Introducing the AI Market Researcher

Post #4 of the AI for Market and UX Research Series

The AI Market Researcher: A New Career Path?

Post #4 of the AI for Market and UX Research Series

Hey Friends! Welcome to the fourth and final post in my series about AI for market and UX researchers, where I’m exploring various ways we can incorporate AI into our work. As I mentioned in my first few articles, I’m experimenting with a different AI writing tool for each post, and for this piece I’ve teamed up with the OG, ChatGPT.

A quick bit of shameless self-promotion before we dive in: A few months back I launched an online course providing an introduction to AI for market research that’s been receiving some great feedback! If the topic piques your interest, please register using this link.

The Evolving Roles in Market Research

For years, the core tenets of market research roles have remained relatively unchanged. To greatly oversimplify things: Quantitative researchers diligently analyze data, often collected through surveys, ensuring precision and accuracy in every detail. At the same time, qualitative researchers go beyond the numbers and engaging directly with those we’re studying through focus groups, in-depth interviews (IDIs), etc. Furthermore, there are a plethora of specialists ranging from research ops, data visualization experts, fieldwork coordinators, and more.

But as AI continues its march into virtually every industry, there’s an emerging role that we might soon add to our roster: The AI Market Researcher.

The AI Market Researcher

Imagine a role that combines the need for proficiency in market research with an in-depth understanding of the intricacies of artificial intelligence. It almost sounds like two distinct jobs, doesn’t it?

An AI Market Researcher wouldn’t merely be an AI specialist parachuted into the world of market research. Instead, they would need to possess an intrinsic understanding of market research techniques, trends, and challenges. They’d also need to be adept at using, tweaking, and even developing AI tools tailored to specific research needs. They would understand the underlying algorithms, the biases that might creep in, and how to fine-tune models for optimal results. Being an AI Market Researcher would mean being an expert in two worlds, and being the bridge that brings them together. Building relationships and fostering collaboration would be absolutely vital to ensure integration and minimize potential issues.

If this role does indeed come to fruition, what would it mean for our market research teams?

Implications for Market Research Teams

Incorporating an AI Market Researcher would signify more than just adding a new member to the team; it would mean navigating the confluence of traditional methods and the transformative power of AI, setting the stage for a more advanced, agile, and insightful market research paradigm.

Adding such a role would impact teams in several dimensions:

• Skill Augmentation: Traditional market research methodologies would gain an additional layer of depth with AI’s predictive analytics, pattern recognition, and data processing capabilities. This would potentially allow for deeper insights derived from larger datasets in shorter times. It would also create the need for continous learning and growth to stay up-to-date with the ever-evolving technology. Training sessions, workshops, and courses would become essential to stay on top of the latest tools and best practices.
• Redefining Roles & Team Dynamics: Traditional roles might need to be redefined. For instance, quantitative researchers would work closely with the AI researcher to leverage machine learning models for predictive analysis. Similarly, qualitative researchers would use AI tools for sentiment analysis or natural language processing to glean insights from vast text datasets. No matter how the roles evolve, there would certainly be a shift in team dynamics to integrate such a teammate with the new skillset.
• Cultural Shift: Beyond the technical and operational aspects, there would be a cultural shift within the team. As with any sizemic change, there could be resistance or skepticism from traditional market researchers. Embracing an AI-driven approach requires a mindset that values innovation, adaptability, and forward-thinking. Therefore, strengthening a culture that fosters these values would be imperative.
• Budget Adjustments: The team would need to become familiar with the plethora of new AI tools, platforms, and softwares. These tools and platforms, especially the more advanced ones, can be an big investment in both time and money. Budgets would likely need to be revisted, with portions of it being siphoned into these new tools, training, and additional staff.
• Ethical Considerations: AI brings up new ethical considerations, especially concerning data privacy, model transparency, and bias. The team (and the company overall) would need to have numerous ongoing conversations around these aspects and determine what they are, and aren’t, willing to do. Take a look at my first article to better understand some of the pros and cons of embracing AI for research.

So, what does all of this mean?

In reflection, the landscape of market research is poised for a significant evolution. It’s easy to imagine a world, not too far in the distance, where we’re seamlessly blending traditional methodologies with the innovative prowess of artificial intelligence. This article forecasts the emergence of a potential new job function, the AI Market Researcher, and highlights its role in blending the strengths of both AI and human ingenuity. As we continue further into this decade, it’s conceivable that this position will not only materialize but will become integral to market research teams. The trajectory of market research is unmistakably shifting, signaling fresh avenues for industry advancement and profound insight generation.

Have you seen any new roles like this? If so, I’d love to hear about it!