University of Pennsylvania ScholarlyCommons Operations, Information and Decisions Papers Wharton Faculty Research 10-2009 An Empirical Analysis of Search Engine Advertising: Sponsored Search in Electronic Markets Anindya Ghose University of Pennsylvania Sha Yang Follow this and additional works at: https://repository.upenn.edu/oid_papers Part of the E-Commerce Commons, and the Management Sciences and Quantitative Methods Commons Recommended Citation Ghose, A., & Yang, S. (2009). An Empirical Analysis of Search Engine Advertising: Sponsored Search in Electronic Markets. Management Science, 55 (10), 1605-1622. http://dx.doi.org/10.1287/ mnsc.1090.1054 This paper is posted at ScholarlyCommons. https://repository.upenn.edu/oid_papers/159 For more information, please contact
[email protected]. An Empirical Analysis of Search Engine Advertising: Sponsored Search in Electronic Markets Abstract The phenomenon of sponsored search advertising—where advertisers pay a fee to Internet search engines to be displayed alongside organic (nonsponsored) Web search results—is gaining ground as the largest source of revenues for search engines. Using a unique six-month panel data set of several hundred keywords collected from a large nationwide retailer that advertises on Google, we empirically model the relationship between different sponsored search metrics such as click-through rates, conversion rates, cost per click, and ranking of advertisements. Our paper proposes a novel framework to better understand the factors that drive differences in these metrics. We use a hierarchical Bayesian modeling framework and estimate the model using Markov Chain Monte Carlo methods. Using a simultaneous equations model, we quantify the relationship between various keyword characteristics, position of the advertisement, and the landing page quality score on consumer search and purchase behavior as well as on advertiser's cost per click and the search engine's ranking decision.