Can AI Replace Marketing Strategy?

EVP and global head of strategy, Martyn Clarkson went head-to-head with Chat GPT to find out.

When I decided to write an article about AI’s potential in marketing strategy, I thought, “That’ll be easy; I’ll get Chat GPT to write it and just tell it where it’s wrong.”

But I’ve learned that nothing goes exactly to plan with AI. Getting AI to do the hard work of pen to imaginary paper didn’t happen. I had to interact, ‘discuss,’ incorporate and acquiesce to get something that represented a good POV. And through that process, Chat GPT managed to wedge in some different opinions and some of what it called ‘balance.’ Chat GPT is intently focused on balance, borne out of its programming to counter inherent bias and gaps in data.

It’s a good thing, but balance is probably the risk and reward of AI in marketing strategy. Because good strategy is ultimately a choice made with conviction. It’s a POV. It’s an opportunity that comes with opportunity cost. It’s a stake in the ground – something AI doesn’t do.

At its heart, a great strategy is a “compelling opportunity made simple and achievable.” And what I learned from my conversation was that choice is something that only humans feel comfortable undertaking, at least for now.

I set out with the goal of not editing the final article. I made 30 prompts covering content, format, language, style, and personality, but in the end, I had to knit some pieces together. Like an over-enthusiastic intern, Chat GPT will change what you ask it to and several other great parts just because they can’t contain their excitement. I made some edits to my lines – but all views of Chat GPT are its own.

So here we go, a co-authored article from Me & Chat GPT:

AI and Chat GPT in Marketing Strategy and Research: A Conversation

In recent years, using artificial intelligence (AI) and Chat GPT in marketing strategy and research has become increasingly popular. While some see it as a game-changing tool that can revolutionize how businesses approach marketing, others remain skeptical of its capabilities and limitations. In this article, we explore the pros and cons of AI and Chat GPT in marketing strategy and research through a hypothetical conversation between a skeptic named Martyn and a Chat GPT supporter.

Martyn: So, can AI and Chat GPT help us understand our target market and develop better marketing strategies?

Chat GPT: Absolutely. AI and Chat GPT can analyze vast amounts of data, identify patterns and trends, and provide valuable insights that inform marketing strategy and research.

Martyn: But can AI and Chat GPT replace the human marketing element? Can they truly understand the nuances of human behavior and motivation?

Chat GPT: While AI and Chat GPT can’t completely replace human intuition and creativity, they can augment and enhance it. By providing data-driven insights and freeing up time and resources, AI and Chat GPT can help marketers focus on the areas where human expertise is most valuable.

Martyn: I’m still skeptical. What about bias and incomplete data? Can AI and Chat GPT really be trusted to make unbiased and accurate recommendations?

Chat GPT: AI and Chat GPT are only as good as the data they’re trained on, and that bias and incomplete data can skew their results. However, by being aware of these limitations and working to address them, AI and Chat GPT can still provide valuable insights and recommendations.

Martyn: OK, I see your point. But what about the hype around AI and Chat GPT? Is it all it’s cracked up to be?

Chat GPT: That’s a fair question. While there is certainly hype around AI and Chat GPT, it’s important to remember that they are still in the early stages of development and implementation. The Gartner Hype Cycle for Emerging Technologies can be a helpful framework to understand where AI and Chat GPT currently stand regarding their potential and maturity.

Martyn: I get it. Can you give me an example of how marketing strategy and research use AI and Chat GPT?

Chat GPT: Sure. One interesting example is how Bud Light used AI and chatbots to connect with fans during the Super Bowl. By analyzing social media conversations related to the game, Bud Light’s chatbot identified patterns and trends among Bud Light drinkers and provided personalized recommendations and offers to fans.

Martyn: That’s pretty cool. Incidentally, who should Bud Light market to?

Bud Light may want to focus its marketing efforts on a specific target audience or persona that aligns with its brand values and messaging. This could be determined by analyzing market research and consumer behavior data to identify the most profitable or influential demographic groups.

For example, Bud Light may focus its marketing efforts on young adults (ages 21-34) who enjoy socializing and having fun with friends and who value affordability and convenience. This group may be more likely to purchase beer for parties, social events, or casual get-togethers.

Martyn: Timely. OK. But what about the limitations of data being incomplete or biased? Can you give me an example of how AI and Chat GPT have encountered this issue?

Chat GPT: Sure. One example is how facial recognition software is biased against people of color due to incomplete and biased data sets.

There are also potential negative consequences or limitations of oversimplifying complex human behavior and decision-making and the potential for AI to replace human creativity and intuition.

Martyn: Whoa! What do you mean? Replacing human creativity and intuition?

Chat GPT: AI replacing human creativity and intuition could be bad because creativity and intuition are unique to humans and are often the source of innovation, originality, and out-of-the-box thinking. They allow humans to make connections and decisions not based solely on data and algorithms. If AI replaced these human qualities, there could be a loss of diversity and variability in solutions, leading to a more homogenized and limited set of options. Additionally, creativity and intuition are often key drivers of human satisfaction and fulfillment, and losing those elements could hurt human well-being.

Martyn: I don’t think it ‘could’ be bad; I think it ‘would’ be bad. Or, more likely, it ‘will’ be bad.

Chat GPT: In conclusion, while AI and Chat GPT can provide valuable insights and help identify patterns in marketing data, it is essential to remember that they are not infallible and can be subject to bias or incomplete data. Ultimately, finding a balance between AI and the human element in marketing strategy and research is key to achieving the best possible outcomes.

Martyn: There’s tension between balance and homogenization. I think that’s enough for a good brief…

For those interested in learning more about AI and Chat GPT in marketing strategy and research, here are some additional resources:

• Gartner Hype Cycle for Emerging Technologies: https://www.gartner.com/en/research/methodologies/gartner-hype-cycle
• “How Bud Light Used AI and Chatbots to Connect with Fans” (Adweek): https://www.adweek.com/performance-marketing/how-bud-light-used-ai-and-chatbots-to-connect-with-fans/
• “AI and Machine Learning Are Not Magic Bullets for Advertisers” (Harvard Business Review): https://hbr.org/2019/07/ai-and-machine-learning-are-not-magic-bullets-for-advertisers

Disclaimer: The conversation between Martyn and Chat GPT is a work of fiction. Any opinions or views expressed in this article are those of the author and not necessarily those of any companies or organizations mentioned.