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

Abstract

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
Volume5
Issue number5
StatePublished - 1 Sep 2010

Keywords

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

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