Fuzzy RFM Analysis: An Application in E-Commerce

Basar Oztaysi*, Mert Kavi

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Citation (Scopus)


RFM (recency, frequency, monetary) analysis is an essential tool for customer segmentation, which is very important for marketing, communication, and even operations management activities. RFM is a widely adopted segmentation tool since it can be accomplished by using purchase transactions. In this study, we use the purchase transactions of Modanisa.com, which is a global e-commerce website from Turkey, to build a fuzzy RFM module. In the first step, the transaction data is converted to R, F, M data parameters, and then the fuzzy c-means algorithm is used to build the RFM clusters.

Original languageEnglish
Title of host publicationIntelligent and Fuzzy Techniques
Subtitle of host publicationSmart and Innovative Solutions - Proceedings of the INFUS 2020 Conference
EditorsCengiz Kahraman, Sezi Cevik Onar, Basar Oztaysi, Irem Ucal Sari, Selcuk Cebi, A. Cagri Tolga
Number of pages8
ISBN (Print)9783030511555
Publication statusPublished - 2021
EventInternational Conference on Intelligent and Fuzzy Systems, INFUS 2020 - Istanbul, Turkey
Duration: 21 Jul 202023 Jul 2020

Publication series

NameAdvances in Intelligent Systems and Computing
Volume1197 AISC
ISSN (Print)2194-5357
ISSN (Electronic)2194-5365


ConferenceInternational Conference on Intelligent and Fuzzy Systems, INFUS 2020

Bibliographical note

Publisher Copyright:
© 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG.


  • E-commerce
  • Fuzzy c-means
  • RFM analysis


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