…but does it sell?’, Admap 496 (July/August 2008), 41–2; Clarke, B., ‘If this child were a car, what sort of car would it be? The global child: Using appropriate projective techniques to view the world through their eyes’, ESOMAR Qualitative Research, Cannes (November 2004); Valentine, V. and Evans, M., ‘The dark side of the onion: Rethinking the meaning of “rational” and “emotional” responses’, Journal of the Market Research Society 35 (April 1993), 125–44. 50. Branthwaite, A. and Cooper, P., ‘A new role for projective techniques’, ESOMAR Qualitative Research, Budapest (October 2001), 236–63.

9 Stage 1

Problem definition

Stage 2 Research approach developed

Stage 3 Research design developed

Stage 4 Fieldwork or data collection

Stage 5 Data integrity and analysis

Stage 6 Communicating research findings

Qualitative research: data analysis Qualitative analysis involves the process of making sense of data that are not expressed in numbers.

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Objectives After reading this chapter, you should be able to: 1 understand the importance of qualitative researchers being able to reflect upon and understand the social and cultural values that shape the way they gather and interpret qualitative data; 2 describe the stages involved in analysing qualitative data; 3 describe the array of data types that qualify as qualitative data; 4 explain the nature and role of coding in the stage of reducing qualitative data; 5 appreciate the benefits of being able to display the meaning and structure that qualitative researchers see in their data; 6 understand why qualitative data analysis pervades the whole process of data gathering and why the stages of analysis are iterative; 7 appreciate the nature and roles of grounded theory, content analysis and semiotics in qualitative data analysis; 8 understand the ethical implications of the ways that qualitative researchers interpret data; 9 appreciate the strengths and weaknesses of analysing data using qualitative analysis software.

Overview The application of qualitative techniques is not necessarily a predefined and structured process. In the majority of instances, qualitative researchers modify their direction as they learn what and who they should focus their attention upon. Data-gathering techniques, the nature of participants and the issues explored can change and evolve as a project develops. This chapter starts by examining how researchers reflect upon what happens to the way they perceive and observe as these changes unfold. It discusses how these reflections form a key source of qualitative data to complement the narrative generated from interviews and observations. The stages involved in a generic process of analysing qualitative data are outlined and described. The first stage of the process involves assembling qualitative data in their rich and varying formats. The second stage progresses to reducing the data, i.e. selecting, classifying and connecting data that researchers believe to be of the greatest significance. A key element of this stage is the concept of coding. The third stage involves the display of data, i.e. using graphical means to display the meaning and structure that researchers see in the data they have collected. Manual and electronic means of displaying data are discussed. The final stage involves verifying the data. Researchers aim to generate the most valid interpretation of the data they collect, which may be supported by existing theories or through the concept of theoretical sampling. Though these stages seem quite distinct, the reality is that they are iterative and totally interdependent upon each other; the stages unfold in ‘waves’ to produce an ultimate interpretation that should be of great value to decision makers. Three alternative perspectives on analysing qualitative data are presented. First, the purpose and concept of grounded theory are discussed, with the stages involved in building theory. Second, content analysis is presented, a much simpler approach to analysing qualitative data, which is sometimes viewed as a quantitative technique. Third, the purpose and concept of semiotics are presented. This approach adopts the view that consumers should be viewed as products of culture, constructed and largely determined by the popular culture within which they live. It allows for the integrated analysis of cues that emerge from text, pictures and sounds. The social and cultural values of qualitative researchers affect how they gather and analyse data. Understanding the social and cultural norms of participants in international environments is discussed. The social and cultural values of researchers affect their interpretation of qualitative data, and the ethical implications of not reflecting upon these values are addressed.

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The digital applications in the stages of qualitative data collection and analyses are described. There are many distinct advantages to the use of qualitative data analysis software, but many researchers contend that it should be a ‘hands-on’ process that cannot be mechanised. The arguments from both of these perspectives are presented. To be able to cope with the great amount of data generated from qualitative techniques, a great variety of software packages are available. Examples of analysis software are briefly described, followed by website addresses that allow demonstration versions of the software to be downloaded and explored. NVivo, a qualitative data analysis package specifically designed for researchers, is also presented.

The qualitative researcher Self-reflection of social and cultural values In Chapter 2, when discussing the diagnosis of research problems, we stated: A major problem for researchers is that their perception of problems may be reflected through their own social and cultural development. Before defining the problem, researchers should reflect upon their unconscious reference to cultural values . . . The unconscious reference to cultural values can be seen to account for these differences. This implies that researchers need to reflect upon their own values and attitudes – the factors that may bias the way they perceive and what they observe. This reflection is just as important in the analysis of qualitative data as it is in the diagnosis of research problems. To illustrate why researchers need to reflect upon what may bias the way they perceive and what they observe, we start this chapter with an example from the world of literature and the treatment of narrative. The example is a précis of an English translation of a Japanese novel; the example could be taken from any novel.

Real research

South of the Border, West of the Sun1 This novel tells the story of an only child, Hajime, growing up in the suburbs of postwar Japan. His childhood sweetheart and sole companion in childhood was Shimamoto, also an only child. As children they spent long afternoons listening to her father’s record collection. When Hajime’s family moved away, the childhood sweethearts lost touch. The story moves to Hajime in his thirties. After a decade of drifting he has found happiness with his loving wife and two daughters, and success in running a jazz bar. Then Shimamoto reappears. She is beautiful, intense, enveloped in mystery. Hajime is catapulted into the past, putting at risk all he has at the present.

Imagine that you had been asked to read this novel, but before you read it you were expected to prepare by reading a description of conditions in postwar Japan. From that you might appreciate the significance of a record collection of 15 albums, and how privileged a family may be to own a record player and to have this collection. Imagine someone else being asked to prepare by reading a biography of the author. From that you might appreciate the social and economic conditions of his upbringing, the literature, music and education that he enjoyed. Preparing to read the novel in these two ways may mean that a reader sees very different things in the story. The reader may interpret passages differently, have a different

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emotional attachment with the conditions and behaviour of the characters, and appreciate the effect of quite subtle events upon the characters. Put aside any prior reading and imagine a female reader enjoying the book. She may empathise with the main female character, Shimamoto, and understand her attitudes, values and behaviour in the way that male readers may not be able to comprehend. In the story, Shimamoto suffered from polio as a child, which made her drag her left leg. Imagine a reader who has had to cope with a disability and who may appreciate how, as a child, one copes with the teasing of other young children. The two main characters were ‘only children’; imagine a reader who was an only child and who can recall how he or she would view large families and appreciate the joys, disappointments and array of emotions of being an only child. The list could go on of the different perspectives of the story that may be seen. The reader, with their inherent values and attitudes, may perceive many different things happening in the story. The reader does not normally reflect upon their unconscious values and attitudes, but just enjoys the story. In talking to others about the story, the reader might be surprised about how others see it. In watching the film version of the book, the reader might be shocked at the different images the film director presents, images that are very different from the one that resides in the reader’s head. Now consider whether there is one ultimate interpretation of the novel, one ultimate ‘truth’. It is very difficult to conceive that there is one ultimate interpretation. One may question why anyone would want to achieve such a thing; surely the enjoyment of literature is the ability to have multiple interpretations and ‘truths’ of a novel?2

Narrative for the qualitative researcher What is the link from the interpretation of a novel to qualitative data analysis in marketing research? Quite simply, the qualitative researcher builds up a narrative and creates a story of the consumers whom decision makers wish to understand. Imagine yourself as a qualitative researcher, supporting decision makers who wish to develop advertisements for an expensive ride-on lawnmower. The key target market they wish to understand is ‘wealthy men, over the age of 60, who own a home(s) with at least 1 hectare of garden’. The decisions they face may include the understanding of: 1 What gardening and cutting grass mean to target consumers. 2 How they feel about the experience of buying and using a lawnmower. 3 What relative values (tangible and intangible) are inherent in different brands of lawnmower. 4 What satisfaction they get from the completed job of mowing a large lawn. 5 The nature and qualities of celebrities they admire (who may be used to endorse and use the product in an advertisement). These questions may be tackled through the use of focus groups. Imagine yourself running these groups. What could you bring to the groups if you have personally gone through the experience of buying an expensive ride-on lawnmower and have gardening and lawnmowing experiences? You may have an empathy with the participants in the same manner as the ‘only child’ reading of the experiences and emotions of an only child in a story. From this empathy, you may be able to question, probe and interpret the participants’ answers really well, drawing an enormous amount from them. Without those experiences you may have to devise ways to ‘step into the shoes’ of the participants. You may look to the attitudes, values and behaviour of your parents, grandparents or friends for a start, looking for reference points that you are comfortable with, that make sense to you. As you go through a pilot or experimental focus group, you may be surprised by certain participants talking about their lawnmowers as ‘friends’, giving them pet names and devoting lavish care and

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attention upon them. Getting an insight into this may mean looking at cases from past research projects or literature from analogous situations, such as descriptions of men forming a ‘bond’ with their cars. The direction that qualitative researchers take in building up their understanding and ultimately their narrative is shaped by two factors. The first factor is the theoretical understanding of the researchers as they collect and analyse the data. This theoretical understanding can be viewed from two perspectives. The first is the use of theory published in secondary data, intelligence and literature. The use of theory from these sources may help the researchers to understand what they should focus their attention upon, in their questioning, probing, observations and interpretations. The second is the use of theory from a grounded theory perspective. The researchers may see limitations in existing theory that do not match the observations they are making. These limitations help the researchers to form the focus of their questioning, probing, observations and interpretations. The second factor that shapes the direction that the researchers take is a marketing understanding. In the case of understanding the wealthy male lawnmower owner, the researchers need to understand what marketing decision makers are going to do with the story they create. The researchers need to appreciate the decisions faced in creating an advertisement, building a communications campaign or perhaps changing features of the product. Reference to theoretical and marketing understanding in researchers helps them to present the most valid interpretation of their story to decision makers. Unlike writing a novel, where the author is happy for the readers to take their own ‘truth’, researchers are seeking an ultimate interpretation and validity in their story. Achieving a valid interpretation enables the researchers to convey to decision makers a vision or picture of a target market that they can quickly ‘step into’. Marketing decision makers, for example, may wish to include a passage of music in an advertisement that the target market has an emotional attachment to, which they find positive and uplifting. With a rich picture or vision of this target market they may be able to choose the right piece of music. The decision makers’ cultural and social development may mean that the piece of music is meaningless to them, but you as a researcher have given them the confidence and enabled them to step into the world of the target market. The following example illustrates how qualitative research, based upon blogging via mobile devices, helped the Knorr brand to understand the characteristics, behaviour and views of a very distinctive target market.

Real research

Tokyo Girls Collection metrics3 In Japan, Knorr wished to develop a new Soup Pasta to target the primary gourmets of noodle cuisine: younger, female consumers. The hardest question Knorr faced was how to develop a Soup Pasta that fitted the target segment’s taste preferences. To generate and commercialise the product successfully, the company needed frank and honest opinions from young, female consumers during the idea generation, idea screening, concept development, product design and detailed engineering phases. In order to do this, Knorr decided to tie its new-product development project to the Tokyo Girls Collection (TGC). The TGC was a twice-annual celebration of ‘all things cute’, organised by Girlswalker.com magazine to showcase the season’s fashionable streetwear. The fashion event included such attractions as live performances by renowned artists, a charity auction and the final stage selection and presentation of the TGC Contest. The fashion show used only amateur models, known as ‘Dokusha moderu’ (in English, ‘reader models’), chosen from trendsetting girls’ magazines, such as Vivi or Ray. The TGC exemplified a grassroots movement that has become so huge in Japan that it has rendered the traditional fashion houses anachronistic. Many previous TGC tie-up campaigns have proven very successful, because young

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female consumers tended to spread the word about their favourite brands. Knorr’s newproduct development project was announced at the TGC venue, with star TGC models assigned as official new Soup Pasta development project members. Knorr launched the mobile Girlswalker.com site, where TGC project members described the product development process in their blogs. Knorr’s blogging project to support its new Soup Pasta development was an ideal way for it to generate such openness. The TGC served as a critical mental and symbolic venue for the virtual discussions.

The researcher’s learning as qualitative data Qualitative researchers have to reflect upon their own social and cultural development, their own attitudes and values, to see how these have shaped the narrative and how they shape their interpretation of the narrative. The researchers should recognise their own limitations and the need to develop and learn; in the cases above, this means learning about wealthy men and their relationship with lawnmowers or Japanese girls and their relationships with soup and fashion. Ultimately they wish to present the most valid story that they see, to have examined the story from many perspectives, to have immersed themselves in the world of their target markets. The following example illustrates the research impact of not recognising one’s own biases and social/cultural conditioning.

Real research

We see our own beliefs reflected in research4 Different advertising agencies cherish different beliefs about what will work and what will not work in an advertisement. Take, for instance, ‘influencing lifestyle’ (such as: drive less, drink less, stop smoking, don’t drink and drive). In this field, there are at least two different schools. One school promotes the ‘confrontation’ strategy; show the negative effects of behaviour as extremely as possible; show cancerous lungs in an anti-smoking campaign; show the remorseful victims of smoking-related diseases. Another school feels that such an approach does not really work, because the consumers will actively shut their system off from this kind of information, countering it with arguments such as ‘I have to die anyway’ or ‘I never have a problem drinking and driving’. This school claims that you can better focus on a more positive approach, or an approach that avoids showing negative consequences. Both schools will be able to find proof for their ideas, and both will tend to open up to reality supporting their ideas, avoiding evidence that goes against their views. In conducting research, both schools will find their views supported by consumers, one asking for ‘extreme examples’, the other claiming to be immune to such an approach and asking for a more positive approach. From the observations of Dutch researchers Jochum Stienstra (www.ferro-mco.nl) and Wim van der Noort (http:// english.minaz.nl) in viewing focus group discussions, the participant that gives ‘the right answer’ is embraced: ‘You see, I knew it, scaring them off doesn’t work.’ Two participants later, another communication manager or researcher will hear proof of the opposite opinion: ‘This is exactly what I mean. They are asking for extreme emotions, otherwise they won’t listen.’ They contend that research that tries to find the right communication approach involves a danger: you might end up finding what you already thought was right, or – even worse – you might find an internal quarrel aggravated since both schools will find their standpoint proved. This means that research as we know it cannot help us out, cannot transfer the problem from the realms of belief to the realms of ‘proof’.

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If you are reading a novel, you may not be inclined to make notes as your reading progresses. You may not make notes of other books to read that may help you to understand the condition of particular characters, or to understand the environment in which they behave. You may not wish to write down the way that you change and learn as you read through the story. A reflection of your unconscious social and cultural values as revealed through your interpretation of the novel may be the last thing you want to do. As a qualitative researcher you need to do all the above as you build and interpret your story of target consumers. A notebook or diary should be on hand to note new question areas or probes you wish to tackle, and to reflect upon how they have worked. As interviews unfold and you feel your own development and understanding progress, a note of these feelings should be made. As you seek out specific secondary data, intelligence or theory to develop your understanding, you should note why. If you see limitations in existing theories or ideas, you should note why. As an understanding of how decision makers can use the observations that are being made, these should be recorded. Included in these notes should be feelings of failure to ask the right question or probe, emotional states should be noted, of feeling up or down, sad or angry, or nervous.5 Ultimately, the story that emerges in your own notebook should be a revelation of your own social and cultural values. There should be an explicit desire to develop this self-awareness and understand how it has shaped the direction of an investigation and the ultimate story that emerges. The creation and development of the researcher’s notebook is a major part of the narrative that is vital to the successful interpretation of questions and observations of consumers. The key lesson that emerges from the creation and development of the researcher’s notebook is that qualitative data analysis is an ongoing process through all stages of data collection, not just when the data have been collected:6 Analysis is a pervasive activity throughout the life of a research project. Analysis is not simply one of the later stages of research, to be followed by an equally separate phase of ‘writing up results’. The evolution of questions and probes, deciding who should be targeted for questions and observations and even deciding the context for questioning or observing, means that analysis takes place as data are being gathered.

The process of qualitative data analysis We examine four perspectives of analysing qualitative data, starting with a generic process. Many of the terms used here differ from those linked to specific types of software or to researchers who follow a particular theoretical approach derived from a specific discipline. The generic process outlined is designed to give an understanding of what is involved in qualitative data analysis and how the stages link and interact. The four stages of the generic process are outlined in Figure 9.1. The concept of coding is introduced in this section – a vital concept to understand in all approaches to analysing qualitative data. The second perspective presented is the concept of grounded theory. The third perspective is the process of content analysis. The fourth is the discipline of semiotics.

Data assembly Data assembly

Data assembly means the gathering of data from a variety of sources. These would include:

The gathering of data from a variety of disparate sources.

1 Notes taken during or after interviewing or observations. 2 Reflections of researchers, moderators or observers involved in the data-collection process. 3 Theoretical support – from secondary data, intelligence or literature sources.

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Figure 9.1 Data assembly

Stages of qualitative data analysis

Data reduction

Data display

Data verification

4 Documents produced by or sourced from participants. 5 Photographs, drawings, diagrams, i.e. still visual images. 6 Audiotape recordings and transcripts of those recordings. 7 Video recordings. 8 Records made by participants, such as mood boards or collages.

Field notes A log or diary of observations, events and reflections made by a researcher as a study is planned, implemented and analysed.

As discussed in the previous section, the researcher should get into the habit of maintaining a notebook, diary or field notes. As a qualitative investigation evolves in terms of the issues to explore and the participants to target, the researcher goes through a learning process. This learning process means that the researcher may see things differently as interviews or observations progress. Keeping field notes aids the researcher’s memory when it comes to the formal process of data analysis and helps enormously in categorising and interpreting collected data. It ultimately helps to generate a ‘deeper and more general sense of what is happening’. In order to create a ‘deeper and more general sense of what is happening’, it is suggested7 that researchers keep four separate sets of notes in order to systematise the process and thus improve their reliability: 1 Short notes made at the time of observation or interview. 2 Expanded notes made as soon as possible after each session of interviews or observations. 3 A fieldwork journal to record problems and ideas that arise during each stage of fieldwork. 4 A provisional running record of analysis and interpretation. Data assembly also includes deciding lines of enquiry that should be developed and those that should be dropped. Given that qualitative research is primarily exploratory in nature, questions and probes are not fixed. As an interview or observation takes place, the researcher learns more about an issue and can develop a new question or probe and decide that a question, initially thought to be vital, is no longer relevant. There may be issues that can be compared over a series of interviews or observations, but the whole data collection and data assembly can evolve. Keeping notes is vital, as memory alone is fallible, unreliable and potentially biased. Being able to recall, for example, the hesitation in replying to a question displayed by a focus-group participant may, upon reflection, be seen as someone evading the issue. After all the group discussions have been completed and the same question has been

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posed to others, the interpretation may change to the individual being embarrassed about an issue, primarily through becoming aware of their own ignorance. The researchers’ notes help them to recall how they were feeling at the point of setting the question, and recall the situation in other groups that gives meaning to a pause that shows up as a quiet spot in an audio or video recording. The notes may also help the researcher appreciate what is happening when laughter occurs by participants in qualitative techniques. Interpreting the meaning of laughter presents one challenge for researchers. When humour is present, group dynamics, the pitch and intensity of laughter, or even the sly smile that masks a feeling that something is incredibly funny would need to be recorded in the researcher’s notes, to set a context to the narrative of any discussion. The same challenges are faced in the example below, which deals with the nature of silence in an interview; what does a particular silence mean? The researcher’s notes at the time of the silence may hold vital clues to what is being felt by participants but not expressed.

Real research

Listening to the sounds of silence8 My in-depth interview went really badly! It was full of long silences . . . my participants just would not open up!! This is a cry from researchers who believe that discussions that are not full of verbal give and take have not ‘got going’. Many fail to understand that the silence received in response to the question asked may have told the researchers what they needed to know. The way people communicate is deeply linked with the culture, values and norms of a society. If one understands the reason for the silence, one can end up with a far stronger set of findings and interpretations. The following is based on the reflections of over 200 focus group discussions and 100 in-depth interviews conducted in different parts of India by Shobha Prasad (www.drshti.com). Silence in India could be based on the social structure between castes. For example, a study conducted in rural Rajasthan among young men ran into severe issues arising from mingling of castes within the focus group. There were demarcated places where castes were allowed to mingle and communicate; they would talk to each other outdoors but not indoors. It was only when some of the participants were taken out of the group that others opened up to voice their opinions. Language block was occasionally encountered where sessions were conducted in Hindi and participants had differing levels of comfort with the language. In some sessions, more educated participants would express themselves in English, creating a sense of inequality in the group. Those who were less educated would then become quiet unless the researcher directly addressed them and tried to draw them back into the discussion. Indians rarely contained strong emotions in silence; they tended to let these feelings out through words. Therefore silences resulting from the two extremes – extreme positive and extreme negative emotion – were rare and if they occurred were short-lived. ‘Extreme delight’ was very rarely silent. Extreme negativity tended to result in a short silence, which very often just ‘broke itself’. The body language accompanying strong negative emotions was very obvious: a closed expression, folded arms, rigid body and refusal to make eye contact. In some cases participants would whisper among themselves. The slightest direct probe was usually adequate to get a verbalisation of these thoughts. The more common causes for silence among both women and men was incomprehension, confusion and feelings of inadequacy, and a lack of confidence. These reasons generally came to light as the session went on, when at some point, in response to a probe, participants would admit to have been confused or bewildered.

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Unfortunately, the recording and use of field notes or a diary is limited in many qualitative marketing research projects. This may be due to the contents of such notes, which could include photographs and other non-verbal data sources. These are unavoidably ‘subjective’, being what the researcher has chosen to notice. They are developmental, representing the learning and self-reflection that the researcher goes through. The subjective choices are reasoned choices, where issues are deliberately included or excluded. Understanding the reasons for those choices, recognising the learning and self-development that can emerge from these notes, can add so much more depth and greater insight into qualitative data. By developing self-awareness, qualitative researchers can take a more balanced view of the data they collect as they realise many of their own biases and hidden agendas. Beyond taking notes or keeping a diary, many qualitative techniques make extensive use of material of a semi- or non-verbal nature, generated through participant tasks such as the use of projective techniques (as described in Chapter 8). These materials can include drawings, lists, stories, clay models or structures and collages of photographs, video footage and music. The commonly held view is that it is not these materials that should be analysed but the meanings attached to them by the participants who produced them.9 These meanings as narrative will have been captured as part of the recorded discussion, or are in the notes of the researcher.10 The materials themselves would normally be available during analysis, enabling the possibility to notice useful features such as consistencies and differences between participants. They can also be useful in communicating and illustrating findings. Other qualitative researchers go further, taking the view that it is legitimate to ‘read’ these materials in the absence of the participants who produced them. They would argue that significant and valid meaning can be extracted from them provided they have a strong theoretical basis to drawing their conclusions and meanings. This relationship between participants’ discourse and non-verbal materials mirrors the debate in using photography in ethnographic studies (a common occurrence in qualitative marketing research, where participants are given disposable or digital cameras to capture stills or moving images of their experiences). Many significant anthropological ethnographies dating from the mid-1920s onwards include photographs relating to the fieldwork. The question that faces anthropologists relates to why photographs may be used in analysis and the relationship, if any, between the photograph and the written text. It is difficult to generalise, but it seems to be the case that photographs have been included in ethnographic reports more for evidential than analytic purposes. The photographs serve essentially presentational and illustrative purposes rather than providing a focus for a more sustained analysis of the visual dimensions of culture.11 Such perspectives are radically changing as more visual ethnographic techniques gain prominence in qualitative marketing research, as illustrated in the following example.12

Real research

Participant photography in visual ethnography13 Visual ethnography is an anthropological approach that incorporates visuality throughout the research process. In a project designed to investigate the consumption of households, an exploratory, initial investigation was designed to expose the various ways that household shoppers engaged with the consumption spaces that they visited. A key aim was to have the householders focus on their shopping in as natural a way as possible and record this so that it could be discussed during an indepth interview. A researcher following participants on shopping trips was deemed to be quite intrusive, in that having a stranger along could affect the usual flow of the experience, no matter how much rapport was developed. It was important, however, to try to capture everyday practice as accurately as possible in order to bring to the

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investigation the real ways in which shoppers engaged with the process of consumption. The research process asked participants to keep a shopping log of all household expenditure over a period of two weeks. This was a straightforward procedure of putting all their receipts into a plastic wallet provided and noting any expenses without a receipt on a notepad. After the fortnight had elapsed they were interviewed using the receipts as prompts and following several themes derived from the literature. Another important element was the addition of a disposable camera. Researchers met with the shoppers and explained their part in the data-gathering process. This initial contact established a rapport before the interview proper, but it continued by explaining the research process and covering ethical issues. In addition, participants were issued with a disposable flash camera and asked to take photographs of anything interesting connected to their shopping. Prior to the in-depth interviews, the photographs were collected and added to the receipts and notes to facilitate probing and the development of issues.

The key feature of the use of photography and visuals is the subtlety of characteristics or events that can be captured and portrayed where words alone may be deficient. This feature has an impact for qualitative researchers for two reasons. The first can be seen from the perspective of qualitative technique participants. Certain participants may not be able to express what they feel about a product, service, advertisement, brand or any design element of their experiences solely using words. They may, however, be able to use visual cues from sources such as photographs to represent their feelings. The second can be seen from the perspective of decision makers who use qualitative research findings. Certain marketing decision makers working in visually creative fields, such as advertising, product and package design and branding, work better with visual data compared with words or statistics. They may understand the impact of how consumers feel and will react to their designs through very subtle interpretations of visual data. Given the importance of visual data to this type of decision maker, we explore the concept of semiotics later in this chapter.

Data reduction Data reduction The organising and structuring of qualitative data.

Transcripts ‘Hard copies’ of the questions and probes and the corresponding answers and responses in focus groups or in-depth interviews.

Data reduction involves handling the data. This process involves organising and structuring the data. It means having to throw some data away! Imagine a series of 10 focus group discussions and the amount of data that could be collected. There are the memories and notes of the moderator and any other observers who took part, there are the transcripts of what was actually said in interviews and there may be contributions from participants in the form of mood boards. The transcripts are a vital, and for most studies the, primary data source in qualitative data analysis, and much care should be taken in transcribing them. Transferring the dialogue from tape or digital devices can be tortuous as recordings are notoriously ‘unclear’. Imagine a focus group in full swing: not every participant takes their turn to speak without talking over other participants, and then they may not speak clearly and loudly enough. As a result it can take a great deal of time to work out what participants actually said and how the questions, responses and ideas connect together. In producing transcripts, it is much better for the researchers to work

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Coding data Breaking down qualitative data into discrete chunks and attaching a reference to those chunks of data.

through the recordings and piece together the components using their notes and memory of events. This is very time-consuming, so many researchers use typists to transcribe their recordings of i nterviews – arguing that their time is better spent reading through and editing transcripts produced in this manner. The use of online software for in-depth interviews and focus groups means that this time-consuming task is eliminated, as the transcript is built up as the interview progresses. The researchers with their transcripts, notes and other supporting material have to decide what is relevant in all these data. Reducing the data involves a process of coding data, which means breaking down the data into discrete chunks and attaching a reference to those chunks of data. Coding is a vital part of coping with qualitative data analysis and, given this importance, the process is discussed in some detail. Researchers need to be able to organise, manage and retrieve the most meaningful bits of qualitative data that they collect. This is normally done by assigning ‘labels’ or codes to the data, based upon what the researcher sees as a meaningful categorisation. What happens is that the researcher condenses the great mass of data from a study into analysable units by creating categories from the data.14 This process is termed the coding of data. Coding is the process of bringing together participants’ responses and other data sources into categories that form similar ideas, concepts, themes, or steps or stages in process. Coding can also enable the categorisation of names, evidence or time sequences. Any hesitations, emotional states or levels of humour can be coded. Indeed, anything that is felt to be revealing in the data can be coded. Data such as a simple response to a question can be coded in many different ways, or placed into many different categories; there is no expectation of mutual exclusivity, and data can be re-coded as often as is thought necessary.15 An illustration of coding is presented using the data presented in Table 9.1. This table presents the verbatim responses from an open-ended question in a self-completion survey targeted at 12 to 14 year olds. The question asked participants what facilities they would like in a planned new community centre. Though the technique used was quantitative, the survey generated qualitative data and, in its much shortened format, demonstrates the process that qualitative researchers must go through. In categorising the responses, the researcher could create codes of ‘swimming pool’ or ‘disco’ and count the times that these were literally expressed. Alternatively, the researcher could code on the basis of ‘sports activities’ or ‘recreational activities’ and group together activities such as ‘swimming, basketball and snooker’ for sports and ‘computers,

Table 9.1

Teenager requests for facilities at a planned community centre

Requested feature of new community centre

Gender

Skate park, death slide, basketball courts, swimming pool Computer room Stuff for all ages Swimming pool Computers, snooker room A space for computers, tuck shop Music, television, up-to-date magazines, pool tables Music, discos Swimming pool Music, pool/snooker, discos What people will enjoy All the things people enjoy

Male Male Male Male Male Male Female Female Female Female Female Female

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television, discos and tuck shop’ for recreational activities. The researcher could code ‘indoor activities’ and ‘outdoor activities’, or activities that would need supervision and those that would need no supervision. There are many ways that the researcher can categorise the data, it is their choice. Consider how the researcher may cope with the requests for a ‘computer room’ and ‘computers’. Could these be combined under one heading of ‘computing’ or would this lose the meaning of having a devoted space, away from other activities that could be noisy and distracting? Consider also how the researcher would cope with the requests for ‘stuff for all ages’, ‘what people will enjoy’ and ‘all the things people enjoy’. It may seem obvious that a new leisure centre needs to develop facilities that people enjoy and that these may be discarded, but there may be a hint in the first statement of ‘stuff for all ages’ that may link to the word ‘people’ used in the two other statements. If the researcher interprets the statements in this way, a category of ‘activities to draw in all ages’ could be created; these responses may be seen as tapping into a notion of a leisure centre that is welcoming and not exclusive. Table 9.2 presents a small selection of the verbatim responses from the same open-ended question in a self-completion survey, this time targeted at adults.

Table 9.2

Adult requests for facilities at a planned community centre

Requested feature of new community centre

Gender

Regard for residents living nearby, special car parking area to avoid streets nearby being jammed New centre would soon bring the wrong sort of people; it could form a centre for thugs and crime Strict rules so as to inconvenience local people living close by as little as possible, e.g. noise Run and organised well to run functions at affordable prices with dress rules for the lounge and bar Membership should be given on signature of applicants to a strict set of rules Emphasis on youth on the estate and run in a way to encourage rather than regiment them Supervised youth activities, daytime crèche, dance floor, serve coffee/soft drinks for youths Should be very welcoming and developed for all kinds of people Active participation by those using the facilities, which should give opportunities for the young To make a safe place for all people of all ages to enjoy Exterior should be modern; inside decorated tastefully with nice seats and tables, plenty of hall space Youth club with a youth leader, luncheon club for older groups and gentle keep-fit for the elderly

Male Male Male Male Male Male Female Female Female Female Female Female

The interesting feature in comparing the statements from the adults with those from the teenagers is how they express themselves in more detail and how they thought beyond specific facilities that make up the leisure centre. These statements were unprompted, so one can imagine how much richer the explanations and justifications would be with an in-depth interview or a focus group. Again, there are many ways that the researcher can categorise the data, perhaps even more than with the teenagers. Categorising these adult statements is not as straightforward as for the teenagers’. The researcher could draw out the words ‘youth’ or ‘rules’ and set these as categories. The researcher could pull out named ‘facilities’ such as ‘dance floor’ and ‘nice seats and tables’, or ‘activities’ such as ‘youth club’ and ‘luncheon club’. What becomes apparent in reading through the statements (especially with the full set of responses) are the implied problems related to issues of parking, the types of people that are attracted or could be attracted, and how ‘regimented’ or not the centre should be. These are categories or patterns that may be apparent to a researcher, though not explicitly expressed. There may be words expressed that make up the categories, but the words broken down and taken in isolation may lose their impact, if they are just counted.

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Table 9.2 illustrates that categorisation into the component words may mean that the contextual material that gives these words meaning can be lost. From the above example, coding can be thought of as a means to: 1 Retrieve data, i.e. from the whole mass of data, particular words or statements can be searched for and retrieved to examine the ‘fit’ with other words or statements. 2 Organise the data, i.e. words or statements can be reordered, put alongside each other and similarities and differences evaluated. 3 Interpret data, i.e. as words or statements are retrieved and organised in different ways, interpretations of the similarities and differences can be made. Coding is a process that enables the researchers to identify what they see as meaningful and to set the stage to draw conclusions and interpret meaning. Codes are essentially labels to assign meaning to the data compiled during a study. In broad terms, the coding process involves the following stages: 1 Set up a broad group of coding categories. These would emerge from an initial reading of the gathered data and the intended purpose of the study. For example, these may be the themes that structured a number of focus group interviews or in-depth interviews. 2 Work through the data to uncover ‘chunks’ of data that may be put into brackets or underlined or highlighted. Codes are usually attached to ‘chunks’ of varying size, i.e. words, phrases, sentences, paragraphs, an extended story, an image, indeed any component of the collected data, connected or unconnected to a specific context.16 Sometimes a single sentence or paragraph might be coded into several categories. For example, one paragraph where participants are overtly discussing parking problems at a community centre may also be discussing issues of ‘mobility’ or ‘independence’. Once the start and end of a chunk to be coded is established, a name or number is assigned to it. 3 Review the descriptions given to the codes. Working through the data, it may be clear that important themes emerging from the data do not fit into the pre-set categories, or that one theme blurs into two or more separate concepts. At this point new categories have to be set to fit the data. With new categories, the data must then be reviewed and recoded where appropriate. This stage therefore is one of immersion in the data and refining the nature of categories as more meaning is uncovered in the data. 4 Examine differences between types of participant. This could be simple demographic comparisons, e.g. to see if there are differences between men and women in how they view independence. The comparisons could be between types of participant that emerge from other codes, e.g. lifestyle aspirations may emerge from the data, with groups emerging that may be labelled ‘sophisticated minimalists’ and ‘spiritual warriors’. Comparisons of the behaviour between these emerging groups can be made. Through these comparisons, new insights may emerge about the assigned codes and the descriptors applied to them. New insights may also emerge about the way that participants are described and categorised, combining knowledge of their demographic, geographic, behavioural, psychographic and psychological characteristics. 5 Develop models of interconnectivity among the coded categories. This involves basic graphical modelling to explain a sequence of events or a process that the data describe. It could show how categories relate to each other, how participants may be alike or differ and how different contexts impact upon the categories and participants. Again, new insights may emerge about the meaning seen in the data, and the coding process may be further refined. 6 Iterate between the code descriptions and the developing model. This stage is again one of immersion in the data, with continual refining of the nature of categories and

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the structural relationship of those categories. These iterations continue until the researchers have what they believe to be the most valid meaning that they see in the data. The relative advantages and disadvantages of manual or electronic approaches to analysing qualitative data, and especially the iterative process of coding and modelling, are presented later in the chapter. The point to consider at this stage is that the immersion in the data to draw out meaning is not formulaic, especially as one considers the different types of qualitative data that can be included in analyses. Reducing qualitative data to the essence of meaning as seen by the researchers is a highly creative and subjective process. Given the time that may be allocated to this process, coding can be observed from two perspectives. First, if there is relatively little time for the researchers to immerse themselves in the data, it can be thought of as a means to simplify or reduce the mass of data. If an initial broad group of coding categories is kept and their number is relatively small, then the data can be ‘stripped down’ to a simple general form. This coding approach can be compared directly with simple forms of content analysis.17 Second, if more time can be afforded, it can be thought of as a means to expand, transform and reconceptualise data, opening up more diverse ideas and analytical possibilities. The general analytical approach is to open up the categories in order to interrogate them further, to try to identify and speculate about further features. Coding here is about going beyond the data, thinking creatively with the data, asking the data questions and generating theories and frameworks.18 Coding is a major process involved in data reduction. The process forces the researchers to focus upon what they believe to be the most valid meaning held in the data. In order to develop that meaning further, the researchers need to communicate their vision to others, to evaluate their interpretations of the data and to reflect upon their own vision. The stage of data display is the means by which researchers communicate their vision of meaning in the data.

Data display Data display Involves summarising and presenting the structure that is seen in collected qualitative data.

Data display is an organised, compressed assembly of information that permits conclusiondrawing and action.19 The most frequent form of display for qualitative data in the past has been extended text. Such an approach is cumbersome, dispersed and sequential, poorly structured and extremely bulky. The qualitative researcher can resolve these problems with the use of matrices, graphs, charts, networks or ‘word clouds’. All are designed to assemble information into an immediately accessible, compact form so that the analyst can see what is happening and either draw justified conclusions or move on to the next step of analysis the displays suggests may be useful. The creation and use of displays is not an end output of analysis, it is an integral part of the analytic process. For example, designing a matrix as a display involves decisions on what should be displayed in the rows and columns, and deciding what qualitative data, in which form, should be entered in the cells. Data display also allows a ‘public’ view of how the researcher has made connections between the different ‘data chunks’. Even if others may not have made the same connections or interpreted the data in exactly the same manner, the logic of connections should be clear. The display may be in a graphical format, with boxes summarising issues that have emerged and connecting arrows showing the interconnection between issues. Verbatim quotes can be used to illustrate the issues or the interconnections. Pictures, drawings, music or advertisements can also be used to illustrate issues or interconnections. The overall structure allows the decision maker who is to use the analysis to see the general meaning in the collected data. The illustration of issues or interconnections brings that meaning to life. One of the simplest means to display data is through the use of a spreadsheet. This can be built up and displayed in a manual or electronic format. Table 9.3 presents an example of how a spreadsheet may be set out. This spreadsheet is a sample of all the interviews that may be conducted and the number of issues that may be tackled. The example relates to a bus and tram operator that wishes to understand the attitudes and behaviour of 18 to 25 year olds

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Table 9.3

Spreadsheet data display of focus group discourse

Interviews?

Evening travel

Group 1: 18–25-year-old male car drivers

Group 2: 18–25-year-old female car drivers

Group 3: 18–25-year-old male bus and tram users

Group 4: 18–25-year-old tram users

Notes on the similarities and differences between groups on issues?

Verbatim discourse taken from the interview that relates to this issue

Commuting Freedom Friends Notes on the dynamics of individual groups?

related to using public transport. In the columns, details of each interview are presented and, in the final column, notes are made of observations between interviews, with a focus on each issue. In the rows, the issues that were discussed in the interviews are presented. These issues may be generated from the topic guide used and/or from the notes of the researchers related to what they see as the emerging issues. The final row details notes of the dynamics of the group, explaining why particular exchanges may be interpreted in a particular way. The analyst cuts and pastes extracts from the transcripts into the relevant cells. With the spreadsheet built up of the reordered transcripts (each focus group may tackle the issues in a different order and with different emphases), comparisons can be made across the columns on particular issues, looking for similarities and differences. Connections between issues can be mapped out with the use of arrows to show the flow of dialogue. The responses from types of participants, such as ‘city-dwellers’ or ‘suburb-dwellers’, can be colour coded in order to compare similarities or differences. Different notes, images or any other supplementary material can be pasted onto the spreadsheet to help in the interpretation; all the assembled data can be displayed, or more probably a reduced and coded set of data can be displayed. Such a spreadsheet can be built up manually using large sheets of paper from, for example, flip charts, divided into a grid, and the evidence (such as chunks of the transcript) physically pasted in. This could even be tacked to a large wall, allowing the researcher to stand back, reflect, move things about and add data. The big advantage of this approach is being able to visualise the whole body of data and to move around the data to ‘play’ with ideas and connections. This works particularly well when there is more than one person working on the analysis and they are drawing ideas and questions out of each other as they relate to the data. The disadvantage is that editing, moving data around and recategorising data can become very cumbersome and messy. This is where electronic means of displaying the data work well. With electronic means, images and notes can be scanned in and added to the transcripts. Changes can be made very easily and quickly in moving data around, recategorising and incorporating new material. Different versions can be easily stored to allow an evaluation of how the thought processes of the researcher have developed. The disadvantage of the approach is that, when attempting to view the data in their entirety, the entire data set is there but, in effect, is viewed through a ‘window’ with a limited field of vision. The ‘window’ can be readily moved about, but the overall perspective is limited.

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Table 9.4

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Cross-tabulation of emerging categories related to evening travel by gender Gender

Evening trave

Male

Female

Expense Personal attacks Spontaneity Style

16 8 5 3

2 24 5 5

Another simple means to display data is through the use of a qualitative cross-tabulation. Table 9.4 presents an example of how a cross-tabulation may be set out. Again, the example relates to a bus and tram operator that wishes to understand the attitudes and behaviour of 18 to 25 year olds related to using public transport. The table shows a sample of categories that have been built around the issue of ‘evening travel’. As the analyst works through the transcripts and codes distinct chunks of data, and with knowledge of who expressed a particular view that is embodied in that chunk, that relationship can be displayed. The table shows that the analyst has established codes to represent views of ‘expense’, ‘personal attacks’, ‘spontaneity’ and ‘style’. With a simple classification of participants, in this case by gender, the analyst can display differences in the number of incidences that a specific code emerges. The large differences between males and females in how they brought up the issues ‘expense’ and ‘personal attacks’ can help the analyst to explore the data further, or indeed collect more data to understand what is creating such divergent attitudes and behaviour. Again, different notes, images or any other supplementary material can be pasted onto the cross-tabulation to help in the interpretation. The other major means of displaying data is to use flow charts. Figure 9.2 displays a very basic structure of the issues or major categories and subcategories related to how 18–25 year olds view the use of public transport after an evening out. Visualising the data in this matter can allow the researchers to dip back into the transcripts and their notes to seek alternative ways of connecting evidence and justifying connections.

Figure 9.2 Flow chart depicting how 18–25 year olds view public transport

Looking after yourself – independence

Self-image M

M/F

Cool Getting home at night

Opportunities to ‘show off’

F M/F

Safety Other road users

M/F M/F Continuing the fun of the night

Costs

The car as a fashion item

Trusting those around you

Being attacked

Sense of style Brand of car

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This means that this form of graphic can play a vital role in data reduction and coding, i.e. in making sense of the data, as well as in portraying a final interpretation of the data. Most proprietary qualitative analysis software packages allow data structures to be displayed as in Figure 9.2, but with far more sophisticated features to display structure, differences and supporting evidence. A simple illustration of this in Figure 9.2 is the ‘M/F’ label attached to categories, used to display behavioural tendencies of male or female participants. With a proprietary qualitative analysis package, quite distinctive structures for participant types may be mapped, with the ability to tap into supporting evidence in actual categories or in the links between categories.20 Once researchers have displayed what they see as the meaning in the data, they need to demonstrate the credibility of their vision. This involves data verification.

Data verification Data verification Involves seeking alternative explanations of the interpretations of qualitative data, through other data sources.

Real research

Data verification involves seeking alternative explanations through other data sources and theories. From the start of data collection, qualitative researchers are beginning to decide the meaning of their observations, and noticing regularities, patterns, explanations, possible configurations, causal flows and propositions. The researcher should form these meanings ‘lightly’, maintaining openness and scepticism, developing conclusions that are embryonic and vague at first, then increasingly explicit and grounded. Final conclusions may not appear until data collection is over, depending upon the volume of data collected in all their forms, the coding, storage and retrieval methods used and the resource constraints placed upon researchers. When final conclusions have been drawn, researchers need to demonstrate that they have presented a valid meaning of the data that they have collected. They need to show that the structure or meaning they see is not just a reflection of their own views. This is where the concept of theoretical understanding, as discussed at the start of this chapter, can help. It is also where the use of the researchers’ field notes proves to be invaluable. The use of theory from secondary data, intelligence and the literature can help to guide what may be reasonably expected as a meaning. Other means to verify the data can be through seeking ‘similar’ research findings and explanations taken from different contexts, different time frames and different researchers.21 Though the findings from these different scenarios will not be the same, there can be categories that give qualitative researchers the confidence that they are representing a valid view of their participants. This process is illustrated in the following example.

Ethnographic interpretations22 Ethnography generally emphasises deep understanding through a focus on small numbers of participants and getting to know their lifestyles intimately. Interpretations become more robust when researchers openly draw upon information from other sources. As well as using more traditional marketing research sources, such as focus groups or surveys, other methods can be integrated. To understand what kind of products and services might resonate effectively with Generation Y consumers, researchers from IDEO (www.ideo.com) went as deep as they could with individuals, interviewing and observing them in different contexts. They talked to experts: parents, teachers, youth programme leaders and therapists. They held classes at universities made up of students from this generation and collaborated with them to study their own cohort. They engaged individuals who were willing to make mini-documentary videos of their own lives. Combining insight from these various sources and experiences, they were able to reach a deeper understanding around complex areas such as identity. They could see how identity played out through their behaviours in co-opting brands, sampling from pop culture and borrowing from other continents, cultures and time periods. By triangulating methods, their understanding became more nuanced and ultimately more useful as a foundation for relevant innovation.

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Triangulation A process that facilitates the validation of data through cross-verification from more than two sources.

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Two forms of validation have been suggested as particularly appropriate to the logic of qualitative research.23 The first is termed ‘triangulation’, a term derived from navigation, where different bearings give the correct position of an object. Triangulation is a process that facilitates the validation of data through cross-verification from more than two sources. In research terms, comparing different kinds of data (e.g. dialogue and photographs, quantitative and qualitative) and different methods (e.g. observations and interviews) allows reflection upon the extent of corroboration, and what may be the causes of any differences.24 The second is termed ‘participant validation’. This involves taking one’s findings back to the participants under study. Where the feedback from participants on emergent conclusions is verified by them, there can be more confidence in the validity of the findings. (The concept of validity will be examined in more detail in Chapter 12.25) It is worth noting that the qualitative researchers should not just present an interpretation and then seek validation or verification of that perspective. The search for verification is a quest that permeates the whole research process. At face value, data assembly, reduction, display and verification appear to be quite distinct and consecutive stages of data analysis. The reality is that they are iterative and totally interdependent upon each other. As researchers assemble new data, they should be thinking of means to validate their views, asking questions of different individuals in different ways and recording these thoughts in their field notes. As data are being reduced and coded, the researchers seek different possible explanations and evidence to support categorising, naming and connecting views in a particular manner. Researchers should question their interpretations of words and gestures and their own ways of seeing. This questioning process adds to the verification. The use of data display is a means to communicate to others the meaning and structure that researchers ‘see’ in qualitative data. The display allows others to understand that vision, to question and evaluate it. The exposure and critique of the vision by other researchers and decision makers further verify the data. Ultimately, such critique can direct the researchers to further data assembly, reduction and display; the stages may unfold in ‘waves’ to produce an ultimate interpretation of great value to decision makers.

Grounded theory

Grounded theory A qualitative approach to generating theory through the systematic and simultaneous process of data collection and analysis.

In 1967 Glaser and Strauss published the seminal work The Discovery of Grounded Theory.26 It was their formal description of the approach to handling and interpreting qualitative data that they had developed in the 1960s in a participant observation study of hospital staff’s care and management of dying patients.27 The method they developed was labelled grounded theory to reflect the source of the developed theory, which is ultimately grounded in the behaviour, words and action of those under study.28 The essence of their beliefs was:29 • • •

•

• •

The need to conduct field research if one wants to understand what is going on. The importance of theory grounded in ‘reality’. The nature of field experiences for participants and researcher as something that continually evolves. The active role of persons in shaping the worlds they live in through the process of symbolic interaction. An emphasis on change and process and the variability and complexity of life. The interrelationship between meaning in the perception of participants and their action.

The application of grounded theory means that the researcher develops conclusions that are grounded in the ‘data’. Grounded theory is meant to be transparent; in other words, for any given conclusion or theory that comes out of the analysis, anyone should be able to reference the theory back to the text, see the steps the researchers have taken to arrive at their conclusions, and follow the development of the theory in a step-by-step way, leaving little or

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no room for subjectivity, preconception and prejudice.30 Grounded theory researchers collect data and analyse them simultaneously, right from the initial phases of research. They would argue that in the initial stages of research it is not possible to know exactly what the most significant social and psychological processes are in particular settings. Research could be guided by existing theories, which may help to predict processes, but they would argue that such guidance may constrain their observations, forcing them to observe a particular setting from a narrow perspective. So they start with broad areas of interest and form preliminary interviewing questions to open up many areas that could hold relevance. They explore and examine participants’ views and then further develop questions around those views, seeking out participants whose experiences address the emerging issues. This sequence is repeated several times during a research project, which means that researchers are kept ‘close’ to their data. Grounded theory gives researchers tools to analyse data that are concurrent with obtaining additional focused data that inform, extend and refine emerging analytical themes. This means that interviews become more focused, with a tight fit between the collected data and the data analysis. With grounded theory, the researcher works in the actual environments in which the actions take place, in order to relate participants’ perspectives to the environments through which they emerge (such as ethnographers sharing the homes of families to observe how they use and listen to the radio). 31 The style of grounded theory adapts well to capturing the contextual complexities in which action unfolds, enabling researchers to understand better the interrelationships of context and action. It is especially useful where existing theories fail to explain observed phenomena, enabling researchers to challenge existing accepted views and think beyond conventional paradigms.32 Essentially, the approach is most commonly used to: 1 Generate new theory where little is already known. 2 Provide a fresh perspective on existing knowledge, i.e. to supplement existing theories. 3 Challenge existing theories. Researchers may challenge or disagree with existing theories for two reasons. The first is based upon the substantive representation of what the theory explains, e.g. of how children respond to certain forms of advertising. The second may be based upon how the theory was created, i.e. the research approach, techniques or forms of analysis.

The grounded theory approach to analysing data Grounded theory provides researchers with guidelines for analysing data at several points in the research process, not simply at an end point or ‘analysis stage’. It involves the following four stages:33 Grounded theory data coding A form of shorthand that distils events and meanings without losing their essential properties.

1. Coding data. Grounded theory data coding is at least a two-step process. It starts with an initial or open coding process, which forces the researchers to begin making broad analytical decisions about the data they are collecting. It moves on to more selective or focused coding, in which the researchers use the most frequently appearing initial codes to synthesise and conceptualise large amounts of data. In essence, coding is a form of shorthand that distils events and meanings without losing their essential properties. During the coding process, researchers work through their collected data on a line-by-line basis, use ‘active’ terms or descriptors to define what is happening in the data, and ultimately follow leads in the initial coding through further data gathering. Throughout the process of coding in grounded theory, the researchers should regularly address the data, as they are built up and in their entirety, with the following list of questions. Attempting to answer these facilitates the questioning of how codes are defined, connected and subsumed into broader categories:34 a What? What is it about here? Which phenomenon is mentioned? b Who? Which persons are involved? What roles do they play? How do they interact?

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c How? Which aspects of the phenomenon are mentioned (or not mentioned)? d When? How long? Where? Time, course, location? e How much? How strong? Aspects of intensity. f Why? Which reasons are given or can be reconstructed? g What for? With what intention, to what purpose? h By which? Means, tactics and strategies for reaching that goal. Memo writing Anything from loosely written notes through to fully formed analytical arguments, which are added to the original data and interpretations.

2. Memo writing. Memo writing links coding to the writing of a first draft of the analysis. This stage helps researchers to: define the properties of the categories that they have created; specify conditions under which each category has developed; and note the impact of each category and the interrelationships with other categories. Memos can be anything from loosely written notes to fully formed analytical arguments, which are added to the original data and interpretations. The process of memo writing helps the researcher to achieve the following:35 a Stop and think about what is emerging from the data. b Generate ideas to explore through other means of collecting data. c Reflect upon gaps and missed opportunities in earlier interviews and observations. d Reflect upon the meanings and impact of personal field notes. e Treat coded data as distinct categories to analyse. f Clarify categories, through their definitions, properties, distinctive elements, consequences and interconnectivity with other categories. g Make explicit and constant comparisons of data with data, category with category, concept with concept.

Theoretical sampling Data gathering driven by concepts derived from evolving theory and based on the concept of ‘making comparisons’.

3. Theoretical sampling. This concept was introduced in Chapter 6 in our discussion of the differences between a positivist and interpretivist approach to research. This type of sampling is not designed to represent a chosen population, but to develop theory by seeking out new data. The process of gathering more data is driven by the challenges in building categories and concepts that are derived from evolving theory. It is based on the notion of seeking out different situations and learning from the comparisons that can be made. Theoretical sampling helps researchers to construct and discard hypotheses and theoretical explanations of the data they are immersed in. Its purpose is to encourage researchers to go to places, people or events that will maximise their opportunities to discover variations among concepts. By generating more focused data to fill in any gaps in emerging categories and concepts, the whole process of theory building becomes more precise, explanatory and predictive. The process of theoretical sampling helps the researcher to achieve the following:36 a Define gaps within and between emerging categories that their coding suggests. b Discover variation within these categories. c Develop the validity of categories and their interconnections. d Seek out and gather more focused and rich data. e Seek out and gather other theoretical frameworks that may help to explain what is emerging in the data. 4. Integrating analysis. Producing more focused and well-developed memos as the analysis proceeds should enable researchers to produce theory that is clear and well validated.

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Researchers should aim to integrate the memos they have crafted in order to reflect the theoretical direction of their analysis or stages of a process. They have to create the order (how do the ideas fit together?) and the connectivity (what order makes the most sense?) that they see emerging from their memos. The process of integrating analysis helps the researchers to achieve the following:

Integrating analysis Creating an order and connectivity that is seen to be emerging from memos.

a Sort the memos, usually done by the titles of categories. b Map out a number of ways to order the memos. c Choose an order that works for the analysis and whoever is going to use and benefit from the emergent theory. d Create clear links between categories. When ordering memos, researchers should consider whether a particular order reflects or challenges the logic of the experiences of participants and their target audiences of decision makers. A balance needs to be made between both parties, which may mean collapsing categories for clarity and ease of reading.

Limitations of grounded theory Grounded theory has been criticised for its failure to acknowledge implicit theories that guide researchers in the early stages of their work. Grounded theory researchers argue that such guidance may constrain their observations, forcing them to question and observe a particular setting from a narrow perspective. The downside of claiming to have such an approach is that it may be extremely difficult to ignore theories that may be embedded into researchers’ ways of thinking. It may also be counterproductive to ignore relevant theories (used with a healthy dose of scepticism) that could be useful in creating focus in gathering and interpreting data. Another major criticism of grounded theory is that the process can degenerate into a fairly empty building of categories, with a great abundance of description, especially when aided by data analysis software.37

Content analysis Content analysis The objective, systematic and quantitative description of the manifest content of a communication.

In qualitative research, content analysis is one of the classical procedures for analysing textual material, forms of communication and images rather than behaviour or physical objects. The focus of the analysis may range from the narrative or images held in brochures or advertising copy, to dialogues held in interview data. Primarily, the objective of content analysis is to ‘reduce’ the data, to simplify by summarising and structuring the data according to rules derived from existing theory. In effect, even though a researcher may be working with qualitative data, content analysis should be classified as a quantitative technique based upon classifying and ‘counting’. Content analysis is seen by many as an ‘objective’, systematic and quantitative description of the manifest content of a communication.38 The term ‘content analysis’ is set to include observation as well as analytic activity. The unit of analysis may be words (different words or types of words in the message), characters (individuals or objects), themes (propositions), space and time measures (length or duration of the message) or topics (subject of the message). Analytical categories for classifying the units are developed, and the communication is broken down according to prescribed rules. Marketing research applications involve observing and analysing the content or message of advertisements, newspaper articles, TV and radio programmes and the like. The following example illustrates an application and process of content analysis that was visually based.

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Food advertising to children39 Content analysis was used to provide descriptive statistics of incidence and a thematic analysis of messages contained in a sample of food advertisements in Australia during children’s TV programming. Three weeks’ data were collected (Monday to Friday on Channel 10 from 7 to 8.30 a.m. and Saturday on Channel 7 from 7 to 9 a.m.) from the two Perth commercial TV channels with morning children’s programming. The data were then independently coded by two researchers using a highly detailed coding instrument that provided an exhaustive list of predetermined options to increase inter-coder reliability. Pilot testing was carried out on a selection of advertisements that were not included in the final sample. Each advertisement was viewed first in its entirety without undertaking any coding, then all spoken and written text was transcribed onto the coding form and a summary of the story and events generated. The advertisement was then viewed several times to capture the information required on the coding instrument. Next, the results were compared across the two coders’ output. There was almost complete agreement, with just a few discrepancies related to the food groups to which certain packaged foods belonged. These discrepancies were resolved after investigation of the products’ ingredients, resulting in complete coder agreement. After the frequencies were tabulated for each code, the ad descriptions and summaries were analysed qualitatively to develop themes relating to the advertisement content. This involved constant iterations between the data and emerging themes to ensure soundness of fit. The 28.5 hours of children’s TV programming sampled contained 950 advertisements. This equated to more than 33 advertisements per hour of TV viewed. These included 212 advertisements for food products and represented 30 discrete advertising campaigns. Several of the 30 campaigns were repeated many times, often appearing twice in the same break. When categorised into the National Health and Medical Research Council’s food groups, the foods advertised to children were diametrically opposed to the foods recommended for children.

Content analysis has several virtues.40 First of all, it is a standardised technique that permits the processing of large amounts of data covering long time spans. It is an unobtrusive research method, avoiding the problems of researcher effects on the data that are inherent in interpretative research methods such as in-depth interviewing.

Limitations of content analysis Content analysis has its shortcomings; the most serious involve the issues of manifest content, data fragmentation and quantification. For qualitative researchers, these set limits on the usefulness of the method for the analysis of visual representations:41 1 Manifest content. A crucial requirement to the success of content analysis is that the established categories of analysis are sufficiently precise to enable different coders to arrive at the same results when the same body of material (e.g. advertising copy) is

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examined. Thus, manifest content refers to what may be seen to be manifestly apparent in the established categories of any communication. This means that, in coding the meanings in any communication, a clearly defined category system must plainly state the characteristics of content – there can be no implicit or hidden meanings from the coding operation. For some analysts,42 the insistence upon coding only manifest content is too restrictive. The essence of their argument is that excessive emphasis on a standardised approach can result in reliability being attained at the expense of validity. The significance of the message may lie more in its context than in its manifest content. 2 Data fragmentation. By virtue of the constraint of focusing upon manifest content, the tendency is to break up communications into their elements, and it is solely the presence, absence or frequency of these elements that is deemed relevant to the investigation. This categorisation isolates those elements of the communication determined by the researcher’s analytical framework or theory. This process de-contextualises the message in a communication – a process described as ‘losing the phenomenon’, or failing to respect the original right of the data.43 3 Quantification. It has been argued that content analysis is essentially a quantitative research technique and that applying qualitative considerations in the technique risks its objectivity and its systematic nature. The strength of the technique lies in allowing the selection and rational organisation of categories to condense the substantive meanings of a communication, with an aim to testing assumptions or hypotheses. If the aim of a study were to count frequencies in order to test hypotheses about communications, then the technique has much to offer. In this case it could be argued that the requirements of objectivity and a systematic approach should be the prime aim of the content analyst, and that the issue of manifest content be treated on a case-by-case basis. When examining individual cases and contexts, the presence or absence of a ‘theme’ may be measured, but not the frequency with which it occurs in the communication. What the essence is of that ‘theme’ takes the method into the realms of qualitative research.44

Semiotics

Semiotics The study of signs in the context of consumer experience.

We have described a range of different qualitative techniques and approaches that primarily focus on the participants or the consumers, questioning and observing them in a direct or indirect manner. Semiotics takes a different approach, in that consumers are not viewed as independent, self-determining agents, making their own choices. Rather, consumers are viewed as products of culture – constructed and largely determined by the popular culture within which they live. Consumer needs and aspirations are seen as not being the result of freely made choices of the individual, but a reflection of the surrounding cultural discourses. Semiotics therefore moves the researcher’s focus towards the cultural context of the consumer, including both popular culture and the marketing context.45 Semiotics combines knowledge and research techniques from across a spectrum of disciplines, including linguistics, psychology, anthropology, cultural studies and the visual arts. It analyses data such as paintings and photography that some other qualitative research methods do not tackle so well.46 It is based on a detailed analysis of language and images, which untangle how meaning is conveyed as well as what that meaning is. A semiotic approach can be integrated with qualitative techniques that may generate much visual data, such as ethnography. This link is illustrated in the following example.

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Pushing the glamour button47

Real research

Unilever wished to grow the Rexona deodorant brand (www.rexona.com) in Russia. To generate consumer insight for its brand development, Unilever undertook a qualitative research approach, using ethnography and semiotics within a creative workshop environment. The semiotics input gave it useful ways of thinking around issues and an inspiration for future communications. Uncovering some of the essential codes that underpinned Russian attitudes to identity, femininity and social status, semiotic methods led to a deeper understanding of deodorant consumers. The most influential aspect of Russian culture identified by semiotics was around the issue of femininity. Unilever noted that ‘Prada was the new Pravda’; that glamour was the new one-party ideology of modern Russian culture. Qualitative research had already identified Russian women’s ambivalent attitudes towards the affluent glamour of the Moscow elite. In Unilever’s semiotic work they expanded on this contradictory state of admiration, jealousy, aspiration and loathing. It seemed that the ‘glamour button’ was the right one to push. While most Russian women, as elsewhere in the world, cannot afford to buy into the high-fashion world of Gucci and Prada, it was felt that the use of deodorant could provide a valuable displacement activity around glamour. On the one hand, ‘regular’ women could appreciate the notion that the richest, most glamourous Muscovites could be let down by their body odour. On a more positive note, the representation of glamour with a degree of accessibilty offered women a chance to ‘buy into’ the fame and beauty without having to spend three months’ wages on a handbag.

Semiotic researchers aim to develop a richer and more holistic understanding of consumers by unearthing the cultural frameworks that underpin their behaviour. This can work across diverse global markets, supporting the design of brands and all the creative output that shapes brands in different cultures.48 In approaching a research problem, a conventional qualitative researcher might ask, ‘Why does Frank buy Pot Noodle?’. The semiotic researcher would be more likely to ask, ‘How does consumer culture give meaning to Pot Noodle, and what are these meanings?’. The semiotic researcher might argue that if we can answer these questions, we will be able to make a good guess not just at why Frank buys it, but also why anyone buys it. This is because behavioural meanings are constructed within popular culture, and consumers are influenced and constrained by this cultural context. An understanding of the broader cultural context is something that semiotic analysis is uniquely well placed to provide, because it focuses on the culture and not just on the consumer.49 Examples of how semiotics can help marketing decision makers are:50 • • •

•

Mapping out a new market or a whole field of cultural activity. Seeing opportunities to position new brands. Analysing how different aspects of marketing communications work together, and the means to create synergies across different media. Evaluating in-store developments and harmonising the different aspects of marketing communications.

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• •

•

Diagnosing problems with brand or marketing communications. Providing models and guidelines for successful brand communications, indicating the key signifiers within the relevant context. Understanding the process of encoding and decoding more precisely, to minimise the potential for misunderstanding between the marketer and the consumer.

As can be seen from the above list, semiotics can play a major role in the development of a wide array of marketing communications. In terms of conducting a qualitative analysis of marketing communications, the approach goes into far more depth in comparison with content analysis. Semioticians investigate the subtext of communication. They begin with the brand, combing through the cultural connotations of advertising imagery and language, the colour, shape and forms of corporate identity, where the brand is distributed and how it is displayed. Then they look outwards to the consumer’s world, hunting for shifts in cultural meaning – how concepts such as masculinity, heroism or indulgence have changed over time and how they might be reinterpreted.51 To illustrate this point, the following questions may be set by a researcher examining the advertising of a particular brand, looking at the past, the potential and the competition. The questions would be directed at the text, sounds and images of the advertisements, the wide breadth of qualitative data:52 • •

•

• • •

• •

•

What are the major signifiers (i.e. the material signs – what it is)? What signifieds (i.e. the conceptual sign – what it means) might they be creating and to whom? How do the advertisements work on a symbolic/metaphorical and on a product/metonymical (literal) level? How do the form and content of the advertisements work together? What codes (i.e. bundles of signs) do the advertisements use? How do the advertisements measure up to the brand’s historical codes and those of its competitors? How do the advertisements work in relation to the brand’s history and its futures? Are is the advertisements using a dominant (everyday, mainstream), emergent (leadingedge, culturally dynamic) or residual (old-fashioned, lacking in energy) set of codes, or are residual codes being applied in an emergent way? What kinds of discourse or discourses are apparent, e.g. postmodernism, feminism, spirituality?

This set of questions and processes will illuminate the advertising material under development. They will help the researcher to understand more completely the material that viewers will be evaluating. However, this may not be readily achievable using a single researcher. To maximise the potential of semiotics, an action research approach (described in Chapter 6) may offer the best results. This would involve taking a more facilitative and involving approach – sharing the actual techniques and questions of semiotic analysis with researchers and decision makers working together towards the co-creation of knowledge. This would be more open and interactive. Semiotics specialists would be vital to the process, but as facilitators and mentors in a workshop-style of joint working, helping clients identify and understand the way forward themselves. A more involving approach also provides the tools to recode, enabling the client to move from insight to the successful implementation of new strategy in any of the applications above.53

Limitations of semiotics Although semiotics is able to analyse a great breadth of interrelated qualitative data, there are four core criticisms:54 1 Reliability. The main criticism of semiotics lies in how reliable or replicable it is.55 Although an individual analyst’s interpretation may be very insightful and could be a valid

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representation of cultural influences upon the consumer, there is little guarantee that another analyst would come to the same conclusion about the relevant codes or structures. 2 Qualitative data set. In practice it can be hard to assemble the relevant data to analyse, given that there is usually no discourse or discussion as might be assembled with a series of focus groups or in-depth interviews. 3 Logic of interpretation. It is not usually clear how the analyst has arrived at an interpretation. It must be accepted that there is no unique way to interpret text or other types of qualitative data. On this score, Derrida56 makes the point that no single interpretation can ever claim to be the final one.57 In the case of semiotics, in many instances an interpretation seems to rely upon a shared knowledge of a cultural background and intuition, which may be valid but extremely difficult to validate. This is where an action research approach can help, where the team of researchers and marketing decision makers share and ‘own’ the interpretation. 4 Consumer theory. The position of the consumer can be unclear in semiotic analysis. In principle, the consumer is seen as passive, determined by culture and unable to break out of their contextual frame.58 Many consumer theorists would disagree with this view, giving the consumer a more active role in interpreting, accepting or resisting the brand’s semiotically encoded meanings.

Qualitative data analysis software As with quantitative data analyses, it is possible to complete qualitative analyses without the aid of a computer. With quantitative analysis, it would be a rare occurrence to analyse data without a computer. With qualitative analysis it is not so rare; many researchers still believe in a ‘hands-on’ immersion in the rich data they have collected. Using the computer should provide speed, memory, ease of data access and the ability to transform and manipulate data in many ways. Overall, it should allow a far more efficient and ultimately effective process, as the researcher’s effort can then be focused upon generating the most effective support for decision makers as quickly as possible, rather than upon laborious administrative tasks. The following list summarises qualitative research activities that may be supported by the use of computers: 1 Field notes. Making notes before, during and after interviews and observations. Writing and editing these notes if needed as part of a data display to justify a particular interpretation. 2 Transcripts. Building up transcripts to represent the discourse in interviews. 3 Coding. Attaching keywords to chunks of data or text. 4 Storage, search and retrieval. Keeping data in an organised manner, so that relevant segments of data or text can be located, pulled out and evaluated. 5 Connection. Linking relevant data segments with each other. 6 Memos. Writing up reflective comments that can be ‘pasted’ onto relevant codes and connections. 7 Data display. Placing selected or reduced data in a condensed and organised format using a spreadsheet matrix or network. The display can be part of the development of the analysis or in the final vision produced by the researcher. 8 Drawing conclusions and verification. Aiding the researcher to interpret the data display and to test or confirm findings.

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9 Theory building. Developing systematic and conceptually coherent explanations of findings that are meaningful to marketing decision makers. 10 Reporting. Presenting interim and final reports of the findings in a written and oral manner. Many of these tasks can be performed with readily available word-processing, spreadsheet and presentation packages. Many researchers may be very comfortable using such packages to gather and record data and to present findings. What may be new to many researchers is the use of proprietary software to help with the technical integration of data assembly, reduction, display and verification. Improvements in the functions and power of software that copes with this technical integration occur at a rapid pace. To see examples of different qualitative data analysis packages, download demos and cases and evaluate how applicable they may be to a particular qualitative technique, visit the following websites: Qualitative data analysis software

Website

NVivo Atlas.ti MAXQDA

www.qsrinternational.com www.atlasti.com www.maxqda.com

The following example illustrates why Progressive Sports Technologies (www.progressivesports.co.uk) use NVivo and the qualitative techniques that are supported by this software. We recommend that you visit the QSR website to evaluate descriptions of applications and cases of NVivo applications. If you do not already have access to NVivo through your university or employer, you can access a demo from the NVivo website at the above address. Qualitative data analysis packages do not automate the analysis process, nor is that their purpose. The process of coding, as described in the data verification section, depends upon the interpretations made by the researcher. The overall description, model or theory that emerges from the analysis also depends upon interpretations made by the researcher. No analysis package can perform such interpretations. Qualitative data analysis is not formulaic; it requires an approach that gives quick feedback to the researcher on the results of emergent questions. This involves an iterative cycle of reflection and innovation, which means total interaction between the researcher and the computer. So, rather than seeing analysis as an automated process, the purpose of software is to aid the researcher to analyse data in a systematic and thorough manner. The researcher seeks patterns, meanings and interconnections in the qualitative data. This can be conducted manually, but by using software the researcher can manipulate the data far more efficiently to help see patterns, meanings and interconnections and, ultimately, to develop theory.

Advantages of computer-assisted qualitative data analysis 1 Speed. The speed at which programs can carry out sorting procedures on large volumes of data is fast. This gives the researcher more time to think about the meaning of data, enabling rapid feedback of the results of particular analytic ideas so that new ones can be formulated. Analysis becomes more devoted to creative and intellectual tasks, less immersed in routine. 2 Rigour. Rigour adds to the trust placed in research findings. In this context it means counting the number of times things occur, as well as demonstrating that negative incidences have been located rather than selecting anecdotes that support a particular interpretation. 3 Team. In collaborative research projects, where researchers need to agree on the meaning of codes, a check can easily be made of whether team members are interpreting segments in the same way. This is particularly useful as coding moves from the more descriptive

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and mundane codes to ones that reflect broader theoretical concerns. Researchers can pass coded interviews between them, and compare the results. 4 Sampling. It is easy to keep track of who has been interviewed, compared with the intentions of who should be interviewed. Beyond the sampling of individuals is the concept of theoretical sampling, i.e. the inclusion of events that corroborate or contradict developing theory. As researchers have more time to spend on creative and intellectual tasks, they can develop stronger descriptions and theories and strengthen the validity of their views by ensuring they have sampled sufficient incidences.59 It must be reinforced that software packages cannot interpret and find meaning in qualitative data. The programs do facilitate, and in some cases automate, the identification and coding of text. But there is sometimes a false assumption that identification and coding are simple and unproblematic, and critical evaluation and scrutiny of coded segments and code counts are not needed. By facilitating quick analyses, which focus on quantitative category relationships, the software may discourage more time-consuming, in-depth interpretations. Thus, while the programs are intended as a means of allowing the researcher to stay close to the data, their misuse can have the unintended result of distancing the researcher from the data. As discussed earlier, many decision makers who use qualitative marketing research do not question how analysis is completed, or indeed why it should be completed. The following arguments illustrate the nature of their concerns.60

Disadvantages of computer-assisted qualitative data analysis 1 Mechanistic data analysis. The computer cannot replace the creative process expected of the qualitative researcher. The researcher can evaluate the interrelated play on particular words, the tone of voice or the gestures of a particular participant. The sensitivity towards these relationships and connections can be lost in a mechanistic search for statements. 2 Loss of the overview. The researcher may be seduced into concentrating on the detail of individual chunks of data and assigning codes to the data. This focus may detract from the overall context that is so vital to identify and name chunks of data. Making sense of codes can be greatly facilitated by an ability to visualise the data in their entirety. 3 Obsession with volume. Given the ability to manipulate large amounts of data, there may be a push to increase the number of interviews. This may be counterproductive in that the emphasis should be on the interrelated qualities of: a individual participants b the data-capture process. 4 Exclusion of non-text data. As noted earlier, qualitative ‘text’ can include notes, observations, pictures and music that make up the total ‘picture’ or holistic representation of individuals. Many programs can only cope with the narrative of questions and answers recorded in transcripts (though rapid developments have been made to overcome this shortcoming). Qualitative analysis software developers have recognised the above limitations and have gone to great pains to overcome them. One of the trade-offs faced by software developers in overcoming these limitations is the user-friendliness of their programs compared with the sophistication of being able to manipulate and represent the structure that may lie in multifarious data. As qualitative researchers use and learn how to generate the most from the software, user-friendliness may take a lesser, though not ignored, role. Experienced qualitative researchers can demand more sophistication to match the realities of coping with qualitative data. For the novice qualitative researcher the packages may seem daunting, but this problem is analogous to an initial exposure to statistical packages such as SPSS. In all cases, researchers need to appreciate how the software may serve them and work through the examples and cases, to experiment and to build up their knowledge and confidence.

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Real research

Taking sporting equipment to a new standard61 Progressive Sports Technologies Ltd is a UK-based sports innovation consultancy that specialises in the research and design of cutting-edge fitness equipment for major global sports brands such as Nike, Reebok and Speedo. In a research project on elite sporting products it used NVivo to conduct qualitative data analysis. The sport and fitness sector is a highly competitive industry where athletes and participants search for the latest training advancements in order to gain improved results. Whether training at an elite level or working out for general health and fitness, sporting participants demand goods and services that will better help them achieve their goals. The biggest challenge for sporting manufacturers is working out exactly what elite athletes want from their equipment. Understanding what this elite group wants is more difficult than it sounds. A thletes who are at the top of their game and striving for the smallest improvement in results may not necessarily be able to articulate where they want changes made. Traditionally, sporting-equipment designers have first created prototypes of new products and then asked athletes for their feedback, in order to fine tune the equipment. At Progressive, this process has been turned on its head by opening up direct communication channels between its designers and the elite athletes via a new perception study. In Progressive’s perception study, detailed interviews were conducted with 25 elite athletes across two countries. By providing the athletes with four distinct products within the same category, such as four very different pairs of running shoes, each participant was asked to describe their perceptions towards the different products in great detail. All interviews were recorded, transcribed and entered into NVivo. The software was used to group all keywords and themes that the athletes were describing. Numerous athletes were tested on multiple days, in different venues and countries. The software was used as an archive of all the testing carried out. The data files had in the order of 50,000 words relating to the athletes’ product perceptions. The software was seen as a huge time saver and allowed Progressive to organise the work in a clear and logical manner. The time saved was huge, the process definitely halved the sorting and evaluation time. In addition, the audiovisual capabilities available in NVivo allowed Progressive to import all files under one umbrella, including sound and movie files for future studies.

Summary

Qualitative researchers should reflect upon how their social and cultural values affect the way they perceive and observe target participants. These reflections should be built up as field notes as the whole process of data gathering develops and evolves. These notes form a key source of qualitative data to complement the broad array of qualitative data generated from interviews and observations. To successfully draw together a valid interpretation, qualitative data analysis must be set in the context of a theoretical understanding of the issue being researched and an understanding of the marketing decision makers’ use of the findings. The first stage of the process of analysing qualitative data involves assembling data in their rich and varying formats. The second stage involves reducing the data, i.e. selecting, classifying and connecting data that are believed to be of the greatest significance. A key element of this stage is the concept of coding. The third stage involves displaying data, i.e. using graphical means to display the meaning and structure that a researcher sees in the data collected. The final stage involves verifying the data. The researcher aims to generate the most valid interpretation of these data, which may be

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supported by existing theories or through the concept of theoretical sampling. The stages of analysis seem quite distinct but in reality they are totally dependent upon each other. Three of the most commonly used approaches to analysing qualitative marketing research lie in grounded theory, content analysis and semiotics. Grounded theory is an approach that develops theory that is ultimately grounded in the behaviour, words and action of those under study. Content analysis is used to ‘reduce’ qualitative data, to simplify them by summarising and structuring the data according to rules derived from existing theory. Semiotics combines research techniques from across a spectrum of disciplines, including linguistics, psychology, anthropology, cultural studies and the visual arts. It helps to analyse visual data that some other qualitative research methods do not tackle so well. The qualitative researcher needs to develop an understanding of the social and cultural frames of target participants in international markets. At the same time, qualitative researchers must have a strong awareness of their own social and cultural frames. Only when they have examined both perspectives can they effectively interpret consumer responses. To be able to cope with the large amount of data generated from qualitative techniques, a great variety of software packages are available. Used correctly, they can facilitate a speedy and rigorous exploration of qualitative data, allowing teams of researchers to perform creative and incisive analyses and interpretations. The main concern with the use of qualitative data analysis packages lies in the potential for them to be mechanistic and to encourage yet more interviews to be completed, sacrificing the quality of data capture.

Questions

1 How may the social and cultural background of researchers affect the way they: a gather qualitative data? b interpret the whole array of qualitative data they have gathered? 2 What is the significance of a qualitative researcher having a theoretical and marketing understanding of the subject they are researching? 3 Why should a qualitative researcher maintain a field notebook? 4 What should be recorded in a field notebook? 5 What may be classified as ‘data’ when assembling data as part of the data analysis process? 6 What does the word ‘coding’ mean in the context of qualitative data analysis? What problems do you see associated with the process of coding? 7 What are the advantages and disadvantages of handing over recordings of qualitative interviews to a typist who has taken no part in the interviews? 8 Evaluate the purpose of displaying qualitative data. 9 What advantages and disadvantages do you see in displaying qualitative data in a spreadsheet format? 10 Evaluate ‘when’ the stage of data verification should occur. 11 How may theoretical sampling aid the process of verification?

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12 How may different types of software help in the whole process of qualitative data gathering and analysis? 13 Evaluate the main concerns that exist with the use of software in qualitative data analysis. 14 Why is the researcher’s understanding of their social and cultural values particularly important in international marketing research? 15 Why does the interpretation of qualitative findings have ethical implications?

Exercises

1 You have been given the task of conducting a series of in-depth interviews about luxury cruises targeted at women of 50 years of age and over. What preparatory work could you do to understand the characteristics of this subject, the target group and how the target group relates to the subject? 2 You have just started to work for a major qualitative marketing research agency. The CEO notes that her researchers use a great variety of methods to keep field notes, ranging from scrappy notes taken at interviews to detailed diaries. You have been given the task of designing a format of field notes that will incorporate ‘short notes made at the time of observation or interview’, ‘expanded notes made as soon as possible after each session of interviews or observations’, ‘a fieldwork journal to record problems and ideas that arise during each stage of fieldwork’ and ‘a provisional running record of analysis and interpretation’. Present the design and the case you would make to other researchers to use your format. 3 You have conducted a series of focus groups with 18 to 21 year olds about travelling home from evening events. As you complete each group, you ask participants to photograph significant events during their journeys home for the forthcoming weekend using their mobile phones. What would you do with the images that they send to you? 4 An ethnographic study is planned of young men using Lynx deodorant. Compare the relative merits of the qualitative data analysis packages ATLAS.ti (www.atlasti.com) and NVivo (www.qsrinternational.com) in terms of coping with the types of data that will be generated and the interpretations that will be performed. 5 In a small group, discuss the following issues: ‘Quantitative techniques of analysis and data display have no role to play in qualitative data analysis’ and ‘Theoretical sampling could never work in commercial marketing research given that it creates an open-ended agenda of issues to explore and participants to pursue.’

Notes 1. Murakami, H., South of the Border, West of the Sun (London: Harvill, 1999). 2. Interpreting narrative, i.e. the nature and scope of analysing literature, is a major subject area in its own right. For a simple introduction to the field, see Barry, P.,

An Introduction to Literary and Cultural Theory 3rd edn (Manchester: Manchester University Press, 2009). 3. Okazaki , S., ‘Mobile finds girls’ taste: Knorr’s new product development’, Journal of Interactive Advertising 9 (2) (Spring 2009), 32–9.

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4. Stienstra, J. and van der Noort, W., ‘Loser, hero or human being – are you ready for emergent truth?’, ESOMAR Best Methodology, Annual Congress, Montreal (September 2008). 5. For an example of the use of field notes in a qualitative study, see Drenten, J., Okleshen Peters, C. and Boyd Thomas, J., ‘An exploratory investigation of the dramatic play of preschool children within a grocery store shopping context’, International Journal of Retail & Distribution Management 36 (10) (2009), 831–55; Rubin, H.J. and Rubin, I.S., Qualitative Interviewing: The Art of Hearing Data (Thousand Oaks, CA: Sage, 1995), 120. 6. Coffey, A. and Atkinson, P., Making Sense of Qualitative Data: Complementary Research Strategies (Thousand Oaks, CA: Sage, 1996), 10–11. 7. Spradley, J.P., The Ethnographic Interview (New York: Holt, Rinehart & Winston, 1979). 8. Prasad, S., ‘Listening to the sounds of silence’, ESOMAR Asia Pacific, Kuala Lumpur (April 2010). 9. Snowden, D. and Stienstra, J., ‘Stop asking questions: Understanding how consumers make sense of it all’, ESOMAR Annual Congress, Berlin (September 2007); Ereaut, G., Analysis and Interpretation in Qualitative Market Research (London: Sage, 2002), 63. 10. Gordon, W. and Langmaid, R., Qualitative Market Research: A Practitioner’s and Buyer’s Guide (Aldershot: Gower, 1988). 11. Ball, M.S. and Smith, G.W.H., Analyzing Visual Data (Newbury Park, CA: Sage, 1992), 9. 12. Verhaeghe, A., Van den Bergh, J. and Colin, V., ‘Me myself and I: Studying youngsters’ identity by combining visual ethnography and netnography’, ESOMAR Qualitative Research, Istanbul (November 2008). 13. Brace-Govan, J., ‘Participant photography in visual ethnography’, International Journal of Market Research 49 (6) (2007), 735–50. 14. Coffey, A. and Atkinson, P., Making Sense of Qualitative Data (Thousand Oaks, CA: Sage, 1996), 26. 15. Rubin, H.J. and Rubin, I.S., Qualitative Interviewing: The Art of Hearing Data (Thousand Oaks, CA: Sage, 1995), 238. 16. Hubermann, A.M. and Miles, M.B., ‘Data management and analysis methods’, in Denzin, N.K. and Lincoln, Y.S. (eds), Handbook of Qualitative Research (Thousand Oaks, CA: Sage, 1994), 428–44. 17. Weltzer-Ward, L., ‘Content analysis coding schemes for online asynchronous discussion’, Campus-Wide Information Systems 28 (1) (2011), 56–74; Roberts, M. and Pettigrew, S., ‘A thematic content analysis of children’s food advertising’, International Journal of Advertising 26 (3) (2007), 357–67; Krippendorf, K., Content Analysis: An Introduction to its Methodology (Beverly Hills, CA: Sage, 1980). 18. Coffey, A. and Atkinson, P., Making Sense of Qualitative Data: Complementary Research Strategies (Thousand Oaks, CA: Sage, 1996), 29–30. 19. Miles, M.B. and Huberman, A.M., Qualitative Data Analysis: An Expanded Sourcebook, 2nd edn (Thousand Oaks, CA: Sage, 1994), 11. 20. This is a very basic overview of the different means to display qualitative data. For a fuller discussion, the

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following is recommended: Huberman, M. and Miles, M.B., The Qualitative Researcher’s Companion: Classic and Contemporary Readings (Thousand Oaks, CA: Sage, 2002); and especially the five chapters devoted to data display in Miles, M.B. and Huberman, A.M., Qualitative Data Analysis: An Expanded Sourcebook, 2nd edn (Thousand Oaks, CA: Sage, 1994), 90–244. 21. This process is known as triangulation. For a fuller description of this topic, set in the context of researcher bias, see Schillewaert, N., De Ruyck, T. and Verhaeghe, A., ‘Connected research – how market research can get the most out of semantic web waves’, International Journal of Market Research 51 (1) (2009), 11–27; Griseri, P., Management Knowledge: A Critical View (Basingstoke: Palgrave, 2002), 60–78. 22. Fulton Suri, J. and Gibbs Howard, S., ‘Going deeper, seeing further: Enhancing ethnographic interpretations to reveal more meaningful opportunities for design’, Journal of Advertising Research 46 (3) (September 2006), 246–50. 23. Silverman, D., Doing Qualitative Research 3rd edn (London: Sage, 2009), 292–310. 24. Patton, M.Q., Qualitative Research and Evaluation Methods 3rd edn (Newbury Park, CA: Sage), 2002. 25. For a fuller explanation of validity in qualitative research, see Barnham, C., ‘Qualis? The qualitative understanding of essence’, International Journal of Market Research 52 (6) (2010), 757–73; Kirk, J. and Miller, M.L., Reliability and Validity in Qualitative Research (Newbury Park, CA: Sage, 1986). 26. Glaser, B.G. and Strauss, A.L., The Discovery of Grounded Theory (Chicago: Aldine, 1967). 27. Locke, K., Grounded Theory in Management Research (London: Sage, 2001), 1. 28. Goulding, C., Grounded Theory: A Practical Guide for Management, Business and Market Researchers (London: Sage, 2002), 40. 29. Glaser, B.G., Basics of Grounded Theory Analysis: Emergence v Forcing (Mill Valley, CA: Sociology Press, 1992), 16. 30. Tottman, P., ‘The Rashoman effect: Exploring the meaning of qualitative research analysis’, Market Research Society, Annual Conference (2010). 31. Baszanger, I., ‘The work sites of an American interactionist: Anselm L. Strauss, 1917–1996’, Symbolic Interaction 21 (4) (1998), 353–78. 32. Bryant, A. and Charmaz, K., ‘Grounded theory in historical perspective: An epistemological account’, in Bryant, A. and Charmaz, K. (eds), Handbook of Qualitative Research (Thousand Oaks, CA: Sage, 2007), 32–57. 33. Charmaz, K., ‘Qualitative interviewing and grounded theory analysis’, in Gubrium, J.F. and Holstein, J.A., Handbook of Interview Research (Thousand Oaks, CA: Sage, 2002), 683–90. 34. Böhm, A., Legewie, H. and Muhr, T., Kursus Textinterpretation: Grounded Theory (Berlin: Technische Universität, Bericht aus dem IfP Atlas, 1992), 92–3, MS. 35. Adapted from Charmaz, K., ‘Qualitative interviewing and grounded theory analysis’, in Gubrium, J.F. and Holstein, J.A., Handbook of Interview Research (Thousand Oaks, CA: Sage, 2002), 687.

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36. Ibid., p. 689. 37. Silverman, D., Interpreting Qualitative Data: Methods for Analysing Text, Talk and Interaction 2nd edn (London: Sage, 2001), 71. 38. Allan, D., ‘A content analysis of music placement in prime-time television advertising’, Journal of Advertising Research 48 (3) (September 2008), 404–17; Neundorf, A.N., The Content Analysis Guidebook (Thousand Oaks, CA: Sage, 2002); Wang, C.L., ‘A content analysis of connectedness vs separateness themes used in US and PRC print advertisements’, International Marketing Review 18 (2) (2001), 145. 39. Roberts, M. and Pettigrew, S., ‘A thematic content analysis of children’s food advertising’, International Journal of Advertising 26 (3) (2007), 357–67. 40. Voorveld, H., Neijens, P. and Smit, E., ‘The interactive authority of brand web sites: A new tool provides new insights’, Journal of Advertising Research 50 (3) (2010), 292–304; Ball, M.S. and Smith, G.W.H., Analyzing Visual Data (Thousand Oaks, CA: Sage, 1992), 15. 41. Bang, H.-K., Raymond, M.A., Taylor, C.R. and Moon, Y.S., ‘A comparison of service quality dimensions conveyed in advertisements for service providers in the USA and Korea: A content analysis’, International Marketing Review 22 (3) (2005), 309–26. 42. Glassner, B. and Corzine, J., ‘Library research as fieldwork: A strategy for qualitative content analysis’, Sociology and Social Research 66 (1982), 305–19. 43. Waksler, F., ‘Studying children: Phenomenological insights’, Human Studies 9 (1986), 71–82. 44. Berelson, B., Content Analysis in Communication Research (New York: Free Press, 1952). 45. Desai, P., Methods Beyond Interviewing in Qualitative Market Research (London: Sage, 2002), 84. 46. Lawes, R., ‘The research gallery’, Research (October 2003), 23. 47. Rowland, G. and Jaroslav, C., ‘Pushing the glamour button’, Research World (February 2008), 46–7. 48. Valentine, V., ‘Unlocking cultural codes’, ResearchWorld (October 2006), 15. 49. Gadsby, N., ‘Enchantment: Using semiotics to understand the magic of branding’, Market Research Society Annual Conference (2010); Desai, P., Methods Beyond Interviewing in Qualitative Market Research (London: Sage, 2002), 85. 50. Adapted from the Semiotics Solutions website (www. semioticsolutions.com), in Desai, P., Methods Beyond

Interviewing in Qualitative Market Research (London: Sage, 2002), 85. 51. Maggio-Muller, K. and Evans, M., ‘Culture, communications and business: The power of advanced semiotics’, Market Research Society Annual Conference (2006); Clegg, A., ‘Just a sign of the times?’, Marketing Week (19 August 2004), 36. 52. Wardle, J., Developing Advertising With Qualitative Research (London: Sage, 2002), 53. 53. Valentine, V., ‘Semiotics, what now, my love?’, Market Research Society Annual Conference (2007); Clatworthy, T. and Flanagan, C., ‘White light white heat’, Research (December 2003), 41. 54. Arning, C., ‘Viewpoint – semiotics: A winning formula?’, International Journal of Market Research 51 (3) (2009), 289–91. 55. Slater, D., ‘Analysing cultural objects: Content analysis and semiotics’, in Seale, C. (ed.), Researching Society and Culture (London: Sage, 2002), 233–44. 56. Derrida, J., Positions, A. Bass (trans.) (Chicago: Chicago University Press, 1981). 57. Lawes, R., ‘Futurology through semiotics’, Market Research Society Annual Conference (2009); O’Shaughnessy, J. and Holbrook, M.B., ‘The linguistic turn in marketing research’, Journal of the Market Research Society 30 (3) (April 1988), 210. 58. Desai, P., Methods Beyond Interviewing in Qualitative Market Research (London: Sage, 2002), 97. 59. Ishmael, G. and Thomas, J.W., ‘Worth a thousand words’, Journal of Advertising Research 46 (3) (September 2006), 274–8; Packenham, L., ‘Can qual research benefit from data-analysis software?’, Admap 462 (June 2005), 48–9; Dembrowski, S. and HanmerLloyd, S., ‘Computer applications – a new road to qualitative data analysis?’, European Journal of Marketing 29 (11) (November 1995), 50; Wolfe, R.A., Gephart, R.P. and Johnson, T.E., ‘Computer-facilitated qualitative data analysis: Potential contributions to management research’, Journal of Management 19 (3) (Fall 1993), 637. 60. www.qsrinternational.com/solutions_case-studies-detail. aspx?view-153, accessed 14 February 2012. 61. Schmidt, M., ‘Quantification of transcripts from depth interviews, open-ended responses and focus groups: Challenges, accomplishments, new applications and perspectives for market research’, International Journal of Market Research 52 (4) (2010), 483–509.

10 Stage 1

Problem definition

Stage 2 Research approach developed

Stage 3 Research design developed

Stage 4 Fieldwork or data collection

Stage 5 Data integrity and analysis

Stage 6 Communicating research findings

Survey and quantitative observation techniques Know exactly what you want to measure – and then select a survey or observation technique that creates cooperative participants, willing to think and be honest.

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Objectives After reading this chapter, you should be able to: 1 discuss and classify survey techniques available to researchers, and describe various survey techniques; 2 identify the criteria for evaluating survey techniques, compare the different techniques and evaluate which is the best for a particular research project; 3 explain and classify the different quantitative observation techniques; 4 identify the criteria for evaluating observation techniques, compare the different techniques and evaluate which are suited for a particular research project; 5 describe the relative advantages and disadvantages of observation techniques and compare them with survey techniques; 6 discuss the considerations involved in implementing surveys and observation techniques in an international setting; 7 appreciate how digital developments are shaping the manner in which surveys and quantitative observation techniques are managed and applied.

Overview In this chapter, we focus on the major techniques employed in descriptive research designs: surveys and quantitative observation. Descriptive research (as explained in Chapter 3) has as its prime objective the description of something, usually consumer or market characteristics. Survey and quantitative observation techniques are vital techniques in descriptive research designs. Survey techniques may be classified by mode of administration as online, telephone surveys, face-to-face and postal surveys. We describe each of these techniques and present a comparative evaluation of all survey techniques. Then we consider the major observational techniques: personal observation including mystery shopping research, electronic observation and trace analysis. The use of the internet has reshaped how surveys are designed and delivered in manners that are more engaging for participants. To begin our discussion, we present two examples of how these digital developments are shaping the practice of survey and observation design. The first example illustrates how researchers designed and implemented an internet survey via mobile phone. The second example illustrates advances in outdoor communications and a means to measure the impact of individuals observing billboards and posters.

Real research

Location-specific mobile research1 Adidas Japan wanted to gauge the performance of an advertising campaign targeted at football fans. The company’s particular need was to assess whether the Tokyo-based campaign had succeeded in generating awareness outside the capital, via television coverage. In order to do this, the company decided to conduct a mobile survey at an international football match played in the city of Sendai. Fans were invited to participate via flyers handed to them as they entered the stadium. The flyers explained how to enter the survey with details of a prize draw and the chance of winning shirts signed by star players. The flyers generated a 29% hit rate on the survey home page and a 33%

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completion rate among fans visiting the site. For Adidas Japan this meant 333 completed questionnaires based upon the distribution of 3,500 flyers at the game. The survey took, on average, eight minutes to complete. This was a reflection that, at 18 questions, the questionnaire was rather long for a mobile survey. One of the strengths of this method was that participants were able to complete the survey at a time of their own choosing, but while the event was still fresh in their minds. Very few fans completed the survey during the game itself; the majority completed it after the game while travelling home.

The great outdoors goes digital2

Real research

Many outdoor poster and billboard locations have been converted to digital screens by JCDecaux (www.jcdecaux.co.uk) and Clear Channel (www.clearchannel.com). Advertisers are able to utilise the flexibility of the screens to show different copy at different times of the day and make live changes throughout a campaign. This flexibility allows smaller advertisers to rent space for a limited time, in effect hiring screen time. This also means that the medium competes with TV advertisements. Added to this ability to digitise outdoor advertisements is the increased ability to measure their impact. In Canada, scientists have developed Eyebox2 (www.xuuk.com/eyebox2), whereby infrared technology assesses how many passers-by turn to look at a display (and for how long). The data from these observations can be linked to point-of-sale data in stores to give even more powerful insights into the impact of a billboard.

Survey methods Survey method A structured questionnaire administered to a sample of a target population, designed to elicit specific information from participants.

Structured data collection Use of a formal questionnaire that presents questions in a prearranged order.

Fixed-response alternative questions Questions that require participants to choose from a set of predetermined answers.

The survey method of obtaining information is based upon the use of structured questionnaires administered to a sample of a target population. Participants may be asked a variety of questions regarding their behaviour, intentions, attitudes, awareness, motivations and demographic and lifestyle characteristics. These questions may be asked verbally, in writing or via a computer (including mobile devices), and the responses may be obtained in any of these forms. ‘Structured’ here refers to the degree of standardisation imposed on the data-collection process. In structured data collection, a formal questionnaire is prepared and the questions are asked in a prearranged order; thus, the process is also direct. Whether research is classified as direct or indirect is based on whether the true purpose is known to the participants. A direct approach is undisguised in that the purpose of the project is disclosed to the participants or is otherwise obvious to them from the questions asked (as explained in Chapter 7). The structured direct survey, the most popular data-collection method, involves administering a questionnaire. In a typical questionnaire, most questions are fixed-response alter native questions that require the participant to select from a predetermined set of responses. Consider, for example, the following question, designed to measure a dimension of students’ attitudes towards the way they are assessed in marketing research classes: I prefer written examinations compared with continual assessment

Strongly Agree Neutral Disagree Strongly agree disagree

n n n n n

The survey method has several advantages. First, the questionnaire is simple to administer. Second, the data obtained are consistent because the responses are limited to the alternatives

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stated. The use of fixed-response questions reduces the variability in the results that may be caused by differences in interviewers. Finally, coding, analysis and interpretation of the data are relatively simple.3 The disadvantages are that participants may be unable or unwilling to provide the desired information. For example, consider questions about motivational factors. Participants may not be consciously aware of their motives for choosing specific brands or shopping at particular stores. Therefore, they may be unable to provide accurate answers to questions about their motives. Participants may be unwilling to respond if the information requested is sensitive or personal. In addition, structured questions and fixed-response alternative questions may result in loss of validity for certain types of data, such as beliefs and feelings. Finally, wording questions in a consistent manner to all potential survey participants is not easy (see Chapter 13 on questionnaire design). In other words, the survey imposes the language and logic of the researcher on the questionnaire participants. Given this core characteristic of survey techniques, great care must be taken to ensure that the language and logic used in questionnaires are meaningful and valid to potential participants. Despite the above disadvantages, the survey approach is by far the most common method of primary data collection in marketing research, representing around 72% of all marketing research spending.4 Access to survey participants may be conducted through two routes (see Figure 10.1). The first is via traditional approaches to building sampling frames, i.e. through personal contact, directories and databases. (These will be discussed in more detail in Chapters 14 and 15.) The second is via the access panel (described in Chapter 3). In short, specialist companies (such as ResearchNow, www.researchnow.com) manage large panels of individuals who have agreed to take part in surveys that are relevant to their backgrounds, location and/or interests. Access panels primarily work for online surveys and have been instrumental in the

Figure 10.1 Survey methods

A classification of survey methods

Traditional sampling methods

Online survey

Access panel

Telephone survey

Traditional

Home or workplace

Mobile device

Face-to-face survey

Postal survey

CATI (computerassisted telephone interview)

Home or workplace

Street

CATI (computerassisted telephone interview)

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rapid growth of online surveys. However, it is possible to use the details of panel members to allow other methods of survey to be conducted. Survey questionnaires may be administered in four major modes: (1) online surveys; (2) telephone surveys; (3) face-to-face surveys; and (4) postal surveys. Online surveys can be conducted via the internet on devices in home and offices. The use of mobile devices in administering surveys could be classified as a telephone survey. While many mobile devices are indeed telephones, the majority of mobile device use is now for accessing services through the internet. Mobile devices enable consumers to access audio and video, while communicating via text, email, social media and web browsing. Globally there are more smartphones in circulation that have great power and functionality and are able to cope with an array of research engagements.5 We thus classify mobile devices as a form of online survey. Telephone surveys may be further classified as traditional telephone survey and computer-assisted telephone interviews (CATIs). Face-to-face surveys may be conducted in the home or workplace, as street surveys, or as computer-assisted personal interviews (CAPIs). The final major method, postal surveys, takes the form of the traditional hard-copy, self-completion survey administered through the post. We now describe each method.

Online surveys Online surveys can be conducted on devices in homes or the workplace, or administered on mobile devices. Unsurprisingly, given the broader trends in technology adoption, online surveys have now become the dominant means of delivering surveys. Some of the issues in terms of declining response rates are covered later in this book, but the following example illustrates why the online survey is so popular. The survey experience can be designed in a personalised manner, and it can be much cheaper and faster to administer compared with traditional phone or face-to-face survey methods.

Real research

Happy campers Hugh Inwood, Director at The Research Box (www.researchbox.co.uk), was approached by the British Holiday & Home Parks Association (BH&HPA) to develop an automated means of collecting customer satisfaction data. BH&HPA is an organisation representing the interests of the British holiday parks industry. Membership is made up of the owners and managers of park home estates, touring and tenting parks, caravan holiday home parks, chalet parks and self-catering accommodation. BH&HPA wanted to develop a single-visitor satisfaction survey that could be used by all its holiday park members. The aim of the survey was to provide all the parks with customer feedback, enabling them to benchmark their performance against other parks and to improve their own levels of customer service. The Research Box used Snap survey software (www.snapsurveys. com) to set up a system to host and collect responses from a single survey, but one that was personalised to the individual circumstances at over 2,000 parks. Questions asked were dependent on the accommodation type and facilities available. Each park had its own unique web link to its version of the survey questionnaire. Customers were invited to fill out the survey online, or to complete a paper version that the park then manually entered onto the system. The system was capable of collecting more than 100,000 survey responses a year. If any unfavourable comments were received, they were emailed directly to the

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relevant park the minute they were recorded, to enable it to take appropriate action. Each month, personalised survey reports were automatically produced and emailed direct to each park and stored online for future viewing. The reports contained park-specific analyses in the form of narrative, supported by summary tables, charts and lists of comments. They included benchmark comparisons between that park’s performance and other similar parks, and that park’s performance for the current month versus the equivalent period last year. The accumulated response data from all parks and for all periods are also available for analysis by The Research Box on behalf of BH&HPA. These analyses are used to identify industry trends and to act as supporting material for business or political case building.

Email surveys Email surveys can be seen as the forerunner to the development of online surveys. Although the main use of email in surveys is to send invitations to complete online surveys, text-based email surveys can be also convenient for participants because they require no facilities or expertise beyond those that they use in their day-to-day email communications. They can be particularly effective on mobile devices. To conduct an email survey, a list of email addresses is first obtained. The survey is written within the body of the email message, which is then sent out over the internet. Participants type the answers to either closed-ended or open-ended questions at designated places, and click ‘reply’. Responses are then data entered and tabulated in the manner of a postal survey, or imported with software that interprets the emailed responses and reads the answers directly into a format compatible with the requirements of an analysis package. Email surveys have several limitations, primarily being that they can appear dry and uninteresting.6 Given the advantages of other online survey methods, the popularity of the email survey is waning. The problems of the email survey for certain types of participant are illustrated in the following example.

Real research

Send an email? Err . . . sorry, you seem to have mistaken me for a sad old geezer7 Email is in steady decline as younger people switch to social networking, texting and instant messaging. According to the marketing research company comScore (www.comscore. com), the under 25s are abandoning email. Younger users say that email still has its uses, for receiving their favourite newsletters or when writing formal messages to strangers. As a result, many have taken to more personal forms of communication. The likes of Facebook, Instagram and messaging platforms ensure that people only ever get contacted by people whom they have already accepted as friends. A similar trend is developing worldwide and is likely to continue. ‘It’s an evolution’, said Ian Angell, a Professor of Information Systems at the London School of Economics. ‘This is how faxes have more or less disappeared.’

Given the technical limitations of most email systems, questionnaires cannot utilise programmed skip patterns, logic checks or randomisation. The limited intelligence of ASCII text cannot keep a participant from, say, choosing both ‘yes’ and ‘no’ to a question where only one response is meaningful. Skipping instructions (e.g. ‘If the answer to Question 5 is yes, go to Question 9’) must appear explicitly, just as on paper, as there is no automated routing. These factors can reduce the quality of data from an email survey and can require much post-survey data cleaning.8 There are also problems in locating accurate and current email address lists and, even if these can be located, given spam protection software, there is no guarantee that an email will reach intended participants.

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Online surveys using fixed and mobile devices Early versions of internet surveys were labelled as CAWI (computer-assisted web interviews) to follow previous acronyms within the research industry of CATIs (computerassisted telephone interviews) and CAPIs (computer-assisted personal interviews). The far simpler term ‘online’ is used for all internet surveys hosted on a website. Participants may be recruited online from potential participant databases maintained by either a research agency or a panel management company, or they can be recruited by conventional techniques (telephone, face to face or postal). Frequently, participants are not recruited, but those who happen to be visiting a website on which the survey is posted (or other popular websites) are invited to participate in the survey. Either all or every nth web visitor is allowed to participate. Web surveys offer several advantages over email surveys. It is usual to construct buttons, checkboxes and data entry fields that prevent participants from selecting more than one response where only one is intended, or from otherwise typing where no response is required. Skip patterns can be programmed and performed automatically, as in CATI or CAPI. It is possible to validate responses as they are entered. Additional survey stimuli, such as graphical images and links to other web pages, may be integrated into or around the survey. The visual layout and care taken in designing additional stimuli can do much for participant engagement. This can contribute to a higher-quality experience for participants, encouraging a more committed response. Researchers are also increasingly conducting online surveys using mobile devices. The smartphone and tablet offer many possibilities as tools that are in nearly every pocket or purse, providing both portability and immediacy for anytime, anywhere data collection. (The use of mobile devices for survey research is discussed in more detail in Chapter 18.) The following lists summarise the advantages and disadvantages of online surveys.9

Advantages •

•

Real research

Speed. Compared with other survey methods, especially when conducting international research, the time taken to conduct a survey can be reduced to a matter of days rather than weeks. Even if one includes the time taken to contact participants, to establish their willingness to take part in a survey, for them to reply, for the survey to be sent, for it to be completed and then emailed back (the procedure adopted to reduce the perception of ‘junk’ email), such a survey can be completed relatively quickly. The only other method that could match its speed would be the telephone survey. Cost. Once the electronic questionnaire is designed, it is almost as easy to mail it to 10,000 people as to 10, since there are no printing, stationery and postage costs. Preparing data for analyses needs less manual intervention and can be also much cheaper. Quality of response. A range of design features can be used to make the survey more appealing and interesting. Graphics can be used to create visual and moving forms of scaling to maintain the interest of participants, but also to put them in a frame of mind that elicits more from them. The following example illustrates how Sony views this advantage.

‘Surveytainment’10 Many of the methods Sony implemented in its online surveys included what it referred to as ‘surveytainment’. This encapsulated a way of making surveys more emotional, engaging and fun for participants. Surveytainment used eye-catching question types and technology, including audio and video clips, drag-and-drop rankings and collaborative tools. For example, by using a ‘whiteboard’ application participants could show Sony what made an attractive cover by rearranging and altering the images provided.

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Although more complex, it was also possible for participants to upload their own images or text. The key to making ‘surveytainment’ effective was in ensuring that the techniques increased participant understanding. For example, the more imagery on a screen, the less likely a participant may read any long question text, relying on inference versus the written word. Sony believed that the ideas behind ‘surveytainment’ had a unique importance in the music/entertainment industry as it introduced sound and imagery into questions that would otherwise be static or require participants to rely on recall. Before the aid of the web and digital recordings, song and video testing with large samples was limited and financially impractical. But no longer are tests based upon focus group responses to a CD on a stereo system; there can be thousands of active music enthusiasts, experiencing and responding to a song or video in their natural music listening habitat – online, and in their home, offices or anywhere!

•

Interviewer bias removed. The method maintains the key advantage of postal surveys in being able to present a consistent form of measurement. Data quality. Logic and validity checks can be built in, thus allowing the development of more personalised questionnaire designs. In areas where open-ended or ‘other – please state’ responses are required, the participant types in answers ready for analysis. Contacting certain target groups. Many participants may be reluctant to complete surveys by traditional methods such as postal and face-to-face surveys. Much of this reluctance can be attributed to the context of where the survey is administered and how comfortable participants are in these contexts. With the online survey, the participants are largely in control of the context and can respond in circumstances that they feel comfortable with. In addition, with the growth of access panels where participants sign up to take part in research projects, very precise definitions of participant types can be devised.

Disadvantages •

•

Sampling frames. There are a growing number of access panels that provide means to access particular types of participant. However, there are still major questions surrounding their representativeness and the motivations of panel members. 11 Email directories exist beyond access panels, but there can be questions about their currency, accuracy and means of classifying different types of target participant. Another sampling issue is that participants who are recruited through browsing or clicking through banner ads or sources such as Facebook are self-selecting and the researcher does not know whether those who choose to take part are really representative of a target population. Being able to generalise findings to a particular population becomes difficult with a self-selecting sample. Access to the web. Though access to the internet has grown enormously, and continues to grow in even remote and poor communities across the globe, the penetration of households and businesses can still vary within countries and across countries. For example, use amongst the over 65s is still limited in many countries. Much depends upon the characteristics of the types of participant that are being targeted for a survey. Even if they do have access to the internet, do they have access to the means to engage with the survey in the manner intended by the questionnaire designer? Technical problems. Depending upon the hardware and software that participants use, the questionnaire may not work as intended by the designer; this is particularly true with surveys that are completed on mobile devices where there are a very wide selection of screen sizes that may require more restraint in the graphic design of such surveys.12

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Telephone surveys As stated earlier, telephone surveys may be categorised as traditional or computer-assisted. As the use of internet surveys increases, telephone surveys have declined.

Traditional telephone surveys Traditional telephone surveys involve phoning a sample of participants and asking them a series of questions, using a paper questionnaire to record the responses. From a central location, a wide geographical area can be covered, including international markets. Given that telephone interviewers cannot give participants any visual prompts, they have to write down answers to any open-ended questions and may have to flick through the questionnaire to find appropriate questions for a particular participant (filtering). These surveys tend to be short in duration and have questions with few options as possible answers. Today, this approach is rarely used in commercial marketing research, the more common approach being CATI.

Computer-assisted telephone interviews (CATIs) CATI uses a computerised questionnaire administered to participants over the telephone with a questionnaire on a networked computer or a PC. The interviewer sits in front of a terminal and wears a small headset. The terminal replaces a paper questionnaire, and the headset substitutes for a telephone. Upon command, the computer dials the telephone number to be called. When contact is made, the interviewer reads questions posed on the screen and records the participant’s answers directly to the computer, ready for immediate analysis. The main benefit of CATI is the speed of collecting data and analyses. Speed is of the essence in subjects where participant attitudes and behaviour can change quickly, an example being the ‘latest’ toys that parents may wish to buy for their children. One of the most widespread uses of CATI is for political opinion polls. With CATI, the computer systematically guides the interviewer. Only one question at a time appears on the screen. The computer checks the responses for appropriateness and consistency. It uses the responses as they are obtained to personalise the questionnaire. Data collection flows naturally and smoothly. Interviewing time is reduced, data quality is enhanced and the laborious steps in the data-collection process, coding questionnaires and entering data into the computer, are eliminated. Because the responses are entered directly into the computer, interim and update reports on data collection or results can be provided almost instantaneously. The biggest drawback of CATI lies in participants’ willingness to be interviewed by telephone. In many countries the percentage of people who only have a mobile device is now greater than those who have a landline. In some countries the segment of the population that used only a mobile phone was dominant as far back as 2007, and in developing markets this trend is likely to only be more pronounced.13 There are many factors that make it very difficult to conduct telephone surveys. At times, the technique may be confused in the minds of participants with cold-call selling techniques. To overcome this problem requires interviewers who are trained to reassure participants and to make the interviewing experience worthwhile. In most businesses, phone calls are screened; how else could managers avoid calls from companies and individuals they do not want to talk to? Many businesses have set up formal procedures to minimise unnecessary calls to management. This is a hurdle that well-trained interviewers are taught to circumvent. Experienced interviewers can ‘run the gauntlet’ of three or four screenings and still secure an interview without in any way upsetting the interviewee.14

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Face-to-face surveys Face-to-face surveying methods may be categorised as home, workplace, street or computerassisted. As a proportion of global spend on marketing research techniques, face-to-face surveys are in decline, one of the main reasons being the costs involved, as illustrated in the following example.

Real research

European Social Survey15 The European Social Survey (ESS) (www.europeansocialsurvey.org) is an attitude survey time series carried out in over 30 countries across Europe. The survey began in 2001 and fieldwork is carried out from September to December every two years. The questionnaire consists of two parts: a core section that is repeated every round, and two rotating modules that are repeated less frequently. The core modules include subjects such as media consumption, political and social trust, religious identification and sociodemographic background data, while the rotating modules each cover a substantive topic in more detail. Rotating modules so far have covered topics such as well-being, work–life balance, ageing, welfare attitudes, immigration and citizenship. To help ensure equivalence of outputs, the hour-long survey interview is conducted face to face in all countries. This mode was initially chosen not only because it tends to get the highest response rates and is the only mode that offers complete coverage in all countries, but also because the ESS questionnaire is particularly well suited to face-to-face interviews. In particular, it involves a long interview, many showcards and some complex routing. It is, however, becoming clear that using face-to-face interviewing as the sole mode of data collection might now need to be reconsidered in view of its rising cost and diminishing response rates. In addition, different countries have different experiences and expertise as well as different penetration of data-collection modes, which means they may be better equipped to use a different mode.

Home or workplace surveys In face-to-face home or workplace surveys, participants are interviewed face to face in their ‘personal space’. The interviewer’s task is to contact the participants, ask the questions and record the responses. In recent years, the use of face-to-face home and workplace surveys has declined due to their high cost. However, there are many situations where they are used because of the reassurances of quality of the interview process, the comfort of the context felt by certain participants and the nature of the questions that are being administered. The following example illustrates such a case where it was paramount to use a face-to-face home survey.

Real research

PARC: 360-degree view of the consumer16 The Pan Arab Research Centre (PARC) (http://arabresearch.iniquus.com/) conducts an ongoing, comprehensive study of the Arab Republic of Egypt. The scope of the survey covers product and brand usage, media exposure, lifestyle and attitudes, daily activities, shopping behaviour and leisure activities. Fieldwork is conducted across different seasons of the year and consists of approximately 5,000 interviews. Two different methods are used to question participants: first, a home interview is used to collect demographics

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and data related to media exposure (including magazines, newspapers, radio, TV and internet). Second, at the end of the interview, fieldworkers leave behind a selfcompletion questionnaire covering personal and household usage of more than 400 product categories and services and 5,000 brands, as well as attitude and lifestyle statements. A wide range of techniques have been used to elicit the full cooperation of participants. Listed households were informed by mail that they would be contacted by an interviewer. Up to six separate attempts were made to contact difficult-to-reach participants. Households presenting language barriers were reassigned to specifically qualified interviewers, as were refusals and other unusual cases.

As well as using face-to-face surveys for ad hoc studies, they are also widely used by syndicated firms for omnibus surveys, as illustrated in the following example.

Real research

Millward Brown Ulster omnibus survey17 The omnibus survey is a cost-effective means of measuring and tracking consumer awareness, behaviour and attitudes. Each omnibus survey incorporates a range of topics. The costs for each survey are directly shared between clients in proportion to the number of questions each decides to include. However, the questions included and the ensuing results are exclusive to each client, with each section treated completely confidentially. The Ulster omnibus survey is based upon a nationally and regionally representative sample of 1,000 adults aged 16 or over, in Northern Ireland. It is conducted twice monthly by personal surveys conducted in-home. The omnibus survey delivers extensive background information on the participants and their household. This covers standard demographics of gender, age, socio-economic group, ethnicity, working status, marital status, household size, presence and age of children in the household, religion, mobility and tenure, through to issues such as internet access. All of this information is available, either for targeting questions or for cross-analysis, to determine any significant differences in responses by segments. Applications of the Ulster omnibus survey include: •

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Advertising. The majority of Northern Ireland’s high-profile advertising campaigns have used this omnibus to benchmark attitudes pre-campaign and track them postcampaign to measure advertising effectiveness. Charities. The methodology has been used by many charities to measure awareness, behaviour and attitudes towards specific organisations, their messages and donation giving. Health. Changing attitudes and behaviour in the area of personal health and activity have been routinely assessed using the omnibus survey. Some aspects of behaviours that have been monitored include issues such as smoking, drinking, healthy eating, recreational drug use and physical activity.

Face-to-face surveys are used extensively in business-to-business research for participant subjects who cannot be effectively interviewed by telephone or post. Managers being interviewed have the comfort and security of their office and can control the timing and pace of the interview. For the researcher, the big benefit of meeting managers in their office is the ability to build up a rapport, probe and gain the full attention of the manager.

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Street surveys For street surveys, participants are intercepted while they are shopping in city centres or shopping centres. They may be questioned there and then in the street, or taken to a specific test facility. In the testing of new product formulations, test facilities are ideal to allow participants the time and context to sample and evaluate products. The technique can also be used to test merchandising ideas, advertisements and other forms of marketing communications. The big advantage of the street survey is that it is more efficient for the participant to come to the interviewer than for the interviewer to go to the participant.18

Computer-assisted personal interviews (CAPIs) In CAPI, a computer partially replaces the interviewer. There are several user-friendly software packages that design easy-to-use surveys with help screens and understandable instructions. The use of colour, graphical images and on- and off-screen stimuli can all contribute to making the interview process both interesting and stimulating. This method has been classified as a face-to-face survey technique because an interviewer is usually present to guide the participant as needed. CAPI has been used to collect data at test facilities from street surveys, product clinics, conferences and trade shows. It can be used in a kiosk format at locations such as museums or heritage sites to conduct visitor surveys. It may also be used for home or workplace surveys. The following example illustrates an application of CAPI where many visual aspects of football sponsorship could be displayed for questioning.

Real research

Brands fall short of their goal19 Major consumer brands use a plethora of sports sponsorship platforms, from players to stadiums, to communicate with a global consumer market and gain international exposure and recognition. Sporting events are an effective vehicle to gain access to a swathe of potential customers yet, according to the CAPI study conducted by TNS Sport, young people and children have a greater awareness than adults of those brands that sponsor leading football clubs. Its research among people who watch football on TV revealed that spontaneous recall of brands by adults (aged over 16) across a range of sponsors was generally less than that of children (aged 10–19).

A major development for marketers, especially in financial services, has been the use of customer satisfaction surveys to guide strategic and operational decisions. With traditional survey techniques, the interviewer may have to carry a huge questionnaire to cope with questions that measure attitudes to a range of banks and a range of services taken from those banks. With CAPI, when a particular bank is chosen, particular questions may be filtered out, and choosing a particular service from that bank can filter out further questions. Questions specific to the participant may then be asked, making the interview process far more efficient.

Postal surveys In the postal survey, questionnaires are mailed to preselected potential participants. As with other forms of ‘offline’ market research, postal surveys have sharply declined in use. A typical mailed package consists of the outgoing envelope, cover letter, questionnaire, return

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envelope and possibly an incentive. The participants complete and return the questionnaires. There is no verbal interaction between the researcher and the participant in the survey process.20 There may be an initial contact with potential participants, to establish the correct person to send the questionnaire to, and to motivate them before they receive the survey. Before data collection can begin, a sampling frame needs to be compiled so that potential participants can be identified. Therefore, an initial task is to obtain a valid mailing list. Mailing lists can be compiled from telephone directories, customer databases or association membership databases, or can be purchased from publication subscription lists or commercial mailing list companies.21 Regardless of its source, a mailing list should be current and closely related to the population of interest. (Chapters 13 and 14 will

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