Identifying customer segments based on their purchasing behavior using RFM analysis and K-Means clustering.
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Updated
May 12, 2023 - HTML
Identifying customer segments based on their purchasing behavior using RFM analysis and K-Means clustering.
Project recommendation system for DonorsChoose.org in R based on RFM analysis and K-Means Clustering
KPMG Virtual Internship
RFM analysis and association rules for an online retail data set.
A simple Blazor app which takes a transaction list and generates a spreadsheet of customers along with their raw RFM metrics.
This repository contains code and analysis for performing RFM (Recency, Frequency, Monetary) analysis on retail store customer data. The analysis is followed by customer segmentation using the KMeans clustering algorithm to gain insights into customer behavior and enable data-driven marketing strategies.
Customers RFM Clustering (Market Segmentation based on Behavioral Approach)
Customer segmentation analysis
Analysis of large retailer's sales data. Customer segmentation using RFM analysis and k-means clustering
EDA and customer segmentation with RFM analysis on hacker earth dataset. https://www.hackerearth.com/challenge/hiring/LMG-analytics-data-science-hiring-challenge
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