Analyzing customer sales data with a fuzzy set approach

Hsin Chieh Wu, Tin-Chih Chen*, Ming Hsuan Chiu

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

2 Scopus citations


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.

Original languageEnglish
Pages (from-to)536-539
Number of pages4
JournalInternational Review on Computers and Software
Issue number5
StatePublished - 1 Sep 2010


  • CRM
  • Customer importance
  • Fuzzy C-means
  • Fuzzy set approach
  • RFM model

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