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

  • Makoto Abe

    (Faculty of Economics, University of Tokyo)

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    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.

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    File URL: http://www.cirje.e.u-tokyo.ac.jp/research/dp/2004/2004cj121.pdf
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    Paper provided by CIRJE, Faculty of Economics, University of Tokyo in its series CIRJE J-Series with number CIRJE-J-121.

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    Length: 15 pages
    Date of creation: Dec 2004
    Date of revision:
    Handle: RePEc:tky:jseres:2004cj121
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