Yakov Bart
Patrick F. and Helen C. Walsh Research Professor, Marketing
Northeastern University
Yakov Bart is a professor of marketing at Northeastern University's D'Amore-McKim School of Business in Boston, Massachusetts, where he holds the Patrick F. and Helen C. Walsh Research Professorship. Trained in mathematics at Moscow State University and in marketing at UC Berkeley, he studies digital advertising and generative AI, from how ChatGPT changed the quality of online reviews to how Google's AI Mode reduces clicks to publishers.
ChatGPT and the Quality of Online Reviews
"A lot of people say ChatGPT improves the productivity of workers," Bart told Northeastern's Institute for Experiential AI. "We wanted to understand what exactly happens when people get access to ChatGPT, because there are different ways to look at productivity in terms of volume and in terms of quality."
With Samsun Knight of the University of Toronto, he compared restaurant reviews from San Francisco, California, on Yelp and camera reviews on Amazon from before and after ChatGPT's release, using a detection tool to flag AI-written text. Reviews written with generative AI drew 15.5% fewer "useful" votes on Yelp and 14.8% fewer "helpful" votes on Amazon. The drop came mainly from casual reviewers. Yelp's Elite reviewers and Amazon's Vine Voice members, who are judged on quality, showed much smaller declines. The paper is forthcoming in Quantitative Economics.
Brand Ads, AI Answers and Shopping Agents
Search advertising has been a steady thread. In an ICWSM 2024 paper with Christo Wilson and others, Bart's team used the search logs of a representative panel of US residents to estimate that ads on navigational and brand searches, where companies often bid on their own names to fend off competitors, account for 28% to 36% of Google's search revenue, with Bing earning an even larger share.
The same group later tested AI answers directly. Bart is a co-author, with Stephanie T. Wang, Jeffrey Gleason, Wilson and Danaé Metaxa, of a 2026 experiment with 1,100 people in which Google's AI Mode cut click-through to outside publishers by 18.8 percentage points. He also co-wrote OPeRA, a dataset accepted at ACL 2026 for testing how well language models can simulate how people shop online.
Virtual Influencers and AI Disclosures
Bart has studied how consumers react when AI shows up in the ad itself. "What's fascinating is that even when consumers are aware that an influencer is AI-generated, many still continue interacting with them," he told D'Amore-McKim in 2025. "AI enables immersive storytelling in ways we haven't experienced before. But the line between immersive and deceptive needs to be both visible and enforceable."
A 2026 paper in the Journal of Marketing Analytics, written with Koen Pauwels and colleagues, examined how consumers read "Made with AI" labels on ads depending on who the disclosure says the AI benefits.
From Moscow State to Northeastern
Bart earned a diploma in mathematics, summa cum laude, from Moscow State University in 1999. He went on to an SM in operations research at MIT in 2002, then an MS in business administration and, in 2009, a PhD in marketing from the University of California, Berkeley. He taught marketing at INSEAD from 2009 to 2015 and spent the 2012-13 academic year as a visiting assistant professor at Wharton.
He joined Northeastern in 2015 and became a full professor in 2024. He is core faculty at the Institute for Experiential AI and the NULab for Digital Humanities and Computational Social Science, and an international research fellow of the Future of Marketing Initiative at Oxford's Saïd Business School.
His research funding includes a Google-WPP Marketing Research Award on mobile advertising and a 2023 Amazon Research Award.