Search Platforms: Big Data and Sponsored Positions
Prof Marcel Preuss
Assistant Professor of Strategy and Business Economics
SC Johnson Graduate School
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 maximize the platform’s revenue from both sponsored position auctions and commission fees. Our results allow us to analyze the welfare effects of sponsored positions.