Abstract

http://ssrn.com/abstract=1490169
 


 



Aggregation Bias in Sponsored Search Data: The Curse and The Cure


Vibhanshu Abhishek


Carnegie Mellon University - H. John Heinz III School of Public Policy and Management

Kartik Hosanagar


University of Pennsylvania - Operations & Information Management Department

Peter Fader


University of Pennsylvania - Marketing Department

March 7, 2011

Forthcoming, Marketing Science

Abstract:     
There has been significant recent interest in studying consumer behavior in sponsored search advertising (SSA). Researchers have typically used daily data from search engines containing measures such as average bid, average ad position, total impressions, clicks and cost for each keyword in the advertiser's campaign. A variety of random utility models have been estimated using such data and the results have helped researchers explore the factors that drive consumer click and conversion propensities. However, virtually every analysis of this kind has ignored the intra-day variation in ad position. We show that estimating random utility models on aggregated (daily) data without accounting for this variation will lead to systematically biased estimates -- specifically, the impact of ad position on click-through rate (CTR) is attenuated and the predicted CTR is higher than the actual CTR. We demonstrate the existence of the bias analytically and show the effect of the bias on the equilibrium of the SSA auction. Using a large dataset from a major search engine, we measure the magnitude of bias and quantify the losses suffered by the search engine and an advertiser using aggregate data. The search engine revenue loss can be as high as 11% due to aggregation bias. We also present a few data summarization techniques that can be used by search engines to reduce or eliminate the bias.

Number of Pages in PDF File: 44

Keywords: e-commerce, sponsored search, online advertising, aggregation bias, econometrics, probabilistic modeling, consumer behavior, generalized second price auctions

JEL Classification: C13, M37

Accepted Paper Series





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Date posted: October 20, 2009 ; Last revised: October 15, 2014

Suggested Citation

Abhishek, Vibhanshu and Hosanagar, Kartik and Fader, Peter, Aggregation Bias in Sponsored Search Data: The Curse and The Cure (March 7, 2011). Forthcoming, Marketing Science. Available at SSRN: http://ssrn.com/abstract=1490169 or http://dx.doi.org/10.2139/ssrn.1490169

Contact Information

Vibhanshu Abhishek (Contact Author)
Carnegie Mellon University - H. John Heinz III School of Public Policy and Management ( email )
Pittsburgh, PA 15213-3890
United States
Kartik Hosanagar
University of Pennsylvania - Operations & Information Management Department ( email )
Philadelphia, PA 19104
United States

Peter Fader
University of Pennsylvania - Marketing Department ( email )
700 Jon M. Huntsman Hall
3730 Walnut Street
Philadelphia, PA 19104-6340
United States

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