The most useful result of an advertising campaign may never appear in a click report. Someone can come away trusting a company more without visiting its website. Understanding what shaped that response could help marketers decide what to say next, before they commit millions to another campaign.

Sara Fagen, CEO and co-founder of Tunnl, wants to make that process conversational. Her Arlington, Virginia-based audience intelligence company turns survey responses into predictive models that help brands reach relevant audiences and track shifts in attitudes. She now envisions marketers talking to an AI version of the people they hope to persuade, drawing on years of human research to explore how a message might land.

“Synthetic research has to remain grounded in a human-in-the-loop conversation, with people’s responses providing the foundation for that work. We conduct several hundred thousand interviews every year, combining the research that powers our platform for subscribers with the custom work our brand clients ask us to undertake,” Fagen tells me in an exclusive interview. “Every one of those questions produces a signal that we use to build a corresponding model. Our technology automates that process, allowing us to translate survey responses into models quickly, with machine learning powering much of the work.”

A four-time founder, Fagen co-founded Tunnl in 2021 after earlier ventures that included Resonate and Deep Root Analytics. Her career began in politics and polling, where a campaign deadline made precision essential. That experience informs her approach to understanding what might persuade someone, beyond what demographic characteristics reveal.

Connecting Consumer Insights With AI Modeling

Fagen says Tunnl’s platform holds more than 25,000 variables on each U.S. person. Research Studio connects survey work to audience building, while the company’s media capabilities help clients put those insights into advertising. Moreover, the platform’s television tools help advertisers plan spending around their target audiences’ viewing habits across traditional and connected TV, building on Fagen’s earlier work in TV ad targeting at Deep Root Analytics.

Tunnl’s historical research also gives its team a way to study how opinions evolve. Fagen describes more than a decade of data and an ongoing effort to determine how much fresh research its models need.

“Some people’s attitudes change regularly, while others remain relatively consistent. Our research gives us a good sense of those patterns, but we still need to capture how opinions evolve over time,” she says. “That is part of what we are exploring now, understanding how much fresh information we need to bring into the existing data set so that our models continue to reflect what people think as their views change.”

She expects synthetic research to develop alongside established methods, giving brands room to explore an idea before undertaking a larger study. Over time, she believes that relationship could change how companies commission research itself.

“We could eventually reach a point where the only research taking place is the work needed to feed synthetic models. That is a possibility. For now, though, most brands want their research rooted in methods they already know and trust,” Fagen says. “Perhaps you want to have a conversation that helps you work through how an audience might respond to a particular message. You could then explore what to say next, using that exchange to think through a follow-up message. Those conversational applications of synthetic research are very valuable.”