Online Search and Product Rankings : A Double Index Approach

We develop a flexible yet tractable model of consumer search and choice, and applyit to the problem of product rankings optimization by online retail platforms. In themodel, products are characterized by an observable search index, which governs whatconsumers search; and a utility index, which governs which of the searched options ispurchased. We show that this framework generalizes several commonly used searchmodels. We then consider how platforms should assign products to search ranks.To optimize consumer surplus, platforms should promote “diamonds in the rough,”products whose utility index exceeds their search index. By contrast, to maximize staticprofits, the platform should favor high-margin products, creating a tension betweenthe two objectives. We develop computationally tractable algorithms for estimatingconsumer preferences and optimizing rankings, and we provide approximate optimalityguarantees in the latter case. When we apply our approach to data from Expedia, oursuggested ranking achieves both higher consumer surplus and higher revenues than isachieved by the Expedia ranking, and also dominates ranking the products in order ofutility