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Frontiers: Generative AI and Personalized Video Advertisements

Author

Listed:
  • 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)

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.

Suggested Citation

  • Anuj Kapoor & Madhav Kumar, 2025. "Frontiers: Generative AI and Personalized Video Advertisements," Marketing Science, INFORMS, vol. 44(4), pages 733-747, July.
    • Handle: RePEc:inm:ormksc:v:44:y:2025:i:4:p:733-747
    DOI: 10.1287/mksc.2023.0494
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    References listed on IDEAS

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    Cited by:

    1. Lu Fang & Zhe Yuan & Kaifu Zhang & Dante Donati & Miklos Sarvary, 2025. "Generative AI and Sales Productivity: Field Experiments in Online Retail," Papers 2510.12049, arXiv.org, revised Jun 2026.
    2. repec:ces:ceswps:_12201 is not listed on IDEAS
    3. Moritz Joerling, 2026. "Integrating GenAI interactions in marketing studies: A methodological guide," Post-Print hal-05489669, HAL.

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