Marketers Using Generative AI Have Witnessed Positive ROI - Spiceworks (2023)

  • Generative AI tools like ChatGPT, Dall-E, and Bard are changing how professionals and organizations work. Similarly, they offer huge opportunities for marketers.
  • So, how are marketing professions using generative AI? And what more can they do? conducted a study to find out.

Artificial intelligence (AI) has gained much importance in the last decade. Despite a brief lull in the last couple of years, the arrival of ChatGPT, Bard, Dall-E, and other generative AI chatbots and systems has reignited the interest in AI systems. These generative AI tools offer massive opportunities to marketers.

But how are marketers using them, and how are these tools affecting business outcomes? recently conducted a study to find the answers. One key finding is that while marketers have started using generative AI, they are underutilizing the chatbots part of it. Here are a few insights in detail.

Most Marketers Use Generative AI To Create Social Media Copies and Images

Generative AI is similar to many other tools. Marketers can use it for several things, from creating content copy and images to sales collaterals, within a short time. The content it generates is not perfect. But marketers can use it to produce the final product faster.

Given that generative AI has many applications, it is unsurprising that marketers are adding generative AI to their toolkits. So, what exactly are marketers using it for? The study found that 44% of marketers use it to create email copy, while 42% use it to create social media copy. About 39% are also using it to create social media images.

Marketers Using Generative AI Have Witnessed Positive ROI - Spiceworks (1)

Types of content marketers are generating using generative AI

Source: The State of GenAI Chatbots in Marketing reportOpens a new window

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Specifically regarding the content format, 69% of respondents use generative AI to create images, 58% to generate text, and 50% to create audio and video files. However, only 37% use it as chatbots, and 36% use it to generate code snippets.

Only about 17% of marketers said they don’t use generative AI. This means that generative AI has become common in small and large companies.

Among the non-adopters, 31% expect to start using the tools within the year, and 46% expect to start using them within two years.

All that said, there is a split in how to use AI in the content creation process. At least two-thirds use generative AI for creative brainstorming sessions, outlines, and first drafts and 49% use it to generate final content. Further, 78% using generative AI are B2B companies, while 65% are B2C.

The most popular generative AI tools, according to the respondents, are ChatGPT (55%), (42%), (36%), (29%), Lensa (28%), Dall-E (25%), and MidJourney (24%).

See more: The Future of AI in Sales: Embracing Generative Technologies

Training Teams Is the Biggest Hurdle in Adopting Generative AI

While generative AI is witnessing increased adoption and benefits, companies face certain roadblocks in its adoption. The most common hurdle in its adoption is the team training required to use it effectively, with almost 50% citing this as an issue. About 45% considered the cost of generative AI, and 45% considered privacy and security concerns as hurdles. A few other challenges include data scarcity (31%), poor content quality (29%), and unethical biases (24%).

Content quality and unethical biases are valid concerns, given that generative AI is similar to general AI; the quality of the output depends on the data it has been trained on. If the input is biased or incorrect data, the output will be prejudiced or false information. Hence, marketers should choose their AI tools carefully to reduce the risk of false information slipping through the cracks.

About three-quarters of respondents said their AI tools were trained on their proprietary content. This theoretically circumvents the problem by removing erroneous data from the pools that internal and proprietary generative AI use.

Marketers Witness Increased Performance Due to Generative AI

Marketers have seen several benefits of using generative AI to develop content. About 58% cited improved performance as the most important benefit. Other creative processes have seen similar benefits. About 50% cited increased creative variety, and 47% reported faster creative cycles. Of the companies using generative AI, 66% have seen positive ROI, with many seeing up to 3x ROI. Further, 50% said cost efficiencies improved over time.

Chatbots Can Fuel Better Outcomes

While marketers are utilizing generative AI for various purposes and reaping several benefits, the study shows that organizations aren’t using the technology to the full extent. One under-valued way to generate value with these tools is to leverage chatbots, which can improve marketers’ ability to reach and engage with customers significantly. Organizations can use today’s advanced AI-powered chatbots to enhance their business strategy and improve the overall customer experience (CX). They can streamline customer interactions and create a more personalized and engaging experience for users. This, in turn, can help organizations drive growth.

When integrated with other generative AI applications, chatbots enable businesses to create more targeted and personalized campaigns. Companies can stay ahead of the curve and ensure long-term success in today’s marketing landscape. And companies can introduce chatbots into their workflows easily.

Marketers can implement chatbots in generative AI-driven marketing in the following ways.

1. Personalization and customer segmentation

Chatbots can be programmed to analyze user data and preferences to create personalized experiences. This helps companies segment their target audience more effectively and tailor campaigns based on audience interests, behavior, and preferences.

2. Customer support

Companies can use AI chatbots to provide 24/7 customer support that can handle a wider range of tasks. By offering quick and accurate assistance, chatbots help companies retain customers and reduce the burden on human customer support representatives.

3. Lead generation and nurturing

Chatbots can engage effectively with prospective customers, gather relevant information, and qualify leads based on certain criteria. Companies can also use chatbots to nurture leads by sending personalized content and follow-up messages to keep them engaged.

4. Enhance other generative AI tools

Companies can combine chatbots with other generative AI tools to improve the latter’s capabilities. For example, content creation tools can leverage a chatbot’s interactions with users to generate personalized messages or marketing materials. This can lead to a more effective campaign.

5. Acquire data insights

Companies can collect valuable user information and insights using chatbots, which they can use to improve marketing strategies and optimize CX. By analyzing the data and insights, companies can identify pain points, trends, and improvement opportunities.

See more: 4 Ways AI Is Changing Content Creation and Marketing as We Know It

Transform Marketing With Generative AI

Generative AI is changing what it means to be a marketer. Today people in various marketing roles are using tools like ChatGPT to ease their work and become more productive. While they are reaping several benefits from generative AI, marketers still lag in leveraging these tools to their fullest potential.

Leveraging these tools as chatbots can make them a force multiplier, as they can help marketers deliver highly targeted and personalized campaigns and engage their audience better. Hence, marketers should consider incorporating these chatbots into their workflow to gain an edge in today’s competitive market.

How are you using generative AI in your marketing efforts? Share with us on FacebookOpens a new window , TwitterOpens a new window , and LinkedInOpens a new window .

Image source: Shutterstock


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Marketers Using Generative AI Have Witnessed Positive ROI - Spiceworks? ›

About 50% cited increased creative variety, and 47% reported faster creative cycles. Of the companies using generative AI, 66% have seen positive ROI, with many seeing up to 3x ROI. Further, 50% said cost efficiencies improved over time.

What are the risks of generative AI? ›

Without proper governance and supervision, a company's use of generative AI can create or exacerbate legal risks. Lax data security measures, for example, can publicly expose the company's trade secrets and other proprietary information as well as customer data.

What are the uses of generative AI? ›

Generative AI is a type of artificial intelligence technology that can produce various types of content, including text, imagery, audio and synthetic data.

What is the role of AI in content marketing? ›

Artificial intelligence enables marketers to focus more on the customer and take care of their needs in real time. Data that algorithms collect and generate makes it easy for marketers to understand what content to target at customers, and which channel to use at which time.

How AI will change content creation? ›

AI plays a vital role in creating tailor-made content that targets specific audiences. With the help of AI algorithms, marketers can track customer preferences and customer personas to understand their likings. This helps marketers create content that resonates with the audience and increases customer engagement.

What is the disadvantage of generative models? ›

Generative AI models can be difficult to explain. It's hard to understand why the model made a particular prediction or how it arrived at a certain conclusion. This can be a major issue for businesses that need to explain their decisions to stakeholders.

What is the disadvantage of generative design? ›

Generative design also comes with drawbacks, though not necessarily of its own doing. The biggest is its potential to automate many jobs and make human workers redundant. That's especially true in the construction industry. Wood trades, painters, plasterers, floorers, and decorators are also vulnerable to automation.

Why is generative AI so popular? ›

Generative AI tools reduce the money and time needed for content creation, thereby boosting productivity and profitability. The rise of generative AI also breeds innovation, paving the way for new business models and applications.

What are the best use cases for generative AI? ›

Use cases for generative AI
  • Produce original content. Create short stories, essays, songs, art, images, and other new content by providing generative AI with natural language prompts.
  • Generate code. ...
  • Expedite customer service. ...
  • Summarize documents.

What is generative AI and how much power does it have? ›

Generative AI refers to deep-learning models that can generate high-quality text, images, and other content based on the data they were trained on. Generative AI refers to deep-learning models that can generate high-quality text, images, and other content based on the data they were trained on.

What is the impact of AI on digital marketing? ›

Chatbots: AI-powered chatbots can provide personalized marketing messages and customer recommendations based on their past behavior and preferences. This can help digital marketers create a tailored customer experience.

How do brands use AI in marketing? ›

AI in marketing and advertising is used to segment customers, message them at optimal times and personalize campaigns. Oftentimes, AI also works to automate these processes to save businesses time and money. These companies below use AI to create advertising campaigns and fine-tune marketing strategies.

How does AI contribute to marketing analytics? ›

AI in marketing analytics helps analyze vast data, identify patterns, and forecast trends to optimize campaigns, improve targeting, personalize content, and enhance customer engagement, ultimately increasing ROI.

What is an example of generative AI? ›

For example, generative AI can be used by physicians to develop custom care plans for patients that will improve health outcomes. Another healthcare use case for generative AI is the improvement of images resulting from MRI, CT and PET scans.

What are the benefits of AI in content creation? ›

What are the pros of AI-generated content?
  • Efficiency and scalability. AI can create content much faster than people, which is probably the biggest benefit. ...
  • Cost-effective. ...
  • Improves SEO. ...
  • Overcome writer's block.
Mar 29, 2023

How will generative AI change the world? ›

AI Will Help Create and Run Websites and Web Apps

There are already tools available that can help you build websites without coding, and generative AI will take this capability to the next level. In the near future, AI will not only help you create websites and web apps, but also run them on autopilot.

What are the benefits of generative model? ›

Generative modeling is used in unsupervised machine learning as a means to describe phenomena in data, enabling computers to understand the real world. This AI understanding can be used to predict all manner of probabilities on a subject from modeled data.

What is the advantage of generative model? ›

However, generative models have the advantage of being able to generate new data samples, which can be useful for tasks such as data augmentation. Generative models are often easier to train, but they can be less accurate than discriminative models. The choice of model depends on the application and the type of data.

What are the challenges of generative models? ›

Generative AI models can be complex and opaque, making it difficult to understand how they are making their predictions. This can be a challenge when trying to ensure that the model is making fair and unbiased decisions.

Why generative design is the future? ›

In the future, generative design will also improve the ability of humans and software to work in tandem. Workflow and interface improvements will help designers set up their problems more robustly, encoding more of their experience before the designs are generated.

Is generative design expensive? ›

$200 USD/month

If you haven't started using generative design yet, check out our Fusion 360 30-day trial and getting started content to see how generative design can help you improve your design and engineering processes. Learn more about and purchase generative design at the button below.

What is the purpose of generative design? ›

Generative design lets you create optimized complex shapes and internal lattices. Some of these forms are impossible to make with traditional manufacturing methods. Instead, they're built using new additive manufacturing methods.

How generative AI will change marketing? ›

Generative AI can expand a marketer's value — and make work more engaging — by giving them the ability to do more quality work faster and shift their mental energy and time to tackle the strategic work that machines can't duplicate.

How does generative AI affect businesses? ›

Using large language models with generative AI allows businesses to reduce labor costs while increasing efficiency and developing more personalized customer experiences.

What is the future of marketing with generative AI? ›

Generative AI can augment, accelerate, and create new content and experiences. The ability to create original content, synthetic data, models of physical objects, and code to improve response time to customer engagement is providing breakthrough innovation opportunities for marketing.

What industries will be disrupted by generative AI? ›

As such, jobs focused on delivering content — writing, creating images, coding, and other jobs that typically require an intensity of knowledge and information — now seem likely to be uniquely affected by generative AI.

What industries use generative AI? ›

Generative AI is impacting the automotive, aerospace, defense, medical, electronics and energy industries by composing entirely new materials targeting specific physical properties.

What is the value of the generative AI market? ›

[385 Pages Report] The market for generative AI is anticipated to increase from USD 11.3 billion in 2023 to USD 51.8 billion by 2028, at a CAGR of 35.6% over the course of the forecast period.

How will generative AI affect the economy? ›

A recent report by Goldman Sachs suggests that generative AI could raise global GDP by 7%, a truly significant effect for any single technology.

How big is the generative AI market? ›

According to Precedence Research, the global generative AI market size valued at USD 10.79 in 2022 and it is expected to be hit around USD 118.06 by 2032 with a 27.02% CAGR between 2023 and 2032.

What is the positive impact of AI in marketing? ›

The positive impact of AI on Marketing:

With the help of AI, marketers can analyze customer data and behaviour, segment their target audience, and personalize their marketing efforts. This can lead to better engagement, higher conversion rates, and increased customer loyalty.

How AI is an advantage in marketing? ›

Understanding your audience better: AI helps you analyse large amounts of data and predict every customer's buying behaviour/decisions. This allows you to effectively implement dedicated marketing campaigns to a target audience. It also helps in boosting customer satisfaction and engagement.

How does AI improve marketing? ›

AI marketing can help you deliver personalized messages to customers at appropriate points in the consumer lifecycle. It can also help digital marketers identify at-risk customers and target them with information that will get them to re-engage with the brand.

How AI can be used in marketing to provide lead generation? ›

Ultimately, AI-powered lead segmentation allows marketers to tailor their messaging to specific customer pains and needs. More personalized interactions directly influence buying behavior and result in a 10-15% increase in revenue.

What is an example of using AI in marketing? ›

Starbucks is one example of a brand using its loyalty card and mobile app to collect and analyze customer data. They announced plans for personalization back in 2016. Since then, they've built quite the app experience. It records purchases, including where they are made and at what time of day.

What are the most popular generative AI? ›

Generative AI Apps and Tools: Table of Contents
  • GPT-4.
  • ChatGPT.
  • AlphaCode.
  • GitHub Copilot.
  • Bard.
  • Cohere Generate.
  • Claude.
  • Synthesia.
May 2, 2023

What are the famous generative AI models? ›

Notable generative AI systems include ChatGPT (and its variant Bing Chat), a chatbot built by OpenAI using their GPT-3 and GPT-4 foundational large language models, and Bard, a chatbot built by Google using their LaMDA foundation model.

How popular is generative AI? ›

The generative AI market size reached 10.3 billion US dollars in 2022, and it is anticipated to reach $53.9 billion by 2028, growing at a compound annual growth rate (CAGR) of 32.2%. Generative AI images and chatbots are some of the generative AI examples that keep getting bigger in the market daily.

What is content strategy using AI? ›

The Role of AI in Content Strategy

AI can enhance the skills of content teams by assisting them with audience insights, content ideas and much more. With AI's abilities, content marketers can take their strategy and results to the next level.

Who are the main players in generative AI? ›

The global generative AI market is dominated by key players such as Adobe, Inc., Amazon Web Services, Inc., D-ID, Genie AI Ltd., Google LLC, IBM Corporation, Microsoft Corporation, MOSTLY AI Inc.,, and Synthesia.

What are the recent developments in generative AI? ›

The recent developments in generative AI have been driven by advancements in deep learning algorithms and hardware, such as GPUs and TPUs. These advancements have enabled the creation of more complex and sophisticated generative models.

How do I incorporate generative AI? ›

Several key steps must be performed to build a successful generative AI solution, including defining the problem, collecting and preprocessing data, selecting appropriate algorithms and models, training and fine-tuning the models, and deploying the solution in a real-world context.

What are the cons of generative adversarial networks? ›

Disadvantages of Generative Adversarial Networks

This is because the two networks in a GAN (the generator and the discriminator) are constantly competing against others, which can make training unstable and slow. Additionally, GANs often require a large amount of training data in order to produce good results.

What are the disadvantages of human centered AI? ›

Cons of Human Centered AI

Human-centered AI advanced technology is beneficial but it does pose some risks. The most concerning risks are misuse of technology, loss of jobs, and a negative impact on human capabilities.

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