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Deriving Customer Lifetime Value from RFM Measures:Insights into Customer Retention and Acquisition

Author

Listed:
  • Makoto Abe

    (Faculty of Economics, The University of Tokyo)

Abstract

The wide use of RFM analysis in CRM suggests that these measures contain rather rich information about customer purchase behavior. This research, using the RFM measures of a customer, develops an individual-level CLV model that identifies the underlying behavior traits of purchase rate, lifetime and spending, which are then linked to CLV. In the application to two datasets, frequent shoppers program data from a department store and a CD chain, the model produces customer-specific metrics that are useful for identifying preferred customers and taking marketing actions targeted at the individual level in CRM. The paper then presents a retention program for existing customers that is most effective in terms of Marketing ROI, such as what action needs to be taken to which customers at which timing. For prospective customers without RFM measures, by relating the demographic characteristics to behavioral traits, insight into acquisition strategy is obtained. --

Suggested Citation

  • Makoto Abe, 2015. "Deriving Customer Lifetime Value from RFM Measures:Insights into Customer Retention and Acquisition," CIRJE F-Series CIRJE-F-962, CIRJE, Faculty of Economics, University of Tokyo.
  • Handle: RePEc:tky:fseres:2015cf962
    as

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    File URL: http://www.cirje.e.u-tokyo.ac.jp/research/dp/2015/2015cf962.pdf
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    References listed on IDEAS

    as
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