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Buy-it-now or Take-a-chance: A New Pricing Mechanism for Online Advertising

Author

Listed:
  • L. Elisa Celis

    (Department of Computer Science, University of Washington)

  • Gregory Lewis

    (Department of Economics, Harvard University)

  • Markus Mobius

    (Microsoft Research New England)

  • Hamid Nazerzadeh

    (Marshall School of Business, University of Southern California)

Abstract

Increasingly sophisticated tracking technology offers publishers the ability to offer targeted advertisements to advertisers. Such targeting enhances advertising efficiency by improving the match quality between advertisers and users, but also thins the market of interested advertisers. Using bidding data from Microsoft's Ad Exchange (AdECN) platform, we show that there is often a substantial gap between the highest and second highest willingness to pay. This motivates our new BIN-TAC mechanism, which is effective in extracting revenue when such a gap exists. Bidders can ``buy-it-now'', or alternatively ``take-a-chance'' in an auction, where the top d > 1 bidders are equally likely to win. The randomized take-a-chance allocation incentivizes high valuation bidders to buy-it-now. We show that for a large class of distributions, this mechanism achieves similar allocations and revenues as Myerson's optimal mechanism, and outperforms the second-price auction with reserve. For the AdECN data, we use structural methods to estimate counterfactual revenues, and find that our BIN-TAC mechanism improves revenue by 11% relative to an optimal second-price auction.

Suggested Citation

  • L. Elisa Celis & Gregory Lewis & Markus Mobius & Hamid Nazerzadeh, 2011. "Buy-it-now or Take-a-chance: A New Pricing Mechanism for Online Advertising," Working Papers 11-21, NET Institute, revised Nov 2011.
  • Handle: RePEc:net:wpaper:1121
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    References listed on IDEAS

    as
    1. Dirk Bergemann & Alessandro Bonatti, 2010. "Targeting in Advertising Markets: Implications for Offline vs. Online Media," Cowles Foundation Discussion Papers 1758, Cowles Foundation for Research in Economics, Yale University.
    2. Michael Ostrovsky & Michael Schwarz, 2023. "Reserve Prices in Internet Advertising Auctions: A Field Experiment," Journal of Political Economy, University of Chicago Press, vol. 131(12), pages 3352-3376.
    3. Monteiro, Paulo Klinger & Svaiter, Benar Fux, 2010. "Optimal auction with a general distribution: Virtual valuation without densities," Journal of Mathematical Economics, Elsevier, vol. 46(1), pages 21-31, January.
    4. Shuchi Chawla & Jason Hartline & David Malec & Balasubramanian Sivan, 2010. "Sequential Posted Pricing and Multi-parameter Mechanism Design," Discussion Papers 1486, Northwestern University, Center for Mathematical Studies in Economics and Management Science.
    5. Pascal Courty & Li Hao, 2000. "Sequential Screening," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 67(4), pages 697-717.
    6. Jean-Charles Rochet & Philippe Chone, 1998. "Ironing, Sweeping, and Multidimensional Screening," Econometrica, Econometric Society, vol. 66(4), pages 783-826, July.
    7. Jonathan Levin & Paul Milgrom, 2010. "Online Advertising: Heterogeneity and Conflation in Market Design," American Economic Review, American Economic Association, vol. 100(2), pages 603-607, May.
    8. Roger B. Myerson, 1981. "Optimal Auction Design," Mathematics of Operations Research, INFORMS, vol. 6(1), pages 58-73, February.
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    More about this item

    Keywords

    Advertising; Auctions; Mechanism Design;
    All these keywords.

    JEL classification:

    • D44 - Microeconomics - - Market Structure, Pricing, and Design - - - Auctions
    • L86 - Industrial Organization - - Industry Studies: Services - - - Information and Internet Services; Computer Software

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