Predictive pricing (e.g., Google's "Smart Pricing" and Yahoo's "Quality Based Pricing") and revenue sharing are two important tools that online advertising networks can use in order to attract content publishers and advertisers. We develop a simple model of the pay-per-click advertising market to study the market effects of these tools. We then present an algorithm, PricingPolicy, for computing an advertising network's best response i.e., given the predictive pricing and revenue sharing policies used by its competitors, what policy should an advertising network use in response? Using PricingPolicy, we gain insight into the structure of optimal predictive pricing and revenue sharing policies. © 2008 Springer Berlin Heidelberg.
CITATION STYLE
Mungamuru, B., & Garcia-Molina, H. (2008). Predictive pricing and revenue sharing. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5385 LNCS, pp. 53–60). https://doi.org/10.1007/978-3-540-92185-1_14
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