Frontiers: Generative AI and Personalized Video Advertisements

Anuj Kapoor () and Madhav Kumar ()
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Anuj Kapoor: Robert J. Trulaske, Sr. College of Business, University of Missouri, Columbia, Missouri 65211
Madhav Kumar: MIT Sloan School of Management, Cambridge, Massachusetts 02142

Marketing Science, 2025, vol. 44, issue 4, 733-747

Abstract: We study the effectiveness of personalized video advertisements created using generative artificial intelligence (GenAI). We run a mobile ad targeting field experiment on WhatsApp in partnership with a leading direct-to-consumer e-commerce brand that sells eco-friendly sustainable products. We randomize users into receiving ads from one of three targeting conditions: (1) GenAI-based personalized video ads, (2) personalized image ads, and (3) generic nonpersonalized video ads. The first group is our main treatment, and the latter two serve as baselines. In the personalized treatment conditions, ad content is tailored to individual purchase histories, whereas in the generic treatment condition, a uniform brand message is delivered to all users. Our results show that GenAI-based personalized video ads increase engagement by six to nine percentage points over the baselines. These gains are robust across consumer demographics such as gender and location. We use back-of-the-envelope calculations to highlight substantial cost savings and productivity benefits of GenAI-based personalized ad campaigns. We discuss the implications of our findings for businesses and policymakers while noting the potential variation in effectiveness and generalizability of GenAI applications across marketing contexts.

Keywords: generative AI; video advertising; field experiments; causal inference (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:inm:ormksc:v:44:y:2025:i:4:p:733-747

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