mmejdoubi / rfm-analysis-python

This repository contains RFM analysis applied to identify customer segments for global retail company and to understand how those groups differ from each other.

RFM Analysis in Python

Identifying customer segments is beneficial for selecting profitable customers and developing customer loyalty. RFM (Recency-Frequency-Monetary) analysis is a simple technique for behaviour based customer segmentation. It is used to determine quantitatively which customers are the most valuable ones by examining:

• how recently a customer has purchased (recency),
• how often they purchase (frequency),
• how much the customer spends (monetary).

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Customer Segmentation with RFM Analysis

In the analysis the dataset of global retail company was examined to identify RFM segments and find patterns in the customer base. The analysis contains:

• Creating customer segments with RFM analysis,

• Evaluating distribution of Recency, Frequency and Monetary,

• Analysis of size and value of RFM segments,

• Demographic analysis of RFM segments,

• Behavioral analysis of RFM segments.

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