Search Platforms: Big Data and Sponsored Positions

Abstract We study a search platform ranking firms’ products across sponsored and organic positions, accounting for the incentives of both firms and consumers. To characterize an optimal ranking when the number of firms is large, we formulate a Mixing Principle for Consumer Search, adapting tools from the social learning literature. The platform assigns the products it deems best to sponsored positions and obfuscates the content of organic positions subject to consumers’ participation constraints. Obfuscation serves to maximise the platform’s revenue from both sponsored position auctions and commission fees. Our results allow us to analyse the welfare effects of sponsored positions.