RFM analysis for customer segmentation using machine learning: a survey of a decade of research

Abstract

Customer segmentation is a method of categorizing corporate clients into groups based on shared characteristics. In this study, we looked at the different customer segmentation methods and execute RFM analysis by using various clustering algorithms. Based on RFM values (Recent, Frequency, and Cost) of customers, the successful classification of company customers is divided into groups with comparable behaviors. Customer retention is thought to be more significant than acquiring new clients are analyzed on two different databases. Results show the significance of each method. Comparison is helps for selection of better customer segmentation.