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Auctions for Online Display Advertising Exchanges: Approximations and Design

Author

Listed:
  • Santiago R. Balseiro

    (Graduate School of Business, Columbia University)

  • Omar Besbes

    (Graduate School of Business, Columbia University)

  • Gabriel Y. Weintraub

    (Graduate School of Business, Columbia University)

Abstract

Ad Exchanges are emerging Internet markets where advertisers may purchase display ad placements, in real-time and based on specific viewer information, directly from publishers via a simple auction mechanism. Advertisers join these markets with a pre-specified budget and participate in multiple second-price auctions over the length of a campaign. This paper studies the competitive landscape that arises in Ad Exchanges and the implications for publishers' decisions. Our first main contribution is to introduce the novel notion of a Fluid Mean Field Equilibrium (FMFE) that is behaviorally appealing, computationally tractable, and in some important cases yields a closed-form characterization. Moreover, we show that a FMFE approximates well the rational behavior of advertisers in large markets. Our second main contribution is to use this framework to provide sharp prescriptions for key auction design decisions that publishers face in these markets, such as the reserve price, the allocation of impressions to the exchange versus an alternative channel, and the disclosure of viewers' information. Notably, we show that proper adjustment of the reserve price is key in (1) making profitable for the publisher to try selling all impressions in the exchange before utilizing the alternative channel; and (2) compensating for the thinner markets created by greater disclosure of viewers' information.

Suggested Citation

  • Santiago R. Balseiro & Omar Besbes & Gabriel Y. Weintraub, 2012. "Auctions for Online Display Advertising Exchanges: Approximations and Design," Working Papers 12-11, NET Institute.
  • Handle: RePEc:net:wpaper:1211
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    References listed on IDEAS

    as
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    Cited by:

    1. L. Elisa Celis & Gregory Lewis & Markus Mobius & Hamid Nazerzadeh, 2014. "Buy-It-Now or Take-a-Chance: Price Discrimination Through Randomized Auctions," Management Science, INFORMS, vol. 60(12), pages 2927-2948, December.
    2. Henk Kox & Bas Straathof & Gijsbert Zwart, 2017. "Targeted advertising, platform competition, and privacy," Journal of Economics & Management Strategy, Wiley Blackwell, vol. 26(3), pages 557-570, September.
    3. Henk Kox & Bas Straathof & Gijsbert Zwart, 2017. "Targeted advertising, platform competition, and privacy," Journal of Economics & Management Strategy, Wiley Blackwell, vol. 26(3), pages 557-570, September.

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    More about this item

    Keywords

    auction design; revenue management; ad exchange; display advertising; internet; budget constraints; dynamic games; mean field; fl uid approximation;
    All these keywords.

    JEL classification:

    • C73 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Stochastic and Dynamic Games; Evolutionary Games
    • L86 - Industrial Organization - - Industry Studies: Services - - - Information and Internet Services; Computer Software

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