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How Do Digital Advertising Auctions Impact Product Prices?

Author

Listed:
  • Dirk Bergemann

    (Yale University)

  • Alessandro Bonatti

    (MIT)

  • Nicholas Wu

    (Yale University)

Abstract

We ask how the advertising mechanisms of digital platforms impact product prices. We present a model that integrates three fundamental features of digital advertising markets: (i) advertisers can reach customers on and off-platform, (ii) additional data enhances the value of matching advertisers and consumers, and (iii) bidding follows auction-like mechanisms. We compare data-augmented auctions, which leverage the platformÕs data advantage to improve match quality, with managed campaign mechanisms, where advertisersÕ budgets are transformed into personalized matches and prices through auto-bidding algorithms. In data-augmented second-price auctions, advertisers increase off- platform product prices to boost their competitiveness on-platform. This leads to socially efficient allocations on-platform, but inefficient allocations off-platform due to high product prices. The platform-optimal mechanism is a sophisticated managed campaign that conditions on-platform prices for sponsored products on off-platform prices set by all advertisers. Relative to auctions, the optimal managed campaign raises off-platform product prices and further reduces consumer surplus.

Suggested Citation

  • Dirk Bergemann & Alessandro Bonatti & Nicholas Wu, 2023. "How Do Digital Advertising Auctions Impact Product Prices?," Cowles Foundation Discussion Papers 2367, Cowles Foundation for Research in Economics, Yale University.
    • Handle: RePEc:cwl:cwldpp:2367
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    References listed on IDEAS

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    1. Heski Bar-Isaac & Sandro Shelegia, 2023. "Search, Showrooming, and Retailer Variety," Marketing Science, INFORMS, vol. 42(2), pages 251-270, March.
    2. Chengsi Wang & Julian Wright, 2020. "Search platforms: showrooming and price parity clauses," RAND Journal of Economics, RAND Corporation, vol. 51(1), pages 32-58, March.
    3. Fuchs, William & Skrzypacz, Andrzej, 2015. "Government interventions in a dynamic market with adverse selection," Journal of Economic Theory, Elsevier, vol. 158(PA), pages 371-406.
    4. Francesco Decarolis & Maris Goldmanis & Antonio Penta, 2020. "Marketing Agencies and Collusive Bidding in Online Ad Auctions," Management Science, INFORMS, vol. 66(10), pages 4433-4454, October.
    5. Dirk Bergemann & Alessandro Bonatti, 2024. "Data, Competition, and Digital Platforms," American Economic Review, American Economic Association, vol. 114(8), pages 2553-2595, August.
    6. Thomas Philippon & Vasiliki Skreta, 2012. "Optimal Interventions in Markets with Adverse Selection," American Economic Review, American Economic Association, vol. 102(1), pages 1-28, February.
    7. Jean Tirole, 2012. "Overcoming Adverse Selection: How Public Intervention Can Restore Market Functioning," American Economic Review, American Economic Association, vol. 102(1), pages 29-59, February.
    8. Yash Kanoria & Hamid Nazerzadeh, 2020. "Dynamic Reserve Prices for Repeated Auctions: Learning from Bids," Papers 2002.07331, arXiv.org.
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    Cited by:

    1. Dirk Bergemann & Alessandro Bonatti, 2024. "Data, Competition, and Digital Platforms," American Economic Review, American Economic Association, vol. 114(8), pages 2553-2595, August.
    2. Guy Aridor & Rafael Jiménez-Durán & Ro'ee Levy & Lena Song, 2024. "The Economics of Social Media," CESifo Working Paper Series 10934, CESifo.

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