RFM Customer Segmentation ML Frameworks

End-to-end projects applying RFM (Recency, Frequency, Monetary) analysis combined with K-Means clustering for customer segmentation and business insights. Does NOT include general recommendation systems, churn prediction, or segmentation using other methodologies without RFM analysis.

There are 38 rfm customer segmentation frameworks tracked. The highest-rated is mukulsinghal001/customer-lifetime-prediction-using-python at 40/100 with 160 stars.

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#	Framework	Score	Tier	Stars	Language
1	mukulsinghal001/customer-lifetime-prediction-using-python What is CLV or LTV? CLV or LTV is a metric that helps you measure the...	40	Emerging	160	Jupyter Notebook
2	kamalu-chioma/OpenRFM Customer Segmentation based on Recency, Frequency and Monetary value	35	Emerging	6	Python
3	pramodkondur/Customer-Segmentation-RFM-CLV This project analyzes online retail transaction data to identify distinct...	31	Emerging	4	Jupyter Notebook
4	shawn-y-sun/Customer_Analytics_Retail Customer Analytics for a FMCG company (K-means clustering, PCA, logistic...	29	Experimental	19	Jupyter Notebook
5	galafis/Customer-Segmentation-Analysis Análise de Segmentação de Clientes usando Machine Learning.	29	Experimental	1	Python
6	harishb1407/crm-using-ai-ml Transforming CRM using AI/ML	26	Experimental	8	Jupyter Notebook
7	basel-ay/Customer-Lifetime-Value-Prediction Clustering and predicting customer lifetime value with machine learning and...	25	Experimental	6	Jupyter Notebook
8	rafael-sfernandes/customer-clustering A clustering case based on the customers RFM (Recency, Frequency and...	23	Experimental	1	Jupyter Notebook
9	maj34/Analysis-Programming-Project [ 전공 프로젝트: 분석 프로그래밍 ] L사의 고객 세분화를 통한 맞춤형 상품 추천	21	Experimental	9	Jupyter Notebook
10	tushar2704/CLV-Prediction The primary goal of the Customer Lifetime Value Project is to develop a...	19	Experimental	4	Jupyter Notebook
11	mftnakrsu/CLTV_prediction CLTV prediction, BGNBD, Gamma Gamma	17	Experimental	1	Python
12	DaniaRaheel/Customer-Segmentation-by-RFM-Kmeans Customer segmentation using RFM analysis and K-Means clustering with Power...	17	Experimental	—	Jupyter Notebook
13	StefanosStefanidis93/high-value-customer-prediction High-Value Customer Prediction using Logistic Regression on retail data —...	15	Experimental	1	Jupyter Notebook
14	jayesh3103/RetailPulse E-commerce customer analytics — RFM segmentation, churn prediction, SHAP,...	15	Experimental	1	Python
15	orewagaurav/ecommerce-customer-analytics-ml ML-powered customer analytics platform that segments users using RFM...	15	Experimental	1	Jupyter Notebook
16	DhruvalVakil/Customer-Segmentation-Product-Recommendation I have implemented segmentation using Machine Learning Algorithms like...	14	Experimental	—	Jupyter Notebook
17	Aghil-hub/Customer_Segmentation K-means customer segmentation using RFM and category behavior for a retail brand	14	Experimental	—	Jupyter Notebook
18	devdebdeb/RFM-Clustering Projeto de Clusterização e Segmentação de Clientes em delivery utilizando...	14	Experimental	—	Python
19	anikajairath/Ecommerce-Advanced-Analysis-Project Advanced e-commerce analytics using Python, SQL, and ML techniques (RFM,...	14	Experimental	—	Jupyter Notebook
20	growithanand/customer-behavior-segmentation Customer segmentation using RFM analysis, K-Means clustering, and PCA...	14	Experimental	—	Jupyter Notebook
21	Tish-01/customer-segmentation- End-to-end ML project for customer segmentation & retention prediction using...	14	Experimental	—	Jupyter Notebook
22	nandita2812/AI-Retail-Customer-Intelligence AI-powered system for customer segmentation, churn prediction, and product...	14	Experimental	—	Jupyter Notebook
23	Ronit178693/Smart-Sales-Customer-Intelligence-System Smart Sales & Customer Intelligence System is a machine learning–based...	14	Experimental	—	Python
24	g-lopes2026/customer-segmentation-kmeans Aplicação interativa de Machine Learning utilizando o algoritmo K-Means para...	14	Experimental	—	Python
25	ntokozon990928-byte/call-center-analytics Call center analysis and PCP risk prediction using Python and Power BI	14	Experimental	—	Jupyter Notebook
26	itsaryanchauhan/online-retail-analysis RFM customer segmentation analysis of £17.7M retail dataset using K-means...	14	Experimental	3	Jupyter Notebook
27	Hasvitha-M/customer-segmentation-rfm-kmeans Customer segmentation using RFM analysis and K-Means clustering on 500K+...	14	Experimental	—	Jupyter Notebook
28	SuzzieA/predictive_customer_behaviour RFM-based feature engineering and regression modelling to analyse and...	14	Experimental	—	Jupyter Notebook
29	divyansh-sahai/Customer-Retention-Prediction Customer retention analysis and repeat purchase prediction using machine...	14	Experimental	—	Jupyter Notebook
30	RameshSTA/clv-long-term-optimization Production-grade CLV forecasting, churn risk modeling & budget-constrained...	14	Experimental	—	Jupyter Notebook
31	Sukma-Jaya/ml-advanced-retail-segmentation 🛒 Uncover customer insights through advanced retail segmentation using...	13	Experimental	—	JavaScript
32	ssgm2911/Customer-Value-Prediction Customer value prediction using machine learning to estimate customer...	13	Experimental	—	Jupyter Notebook
33	ThakkarVidhi/rfm-customer-segmentation Segment Sphere is a customer segmentation tool using RFM analysis to group...	11	Experimental	—	HTML
34	mvnbernardes-source/segmentacao-clientes-rfm Segmentação de clientes utilizando análises RFM e K-Means para identificar...	11	Experimental	—	Jupyter Notebook
35	JamesN883/pyspark-customer-analytics Customer segmentation and churn prediction using PySpark with RFM,...	11	Experimental	—	Jupyter Notebook
36	grschneier/marketing-analytics-case-study A comprehensive analysis of 2,205 customers using clustering, RFM analysis,...	11	Experimental	—	Jupyter Notebook
37	chinneee/R--Marketing_Campaign_Analysis Using a variety of techniques, including descriptive analysis, machine...	10	Experimental	2	R
38	sankalp130/Customer-Lifetime-Value-Prediction By understanding and predicting CLV, PT Asuransi Mobil Sejahtera can make...	10	Experimental	2	Jupyter Notebook

Comparisons in this category

Customer-Segmentation-RFM-CLV and Customer-Lifetime-Value-Prediction (31 vs 25) Customer-Segmentation-RFM-CLV and customer-clustering (31 vs 23)