An important technique of analyzing sales data for customer importance evaluation is RFM analysis. However, there are some shortcomings in traditional crisp RFM models. To overcome these shortcomings, a fuzzy set approach is proposed. Firstly, the formula for calculating the R, F, and M scores as well as that for calculating the RFM total score are fuzzified, and a customer's importance is now evaluated with a more reasonable fuzzy value instead. Secondly, a formula for calculating the fuzzy weighted RFM total score is also proposed to deal with the situation in which R, F, and M are considered unequally important. After screening out unimportant customers with low fuzzy (weighted) RFM total scores, the Fuzzy C-means approach is applied to cluster important customers based on the fuzzy RFM scores, so as to establish different marketing strategies. A demonstrative example is given. Advantages of the fuzzy set approach over the existing approaches are then concluded.
|Number of pages||4|
|Journal||International Review on Computers and Software|
|State||Published - 1 Sep 2010|
- Customer importance
- Fuzzy C-means
- Fuzzy set approach
- RFM model