"Incorporating Theory and Modeling in Data Analysis for CRM: RF Analysis based on a Consumer Behavior Model"(in Japanese)
AbstractWhile 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.
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Bibliographic InfoPaper provided by CIRJE, Faculty of Economics, University of Tokyo in its series CIRJE J-Series with number CIRJE-J-121.
Length: 15 pages
Date of creation: Dec 2004
Date of revision:
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