In this chapter, we analyze the economics behind the use of big data and, in particular, ratings, reviews, and recommendations that have become mainstream on digital platforms. We start in Section 2.1 by analyzing rating and review systems. These systems provide platform users with information about either products or their counterparties to a transaction. Of crucial importance is, of course, the informativeness of these systems, which depends on the users’ actions. We then turn, in Section 2.2, to recommender systems, which aim to reduce users’ search cost by pointing them towards transactions that may better match their tastes. Besides the ability of such systems to generate network effects, we also discuss their effects on the distribution of sales between “mass-market” and “niche” products. Finally, in Section 2.3, we complement the analysis of ratings and recommender systems by uncovering additional channels through which big data may generate network effects and other self-reinforcing processes on platform.