What Improves Customer Satisfaction in Mobile Banking Apps? An Application of Text Mining Analysis

Abstract

Consumer-generated reviews re fl ect consumers ' experiences and perceptions toward a product or service. In this context, we propose a text mining approach to identify factors that improve customer satisfaction in the mobile banking app service. To do so, we collect 96,140 mobile app reviews for four U.S. banks: Bank of America, Capital One, Chase, and Wells Fargo. Using the Latent Dirichlet Allocation (LDA) topic model, we fi rst derive the critical quality dimensions such as ease of use, convenience, security, and customer support. Analysis of weekly panel data shows that positive responses to the security and convenience of mobile banking apps improve app ratings. However, increased comments about insecurity, negative customer support experiences, discomfort, and complexity lower user ratings. Overall, the empirical results support that security is the most in fl uential factor in customer satisfaction with mobile fi nancial services.