An empirical analysis of return on investment maximization in sponsored search auctions

Authors:
Jason Auerbach;Joel Galenson;Mukund Sundararajan
Affiliations:
Stanford University;Stanford University;Stanford University
Venue:
Proceedings of the 2nd International Workshop on Data Mining and Audience Intelligence for Advertising
Year:
2008

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Abstract

We empirically investigate whether advertisers are maximizing their return on investment (ROI) across multiple keywords in sponsored search auctions. Because testing for ROI maximization relies on knowledge of advertisers' private true values per click, we instead use necessary (although not sufficient) conditions for ROI maximizing behavior that rely only on advertisers' bids. We classify advertisers based on the extent to which they satisfy the test conditions. Our results indicate that a large fraction of advertisers in the Yahoo Webscope first price data set may be following ROI-based strategies.