AI in market research

AI in Market Research: Balancing Machine and Human Collaboration

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Researchers might be going back and forth from excitement to apprehension when it comes to AI in market research. The reality is that artificial intelligence certainly is claiming its role in our industry.

On my podcast, “Research Revolutionaries,” I had the pleasure of talking with two industry leaders – Babita Earle, Zappi’s Managing Director International, and Caroline Frankum, Global CEO of Kantar’s Profiles Division – about this very topic.

Our discussions shed light on the current state of AI in market research, the opportunities and challenges it presents, and how to maximize its power to generate game-changing insights.

In this article, I’ll share some of the key takeaways from these conversations and explore what the rise of AI could mean for the future of our industry.

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The buzz around AI: A double-edged sword

One thing that became abundantly clear is that AI is the talk of the town in market research circles. AI would have been the runaway winner if there had been a “word bingo” game at industry conferences in 2023 and 2024.

This buzz is understandable, given the tantalizing potential of AI impact on how we conduct research and generate insights. AI-powered tools can automate tedious tasks, crunch massive datasets quickly, and uncover patterns that human analysts might overlook.

In theory, this could liberate researchers to focus on higher-level strategic work and enable faster, more responsive research processes.

However, the AI hype is tempered by a fair amount of uncertainty and unease about its implications for the future of market research jobs and practices, including:

  • Job security: Will AI render human researchers obsolete?
  • Data bias: Could biased AI models lead to skewed or misleading insights?
  • Insight quality: Can we trust the outputs of AI?
  • Research rigor: Will overreliance on AI keep research standards in mind?

We don’t know exactly how AI will reshape our industry in the years ahead. But it’s here to stay.

But, change and disruption are par for the course in market research.

“I think we’re experienced as an industry,” Babita noted. “And if you’re an innovator, you know, you will be comfortable with the discomfort it’s potentially bringing.”

In other words, while the AI revolution may be daunting, it’s also an exhilarating opportunity for researchers who are willing to embrace change and push the boundaries of what’s possible.

AI applications: From predictive insights to fraud detection

So, what does embracing AI look like in practice?

Predictive insights

One key area of focus is using AI to generate predictive insights from the vast troves of data that brands have accumulated, which can lead to answers to these questions:

“We’ve got quite a few organizations that have amassed a great deal of data on a platform that is standardized, and scale, and it’s good data,” Babita said. “So it gives us that ability to sort of overlay AI to say, Okay, can we generate new ideas? What does this do from a storytelling perspective? What does this predict for certain categories and certain brands?”

This predictive use case for AI is incredibly powerful. Imagine being able to forecast consumer trends, anticipate market disruptions, or test new concepts before they even exist – all based on the patterns and insights hidden in your historical research data.

Combating fraud

Another critical application of AI in market research is combating fraud and ensuring data quality. With the rise of sophisticated fraud attacks and “bad actors” infiltrating panels,  AI-powered tools can detect and eliminate fraudulent responses at lightning speed.

“Fraud is an interesting thing. It’s never going to go away,” said Caroline. “It’s about how we stay one step ahead of the fraudsters to make it so challenging for them to get into our surveys that they just don’t bother; they go somewhere else.”

By combining cutting-edge AI with decades of expertise in panel management, leading research firms are ensuring clients get truthful, reliable data to inform their decisions – even as the threats become more sophisticated.

Of course, getting to this level of AI sophistication requires a strong foundation of clean, consistent, and well-structured data.

The future of research careers

Inevitably, the growing prominence of AI in market research for some raises existential questions about the future of research careers. Will intelligent machines ultimately displace human insight professionals?

The consensus from my conversations is that researchers aren’t going away anytime soon. But the roles are likely to evolve significantly.

Rather than being replaced by AI, we’ll need to learn to work alongside these powerful new tools – to become “prompt engineers” or use AI as “co-pilots.”

We’ll need to master asking AI the right questions and interpreting its outputs through a human lens. This will require researchers to upskill in areas like data science, analytics, and storytelling. And they need to double down on the fundamental human skills of critical thinking, creativity, and empathy.

“We fundamentally believe our sector is a people business,” said Caroline. “After all, we source information from people, we sell information to people. We are about reflecting the truly diverse world that we have the accountability and the privilege to serve.”

In other words, AI is a means to an end. It’s a powerful tool for augmenting and scaling human expertise, but not a substitute for it. The real value will continue to come from researchers’ ability to understand consumers’ needs, motivations, and experiences and to translate that understanding into actionable business recommendations.

With the great power of AI comes great responsibility. We’ll need to be vigilant about its potential risks and downsides.

One key area of concern is bias. Skewed data fed into AI will also deliver skewed results. This could lead to flawed decision-making and even discriminatory outcomes if left unchecked. As an industry, we’ll need robust processes to audit AI models for bias, ensure diverse and representative training data, and maintain human oversight of machine-generated insights.

We’ll also need to prioritize transparency and interpretability in AI research. Researchers and brands will rightly demand to know the “why” behind the “what.” That means developing AI systems that are explainable, accountable, and open to human interrogation.

Finally, we’ll need to grapple with the broader ethical implications of using AI in a field as sensitive as consumer research. How do we protect people’s privacy and data rights? How do we ensure that AI is being used responsibly and for the benefit of consumers, not just the bottom line?

These are complex challenges without easy answers. But they’re ones that we as an industry will need to confront head-on as we navigate the brave new world of AI-powered research.

Looking ahead

What does the future hold for AI in market research? It’s going to be an exhilarating and transformative time for our industry.

We’re already seeing AI being applied in many ways across the research process:

  • Automated data collection
  • Analysis
  • Predictive modeling and insight generation. And as the technology continues to advance at breakneck speed, the possibilities are only going to expand.

At the same time, it’s clear that the successful integration of AI will require a delicate balance – between machine efficiency and human expertise, between speed and quality, between innovation and responsibility.

“Growth never comes from comfort zones,” said Caroline.  “We as researchers will need to lean into the discomfort, ask tough questions, and experiment fearlessly to realize the full potential of AI.”

But if we can do that – if we can be the innovators and the revolutionaries that this moment demands – then I have no doubt that our industry’s brightest days are still ahead of us.