The customer value theory has been widely applied to investigate salient factors that influence customers’ purchasing intention in the context of e-commerce. This study extends this literature by combining predictors of product performance with customer value framework to explore the effect of in-store information on mobile application downloads. It calls for understanding the unique characteristics of mobile environment. In this study, we apply text-mining techniques to analyze customers’ reviews and product descriptions in the mobile application store and find the embedded meaningful information valued by customers. We also find that for mobile applications, price, number of raters, and helpful information in customer reviews and product descriptions have significant impacts on the number of downloads, while average rating has no influence on application downloads. Theoretical and practical implications are discussed.