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Abstract
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Application of data mining techniques in customer relationship management (CRM) is well-known. One of the important
issues in CRM is customer segmentation. Customer segmentation based on customer lifetime value (CLV) is a useful approach
that recently used by researchers. Although many other studies used CLV for end customer segmentation, but the aim of this
study is using CLV for retailer segmentation. RFM model (Recency, Frequency, and Monetary value) is one of the most
powerful and simplest models for estimating customer life time value. In this paper, we have used an extended version of the
RFM model, the LRFM model, which is obtained by adding L (relationship length) to the RFM model to cluster retailers of a
hygienic manufacturer in Iran. K-means clustering algorithm with K-optimum according to Davies-Bouldin index is applied on
LRFM variables. The results of retailer segmentation help the marketing managers of the manufacturer to formulate
segment-specific marketing actions for retailers.
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