The Customer May Not Always Be Right: Customer Compatibility and Service Performance

This paper investigates the impact of customer compatibility—the degree of fit between customers’ needs and the capabilities of the operations serving them—on customer experiences and firm performance. We use variance decomposition analysis to quantify the relative importance of customer, employee, process, location, and market-level effects on customer satisfaction. In our models, which explain roughly a quarter of the aggregate variance, differences among customers account for 96%–97% of the explainable portion. Further analysis of interaction-level data from banking and quick-service restaurants reveals that customers report relatively consistent satisfaction across transactions with particular firms but that some customers are habitually more satisfied than others. A second set of empirical studies provides evidence that these customer-level differences are explained in part by customer compatibility. Customers whose needs, proxied by differences in demographics and product choices, diverge more starkly from those of their bank’s average customers report significantly lower levels of satisfaction. Consistently, banks that serve customer bases with more dispersed needs receive lower satisfaction scores than banks serving customer bases with less dispersed needs. Finally, a longitudinal analysis of the deposit and loan growth of all federally insured banks in the United States from 2006 to 2017 reveals that customer compatibility affects a firm’s financial performance. Branches with more divergent customers grow more slowly than branches with less divergent customers. Institutions serving customer bases with more dispersed needs have branches that exhibit slower growth than those of institutions serving customer bases with less dispersed needs. This paper was accepted by Vishal Gaur, operations management.