The Value of Different Customer Satisfaction and Loyalty Metrics in Predicting Business Performance

Abstract

Managers commonly use customer feedback data to set goals and monitor performance on metrics such as “Top 2 Box” customer satisfaction scores and “intention-to-repurchase” loyalty scores. However, analysts have advocated a number of different customer feedback metrics including average customer satisfaction scores and the number of “net promoters” among a firm’s customers. We empirically examine which commonly used and widely advocated customer feedback metrics are most valuable in predicting future business performance. Using American Customer Satisfaction Index data, we assess the linkages between six different satisfaction and loyalty metrics and COMPUSTAT and CRSP data-based measures of different dimensions of firms’ business performance over the period 1994–2000. Our results indicate that average satisfaction scores have the greatest value in predicting future business performance and that Top 2 Box satisfaction scores also have good predictive value. We also find that while repurchase likelihood and proportion of customers complaining have some predictive value depending on the specific dimension of business performance, metrics based on recommendation intentions (net promoters) and behavior (average number of recommendations) have little or no predictive value. Our results clearly indicate that recent prescriptions to focus customer feedback systems and metrics solely on customers’ recommendation intentions and behaviors are misguided.