International Journal of Research in Industrial Engineering (Mar 2022)
Customer segmentation to identify key customers based on RFM model by using data mining techniques
Abstract
Accurate identification, attracting, and keeping the customers particularly loyal Customer Relationship Management (CRM) with the goal of optimum allotment of resources and achievement to higher profit is not a competitive profit, but it is a life persistence necessity of companies in virtual space. One of the challenges of companies in this part is how to identify the customer’s traits and the separation of different segments of them. Now Customer Lifetime Value (CLV) is the comparison priority in the segmentation of customers to congruous segments. The main goal of this research is to identify key or strategic customers using the RFM model. In this part after determining the amount of Recency, Frequency and Monetary (RFM) in, registered transactions of one store in Iran (Refah Chain Store) at a time about seven months from 23 September 2017 to 20 April 2018 (71161 transactions as final inputs were used), the weight of each variable according to the fuzzy Analytic Hierarchy Process (AHP) was determined. At the next stage customers using the K-means and Two-step’s algorithms were clustered and K-means the method according to the Silhouette index was the better algorithm of this letter. According to the results, customers were segmented into three parts and CLV was calculated and for identifying key or strategic customer segmentation, the clustering process was repeated and priorities of all clusters were indicated. Results of data analysis are below: Segment 3: customers of this segment were 3425 members and 11.5% of all company customers were the most loyal customers those are identified as golden customer's segment and all of the variables were higher than average of all data. This research identified the valuable customers for the shop, and it gives them a chance to choose goal customers and invest in them.
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