Ad auctions with data

Hu Fu, Patrick Jordan, Mohammad Mahdian, Uri Nadav, Inbal Talgam-Cohen, Sergei Vassilvitskii

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

The holy grail of online advertising is to target users with ads matched to their needs with such precision that the users respond to the ads, thereby increasing both advertisers' and users' value. The current approach to this challenge utilizes information about the users: their gender, their location, the websites they have visited before, and so on. Incorporating this data in ad auctions poses an economic challenge: can this be done in a way that the auctioneer's revenue does not decrease (at least on average)? This is the problem we study in this paper. Our main result is that in Myerson's optimal mechanism, additional data leads to additional revenue. However in simpler auctions, namely the second price auction with reserve prices, there are instances in which additional data decreases the revenue, albeit by only a small constant factor.

Original languageEnglish
Title of host publication2012 IEEE Conference on Computer Communications Workshops, INFOCOM WKSHPS 2012
Pages184-189
Number of pages6
DOIs
StatePublished - 2012
Externally publishedYes
Event2012 IEEE Conference on Computer Communications Workshops, INFOCOM WKSHPS 2012 - Orlando, FL, United States
Duration: 25 Mar 201230 Mar 2012

Publication series

NameProceedings - IEEE INFOCOM

Conference

Conference2012 IEEE Conference on Computer Communications Workshops, INFOCOM WKSHPS 2012
Country/TerritoryUnited States
CityOrlando, FL
Period25/03/1230/03/12

All Science Journal Classification (ASJC) codes

  • General Computer Science
  • Electrical and Electronic Engineering

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