Abstract
In the standard model of sponsored search auctions, an ad is ranked according to the product of its bid and its estimated click-through rate (known as the quality score), where the estimates are taken as exact. This paper re-examines the form of the efficient ranking rule when uncertainty in click-through rates is taken into account. We provide a sufficient condition under which applying an exponent—strictly less than one—to the quality score improves expected efficiency. The condition holds for a large class of distributions known as natural exponential families, and for the lognormal distribution. An empirical analysis of Yahoo’s sponsored search logs reveals that exponent settings substantially smaller than one can be efficient for both high and low volume keywords, implying substantial deviations from the traditional ranking rule.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Aggarwal, G., Goel, A., Motwani, R.: Truthful auctions for pricing search keywords. In: Proceedings of the 7th ACM Conference on Electronic Commerce, pp. 1–7 (2006)
Athey, S., Nekipelov, D.: A structural model of sponsored search advertising auctions. Tech. rep., Microsoft Research (May 2010)
Edelman, B., Ostrovsky, M., Schwarz, M.: Internet advertising and the Generalized Second Price auction: Selling billions of dollars worth of keywords. American Economic Review 97(1) (March 2007)
Efron, B., Morris, C.: Data analysis using Stein’s estimator and its generalizations. Journal of the American Statistical Association 70(350), 311–319 (1975)
Fain, D.C., Pedersen, J.O.: Sponsored search: A brief history. In: Second Workshop on Sponsored Search (2006)
Gelman, A., Carlin, J.B., Stern, H.S., Rubin, D.B.: Bayesian Data Analysis. Chapman and Hall/CRC (2003)
Gelman, A., Pardoe, I.: Bayesian measures of explained variance and pooling in multilevel (hierarchical) models. Technometrics 48(2), 241–251 (2006)
Lahaie, S.: An analysis of alternative slot auction designs for sponsored search. In: Proceedings of the 7th ACM Conference on Electronic Commerce, pp. 218–227 (2006)
Lahaie, S., Pennock, D.M.: Revenue analysis of a family of ranking rules for keyword auctions. In: Proceedings of the 8th ACM Conference on Electronic Commerce, pp. 50–56 (2007)
Lahaie, S., Pennock, D.M., Saberi, A., Vohra, R.V.: Sponsored search auctions. In: Nisan, N., Roughgarden, T., Taros, É., Vazirani, V.V. (eds.) Algorithmic Game Theory, pp. 699–716. Cambridge University Press (2007)
Louis, T.A.: Estimating a population of parameter values using Bayes and empirical Bayes methods. Journal of the American Statistical Association 79(386), 393–398 (1984)
Morris, C.N.: Natural exponential families with quadratic variance functions. The Annals of Statistics 10(1), 65–80 (1982)
Plummer, M.: JAGS: A program for analysis of Bayesian graphical models using Gibbs sampling, www-ice.iarc.fr/~martyn/software/jags/
Varian, H.R.: Position auctions. International Journal of Industrial Organization 25, 1163–1178 (2007)
Wainwright, M.J., Jordan, M.I.: Graphical Models, Exponential Families, and Variational Inference. Now Publishers Inc. (2008)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2011 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Lahaie, S., McAfee, R.P. (2011). Efficient Ranking in Sponsored Search. In: Chen, N., Elkind, E., Koutsoupias, E. (eds) Internet and Network Economics. WINE 2011. Lecture Notes in Computer Science, vol 7090. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-25510-6_22
Download citation
DOI: https://doi.org/10.1007/978-3-642-25510-6_22
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-25509-0
Online ISBN: 978-3-642-25510-6
eBook Packages: Computer ScienceComputer Science (R0)