NDLI: To match or not to match: economics of cookie matching in online advertising

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To match or not to match: economics of cookie matching in online advertising

Content Provider	ACM Digital Library
Author	McAfee, Preston Mahdian, Mohammad Ghosh, Arpita Vassilvitskii, Sergei
Abstract	Modern online advertising increasingly relies on the availability of user tracking technology called cookie-matching to increase efficiency in ad allocations. Web publishers today use this technology to share information about the websites a user has visited, making it possible to target advertisements to users based on their prior history. This begs the question: do publishers (who are competitors for advertising money) always have the incentive to share online information? Intuitive arguments as well as anecdotal evidence suggest that sometimes a premium publisher might suffer from information sharing through an effect called information leakage: by sharing user information with the advertiser, the advertiser will be able to target the same user elsewhere on cheaper publishers, leading to a dilution of the value of the supply on the premium publishers. The goal of this paper is to explore this aspect of online information sharing. We show that when advertisers are homogeneous (i.e., they value the users similarly, up to a constant multiple), in equilibrium, the publishers always agree about the benefits of cookie-matching (i.e., either they all benefit, or they all suffer from it). We also analyze a simple model that exhibits how information leakage can help one publisher and harm the other when the advertisers are not homogeneous.
Starting Page	741
Ending Page	753
Page Count	13
File Format	PDF
ISBN	9781450314152
DOI	10.1145/2229012.2229069
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2012-06-04
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Ad auctions Information in auctions Cookie-matching
Content Type	Text
Resource Type	Article

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