| 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. |