How MarketCast Is Using AI to Modernize Research—Without Losing the Human Touch

In the latest in our Truth In Numbers series, Jon Watts, Managing Director of the Coalition for Innovative Media Measurement (CIMM), spoke with MarketCast Co-President Amy Fenton, about how AI is transforming the research industry, what it takes to move at the speed of modern marketing, and why the human element still matters in a world increasingly driven by data.

Jon Watts: What’s new at MarketCast?

Amy Fenton: We’re embracing AI in a big way—especially across ad effectiveness and market measurement. The goal is to help our clients keep up with the rapid pace of change by delivering predictive insights and enabling faster decision-making. We’re working hard to put insights in our clients’ hands in real time. That’s a big part of our transformation, which I’ve been deeply involved in.

JW: How is AI changing market research?

AF: It’s already making an impact. At Cannes, AI was a major theme—and not just in theory. For us, it's about using AI to increase speed and scale without losing the human touch. We’re applying it to concept and copy testing by training language models to predict ad performance before launch. We also use it in brand effect studies and product placement measurement. It allows us to deliver more granular insights faster, even same-day in some cases.

JW: Is AI integrated across all your operations?

AF: Yes, but it didn’t start that way. Initially, we thought about putting AI everywhere—but that approach didn’t scale. So we adopted a modular strategy, embedding AI in targeted parts of the research process where it could drive speed or generate insights we couldn’t access before. Over time, these modules have connected into a more holistic solution.

JW: What do you mean by more "granular" insights?

AF: One example is our In-Program Brand Placement (IBP) service. With AI, we can detect every product featured in a show or live event, like a PGA tournament with multiple sponsors. We then measure the effectiveness of each placement. It gives clients a more complete picture of touchpoints, brand exposure, and ultimately, ROI.

JW: Will AI transform media and marketing mix modeling?

AF: Absolutely. Traditional mix models look backward and take weeks or months to run. By then, decisions have already been made. With AI, we can deliver same-day insights and feed in more detailed, granular data. This lets marketing leaders make faster, smarter allocation decisions—potentially on the same day.

JW: There’s concern in the industry about bots and fraudulent responses. How are you addressing that?

AF: We use AI to detect fraudulent responses in real time. It’s built into our operations to flag and remove bad data before it hits our data lake. Clean data is critical—if the data is off, the insights will be too, and that can derail an entire campaign.

JW: Are clients ready to act on these faster, more agile insights?

AF: Some are, but not all. There are two stages of transformation: one is speeding up access to existing data. The second is more complex—integrating new data types and making smarter decisions. That requires major operational changes. I spoke with advertisers at Cannes who are planning two- to three-year transformations to build the infrastructure to support this.

JW: MarketCast is a member of CIMM. What kinds of industry collaboration would you like to see?

AF: First, we need shared best practices for using AI in research—especially around data quality. That should be table stakes. Second, we need a shared understanding of how far AI should go in the creative process. There’s pressure to use AI to reduce costs, but authenticity still matters. AI can’t replicate human connection, and that connection is what drives ad effectiveness.

JW: That’s an important distinction. Not all creative is the same.

AF: Exactly. There’s a place for AI in low-risk, low-cost ads. But for high-stakes, high-investment campaigns—where the risks are higher and the audience more targeted—the human touch is still essential.