Personalized product recommendations and firm performance

This paper investigates the incentives of e-commerce platforms to show personalized recommendations and its effects on performance. A theoretical framework is developed that characterizes the optimal decision policy of a firm, given current state of shoppers. The key finding is that the firm must always show recommendations to shoppers in the high state above a certain price or value threshold. In the low state, recommending is optimal if the “salience effect” is above a threshold that maximizes discounted future stream of profits. An empirical model provides support to the theoretical findings, highlighting the reputation effects of personalized recommendations, using browsing and purchase data from a Finnish multi-product platform. While recommendations are associated with a 29% increase in firm revenue, relevance of such recommendations potentially boost revenue by a significant 30%. Furthermore, strong evidence is presented that consumer state is endogenous in firm revenue regressions. A three-step IV process extracts the direct effect of consumer state on revenue which shows positive association between reputation effects and firm performance.