Repeated Auctions with Budgets in Ad Exchanges: Approximations and Design

• Published in: Management science Vol. 61; no. 4; pp. 864 - 884
• Main Authors: Balseiro, Santiago R., Besbes, Omar, Weintraub, Gabriel Y.
• Format: Journal Article
• Language: English
• Published: Linthicum INFORMS 01-04-2015; Institute for Operations Research and the Management Sciences
• Subjects: ad exchange; Advertisers; Analysis; auction design; Auctions; Bidding; Budget; budget constraints; Budgets; display advertising; dynamic games; fluid approximation; Internet; Internet marketing; Internet/Web advertising; Markets; mean field; Online advertising; Prescription drugs; revenue management; United States
• ISSN: 0025-1909; 1526-5501
• DOI: 10.1287/mnsc.2014.2022

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 prespecified 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. The presence of budgets introduces dynamic interactions among advertisers that need to be taken into account when attempting to characterize the bidding landscape or the impact of changes in the auction design. To this end, we introduce the notion of a fluid mean-field equilibrium (FMFE) that is behaviorally appealing and computationally tractable, and in some important cases, it yields a closed-form characterization. We establish that an FMFE approximates well the rational behavior of advertisers in these markets. We then show how this framework may be used to provide sharp prescriptions for key auction design decisions that publishers face in these markets. In particular, we show that ignoring budgets, a common practice in this literature, can result in significant profit losses for the publisher when setting the reserve price.
This paper was accepted by Dimitris Bertsimas, optimization
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