Customers Clustering Based on RFM Model by Using Fuzzy C-means Algorithm (Case Study: Zahedan City Refah Chain Store)

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IMANI ABDOLMAJID; Abbasi Meysam

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Journal: PUBLIC MANAGEMENT RESEARCHES Year:2017 | Volume:10 | Issue:37 Page(s): 251-276

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Information Journal Paper

Title

Customers Clustering Based on RFM Model by Using Fuzzy C-means Algorithm (Case Study: Zahedan City Refah Chain Store)

Author(s)

IMANI ABDOLMAJID | Abbasi Meysam | Issue Writer Certificate

Keywords

Fuzzy clusteringQ1

Fuzzy AHPQ2

RFM modelQ1

Customer lifetime value (CLV)Q1

Abstract

One of the major challenges of customer-centric organizations is the recognition of customers, the distinction between different groups of customers and their ranking. Clustering is one of the data mining techniques used to group customers into their various characteristics. The main purpose of the research is to customer clustering based on the Recency, Frequency and Monetary indicators using the fuzzy c-means algorithm. The study was conducted on 76379 registered transactions from customers of Zahedan City Refah Chain Store. The results of this research provide a framework for developing customer relationship management programs for each customer group...

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APA: Copy

IMANI, ABDOLMAJID, & Abbasi, Meysam. (2017). Customers Clustering Based on RFM Model by Using Fuzzy C-means Algorithm (Case Study: Zahedan City Refah Chain Store). PUBLIC MANAGEMENT RESEARCHES, 10(37 ), 251-276. SID. https://sid.ir/paper/222102/en

Vancouver: Copy

IMANI ABDOLMAJID, Abbasi Meysam. Customers Clustering Based on RFM Model by Using Fuzzy C-means Algorithm (Case Study: Zahedan City Refah Chain Store). PUBLIC MANAGEMENT RESEARCHES[Internet]. 2017;10(37 ):251-276. Available from: https://sid.ir/paper/222102/en

IEEE: Copy

ABDOLMAJID IMANI, and Meysam Abbasi, “Customers Clustering Based on RFM Model by Using Fuzzy C-means Algorithm (Case Study: Zahedan City Refah Chain Store),” PUBLIC MANAGEMENT RESEARCHES, vol. 10, no. 37 , pp. 251–276, 2017, [Online]. Available: https://sid.ir/paper/222102/en

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