"Incorporating Theory and Modeling in Data Analysis for CRM: RF Analysis based on a Consumer Behavior Model"(in Japanese)

While RFM analysis is popular among practioners, ad-hoc rules are often employed to judge whether customers are alive or not. Because customers do not declare explicitly when they are dead, a company infers a customer is dead if she did not make any purchase, for example, for over three months. Even with the same period of nonpurchase, however, customers with a long interpurchase time need not be worried for death whereas those with a short interpurchase time could be dead. Hence, it is very important to account for customer heterogeneity when assessing the survival of customers. In this research, using standard RF data, I will derive the survival probability of an individual customer based on the common hypotheses on consumer behavior.