Revenue analysis of a family of ranking rules for keyword auctions

Sébastien Lahaie, David M. Pennock

Research output: Chapter in Book/Report/Conference proceedingConference contribution

85 Scopus citations

Abstract

Keyword auctions lie at the core of the business models of today's leading search engines. Advertisers bid for placement alongside search results, and are charged for clicks on their ads. Advertisers are typically ranked according to a score that takes into account their bids and potential click-through rates. We consider a family of ranking rules that contains those typically used to model Yahoo! and Google's auction designs as special cases. We find that in general neither of these is necessarily revenue-optimal in equilibrium, and that the choice of ranking rule can be guided by considering the correlation between bidders' values and click-through rates. We propose a simple approach to determine a revenue-optimal ranking rule within our family, taking into account effects on advertiser satisfaction and user experience. We illustrate the approach using Monte-Carlo simulations based on distributions fitted to Yahoo! bid and click-through rate data for a high-volume keyword.

Original languageEnglish (US)
Title of host publicationEC'07 - Proceedings of the Eighth Annual Conference on Electronic Commerce
Pages50-56
Number of pages7
DOIs
StatePublished - 2007
Externally publishedYes
Event8th ACM Conference on Electronic Commerce, EC'07 - San Diego, CA, United States
Duration: Jun 11 2007Jun 15 2007

Publication series

NameEC'07 - Proceedings of the Eighth Annual Conference on Electronic Commerce

Other

Other8th ACM Conference on Electronic Commerce, EC'07
CountryUnited States
CitySan Diego, CA
Period6/11/076/15/07

All Science Journal Classification (ASJC) codes

  • Management of Technology and Innovation
  • Marketing
  • Computer Networks and Communications
  • Computer Science Applications

Keywords

  • Keyword auctions
  • Search engines
  • Sponsored search

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