Applying Behavioral Economics in Predictive Analytics for B2B Churn: Findings from Service Quality Data

Abstract

Abstract Motivated by the long-standing debate on rationality in behavioral economics and the potential of theory-driven predictive analytics, this paper examines the link between service quality and B2B churn. Using longitudinal B2B transactional data with service quality indicators provided by a large company, we present evidence that both rationality and bounded-rationality assumptions play significant roles in predicting organizational decisions on churn. Specifically, variables that relate to the assumed rationality of organizations appear to provide accurate predictions while, at the same time, variables that capture boundedly rational decision rules appear to play a role through “somatic states” that make organizations more sensitive to the rational variables. In addition to presenting a novel approach for predicting organizational decisions on churn, this paper offers theoretical and managerial insights as well as opportunities for future research at the intersection of behavioral economics and predictive analytics for decision-making.