Python script (and IPython notebook) to perform RFM analysis from customer purchase history data

This contains projects based on Algorithmic Marketing like Marketing Mix Modeling, Attribution Modeling & Budget Optimization, RFM Analysis, Customer Segmentation, Recommendation Systems, and Social Media Analytics

In this project, a RFM model is implemented to relate to customers in each segment. Assessed the Data Quality, performed EDA using Python and created Dashboard using Tableau.

Customer Segmentation using RFM Analysis

Algorithmic Marketing based Project to do Customer Segmentation using RFM Modeling and targeted Recommendations based on each segment

Python Package for RFM Analysis and Customer Segmentation

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 (Recency, Frequency, Monetary) analysis is a proven marketing model for behavior based customer segmentation. It groups customers based on their transaction history – how recently, how often and how much did they buy. RFM helps divide customers into various categories or clusters to identify customers who are more likely to respond to promot…

A Repository Maintaining My Summer Internship Work At Datalogy As A Data Science Intern Working On Customer Segmentation Models Using Heirarchical Clustering, K-Means Clustering And Identifying Loyal Customers Based On Creation Of Recency, Frequence, Monetary (RFM) Matrix.

Data Analysis with Python - Customer Segmentation ( RFM Analysis) - Power BI Dashboard - Tableau Dashboard

Data Mining project 2020/2021 @ University of Pisa

A fully interactive data storytelling dashboard for e-commerce analytics. Built with Python, Streamlit, and Plotly, it transforms transactional data into actionable insights through KPIs, cohort retention, RFM segmentation, and global visualizations, perfect for analysts and data scientists.

A comprehensive guide and codebase for building interactive storytelling dashboards with Python, Streamlit, and Plotly. Learn how to transform static analytics into dynamic, user-driven data experiences that engage and inspire, featuring RFM segmentation, cohort analysis, and real-world insights.

The main purpose of this repository is to model and forecast customer lifetime value.

customer segmentation with rfm

This repository contains the "RFM Analysis" for a Sales Data of a Retailer in SQL. This is part of my Data Science Portfolio Projects

Segmented customers based on Recency,Frequency & Monetary Value (RFM) metrics using K-means clustering algorithm

Crafting & testing a dynamic Recency-Frequency-Monetary model as published in Towards Data Science on Medium.com

Basic RFM model to kickstart customer value segmentation. This project aims to guide the first time user to have a bouncing board into setting up their first segmentation model.