In this study, we conducted a multilevel analysis of factors affecting customer satisfaction in the global hotel industry. The survey data collected from TripAdvisor.com included customer reviews relating to 13,410 hotels located in 80 major global urban tourism destinations. We examined multiple relevant factors at each of the following five levels of analysis: (a) service encounter, (b) visitor, (c) visitor’s nationality, (d) hotel, and (e) destination. The results show that hotel attributes and the personal characteristics of visitors most powerfully influence customer satisfaction. However, the purpose of the trip, the characteristics of the destination, and the visitor’s nationality are also found to play an important role in hotel evaluation. By integrating multiple levels of analysis into a single statistical model, multilevel modeling framework enables researchers and professionals to see the “big picture” of factors affecting customer satisfaction in the contemporary hotel industry.