Can we effectively predict and seed top-performing products, services, or businesses through a small set of individuals? Most previous studies focused on the effects and predictive power of the adoptions by" hub" individuals with many social contacts, but the resulting insights are typically not applicable by firms that lack access to relevant social network data. Here we examine the predictive power of selected customer groups detected without network data across diverse domains: an e-commerce retailer, Yelp, Ethereum, and user-generated content online communities. Despite the differences among the studied domains, we consistently detect a small set of" discoverer" customers who exhibit a stronger and more reliable out-of-sample predictive power than previously-studied customer groups. Further, the discoverers' early adoptions can improve the performance of statistical-learning models for success prediction. We explore the marketing implications of the found regularities through a two-stage laboratory experiment, whose results indicate that informing the discoverers first on new products has a causal impact on the success difference between high-quality and lowquality products. Our findings suggest that organizations can leverage the discoverers' behavior to predict and influence the differential success of new products, even without the need for social network data.
