Testing the predictive validity of the net promoter score in ski resorts: a longitudinal analysis

Abstract The net promoter score (NPS), often acclaimed for its simplicity and predictive power for growth, has become a ubiquitous metric across industries. However, empirical findings about its effectiveness are mixed. Thus, we examine the effectiveness of different customer-related metrics in predicting skier visits, compare NPS’s predictive ability against other metrics like customer satisfaction and perceived value, and consider how the destination experience of the sampled respondents impacts the predictive ability of NPS. We leverage a unique longitudinal dataset (136 destination-year observations), combining bi-annual survey data on customer satisfaction for the period 2011/12 to 2017/18 (more than 120,000 responses), along with archival access data from 38 ski resorts. We examine our research questions applying panel data regression analysis in STATA. Our findings reveal that while NPS significantly influences skier visits, it is not superior to customer satisfaction. Notably, the ski destination experience of the sampled respondents attenuates the predictive ability of NPS. Additionally, NPS with a two-year lag demonstrates the strongest explanatory power. The paper extends literature by providing important theoretical and practical insights on the value of NPS for predicting skier visits to ski resorts. Specifically, we show that NPS has predictive power but is not superior to traditional customer satisfaction metric. In addition, we provide crucial insights for how NPS metrics must be implemented by demonstrating that the destination experience of the sampled respondents impacts the predictive power of NPS.