Beyond the Buzz: Creating Marketing Value with Generative AI
Online veröffentlicht: 25. Apr. 2024
Seitenbereich: 50 - 55
DOI: https://doi.org/10.2478/nimmir-2024-0008
Schlüsselwörter
© 2024 Fabian Buder et al., published by Sciendo
This work is licensed under the Creative Commons Attribution-NonCommercial 4.0 International License.
The technological leap in generative AI has aroused much excitement and speculation in the marketing industry, fueling a narrative that presents generative AI as a cure-all for various marketing challenges. This hype is driven by the promise of the effectiveness and almost limitless efficiency of AI tools that seem to be able to automate tasks, including complex data analysis, content creation and the personalization of customer experiences. Amid this enthusiasm, however, critical questions arise: What is the reality beyond the hype? How is generative AI actually being used in marketing, and what are the implications and challenges for marketers and organizations? A study by the Nuremberg Institute for Market Decisions (NIM) examines the usage and perception of generative AI tools among B2C marketing professionals (see Box 1).
In the rapidly evolving world of marketing, generative AI tools have already become a staple. Every marketing professional interviewed reported that they were already using generative AI to some extent. Nearly half of the respondents reported significant or even predominant use of AI tools for their marketing activities. Moreover, there was a strong consensus among respondents that generative AI will significantly improve their marketing activities, with almost two-thirds expecting a substantial improvement (see Figure 1).
Figure 2 lists the marketing activities for which marketers are using generative AI. Notably, the top five activities include tasks that require extensive data handling and analytical processing. It appears that generative AI has been quickly adopted as a standard means of facilitating not only data analysis but also market research and insight generation. The preference for AI in these areas suggests that marketers recognize its efficiency as well as its ability to generate plausible interpretations of data and information that are either too large or too complex for manual processing.
The study focused on assessing the use, benefits and challenges of generative AI in marketing. From the end of October to the middle of December 2023, insights were gathered from 600 B2C marketing professionals through computer-assisted telephone interviews with web screen sharing in three major markets: Germany, the United Kingdom and the United States. Small (100–249 employees), medium (250–499 employees) and large (500+ employees) companies were represented in roughly equal shares.
It is hardly surprising that generative AI is being used extensively by many marketers to create, summarize and translate text. One notable finding, however, is the extent to which respondents are using generative AI in the ideation process, such as brainstorming and idea generation. This application may represent a shift in creative processes, as AI is now being used as a tool to inspire and generate new marketing ideas. This underscores the growing recognition of AI's value in not only performing analytical tasks but also contributing to the creative aspects of marketing, an area long considered one of the last bastions of exclusively human skill. Other marketing tasks involve a more moderate to low level use of generative AI. These include specialized tasks such as video and audio content generation and programming as well as more general activities such as campaign planning and decision-making.
Despite the widespread adoption of generative AI for a multitude of marketing activities, the essential question remains: Where does AI truly excel? Beyond the initial excitement about this new technology, where does AI significantly increase efficiency, improve the quality of results or reduce costs? In our quest to understand the tangible value that generative AI tools bring to marketing, we zeroed in on the “heavy users” – those professionals who reported significant or predominant use of generative AI for a specific task (Figure 2). These were the main findings:
Heavy users have found that generative AI excels at saving time and significantly accelerating market research and content creation tasks. AI's ability to swiftly process large data sets and collect and summarize information allows marketers to gain timely insights and quickly adjust strategies. In content creation, AI helps overcome the challenges of producing customized text and images in a timely manner, thereby increasing productivity.
AI is being recognized not only for its speed but also its potential to improve the quality of marketing output. In conducting market research and data analysis, as well as in creating text content, experienced users report much higher quality when using generative AI tools. In addition, AI helps to generate higher-quality ideas, a critical component for differentiating marketing strategies in a competitive landscape.
FIGURE 1
Usage of generative AI tools in marketing and the expected improvement resulting from their use
In terms of cost-effectiveness, the perception of the value of generative AI is more nuanced. Savings are most evident in tasks involving traditionally high external costs, such as content creation and market research. AI's ability to streamline these processes can reduce reliance on external resources, lowering overall costs. AI-driven personalization and technical tasks such as programming also benefit from cost reductions.
These findings underscore the potential of the technology to enhance the speed and quality of marketing tasks and to bring about cost savings, especially in content-related and analytical functions. Still, while generative AI may offer clear benefits, its effective use in practice hinges on understanding its capabilities and limitations.
The understanding and use of generative AI in marketing appear to be interrelated: More knowledge about AI often goes hand in hand with more extensive use, which in turn can foster a deeper understanding. In addition, more frequent usage of generative AI typically comes with an increased recognition of its benefits. While these correlations don’t necessarily imply causation, they do indicate that enhancing knowledge might be a crucial factor in boosting AI usage, especially since it represents an area that companies can actively influence.
FIGURE 2
Usage and benefits of generative AI for marketing activities
Our research reveals a critical knowledge gap among marketers in key areas related to the legally and ethically sound use of generative AI. While most respondents feel they have a basic understanding of generative AI and how it works, 43% of professionals state that they have only limited knowledge at best of the legal implications of using generative AI content, while 38% admit to having a knowledge gap regarding the ethical use of AI content in marketing. These findings highlight an urgent need for companies to invest in skill development to ensure legal compliance and ethical integrity. In addition, a significant share of marketers admit that they have not fully understood important practical aspects of AI application, such as content curation, prompt writing and the integration of AI output into campaigns. This points to another area where skills need to be developed to realize the full potential of generative AI in marketing. Importantly, our findings suggest that companies should think about providing development opportunities beyond formal in-house trainings or degrees. The marketing professionals in our study found hands-on experimentation with AI tools in projects and participation in industry conferences and webinars particularly beneficial for skill enhancement in generative AI.
Knowledge seems to be a crucial point in the context of generative AI in marketing, yet the organizational environment is also likely to play a pivotal role in enabling professionals to successfully apply AI. Aside from legal and ethical challenges regarding customer data privacy and biased algorithms, respondents identified problems with the integration of AI in existing infrastructure and processes, high costs and a lack of organizational expertise and clear policies as being among the top barriers to effective AI use.
So what can organizations do to better facilitate the use of generative AI in marketing? We found that marketers who use generative AI more extensively often work in environments that have certain organizational characteristics. These include having dedicated resources and budgets for AI initiatives, which ensures that the essential components for AI adoption are in place. Beyond monetary investment in AI, these companies incorporate generative AI as a core component of their marketing strategy. This means not only having the right tools in place, but also aligning their use with the company's overall marketing goals. Finally, these companies successfully foster a culture where sharing insights and best practices around generative AI is commonplace. While these findings do not establish causation, they do suggest avenues for companies looking to leverage generative AI for more sophisticated, efficient and effective marketing outcomes.
Generative AI is not just a passing trend in marketing; it is a transformative force that is already reshaping how marketing professionals actually work and make decisions. By speeding up market research and content creation, improving the quality of analytical and market research tasks, text generation and ideation, and offering the potential for cost efficiencies, AI is proving to be a valuable asset in the marketing toolkit of experienced, knowledgeable users. Applications may even go beyond operational improvements and entail a more strategic shift, with AI evolving as a partner in creativity and marketing planning.
For marketers, the key takeaway is this: Embrace the practical uses of AI in your strategies while being mindful of its limitations and the challenges of integrating it at both the user and organizational levels.