Customer Segmentation using RFM Analysis

Introduction In a previous post, we had introduced our R package rfm but did not go into the conceptual details of RFM analysis. In this post, we will explore RFM in much more depth and work through a case study as well. RFM (Recency, Frequency & Monetary) analysis is a behavior based technique used to segment customers by examining their transaction history such as:

RFM Analysis in R

We are pleased to announce the rfm package, a set of tools for recency, frequency and monetary value analysis, designed keeping in mind beginner/intermediate R users. It can handle: transaction level data customer level data Installation # Install release version from CRAN install.packages("rfm") # Install development version from GitHub # install.packages("devtools") devtools::install_github("rsquaredacademy/rfm") Shiny App rfm includes a shiny app which can be launched using