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

What is CLV or LTV? CLV or LTV is a metric that helps you measure the customer's lifetime value to a business. In this kernel, I am sharing the customer lifetime value prediction using BG-NBD, Pareto, NBD & Gamma Model on top of RFM in Python.

Analysing the content of an E-commerce database that contains list of purchases. Based on the analysis, I develop a model that allows to anticipate the purchases that will be made by a new customer, during the following year from its first purchase.

Customer Segmentation using RFM Analysis

The binary build of LEO CDP Free Edition for training purposes

Customer & Purchase Analytics using Segmentation, Targeting, Positioning, Marketing Mix, Price Elasticity

Customer life time analysis (CLV analysis). We are using Gamma-Gamma model to estimate average transaction value for each customer.

Customer churn prediction with Python using synthetic datasets. Includes data generation, feature engineering, and training with Logistic Regression, Random Forest, and Gradient Boosting. Improved pipeline applies hyperparameter tuning and threshold optimization to boost recall. Outputs metrics, reports, and charts.

Customer Analytics for a FMCG company (K-means clustering, PCA, logistic regression, linear regression)

A deep exploration of loyalty as a multi-dimensional behavioral system shaped by intent, habit, and sensitivity. This article introduces a geometric framework for modeling customer behavior, predicting churn trajectories, and designing ML systems that understand loyalty as a dynamic state, not a metric.

AI-powered retail analytics platform that uses computer vision to track customer behavior, optimize store layouts, manage inventory, and provide personalized shopping recommendations using transformer architectures.

This repo hosts the course content of Customer Analytics, taught at Tilburg University by George Knox last taught Fall 2022.

Predicting customer churn using scikit-learn

This project explores predictive customer analytics in the e-commerce industry using the Customer Personality Analysis Dataset. By combining exploratory data analysis, supervised learning, and unsupervised segmentation techniques, it aims to uncover hidden patterns in user demographics, purchasing behaviors, and marketing responses.

Coursera-Customer analytics

Pickl.AI’s Datathon - 4

This repo is a code demo that implements a custom Customer Retention Analysis class with a number of helpful methods/functions to generate customer churn insights frequently used for marketing analytics to understand the growth and change of your customer base (new vs retained vs lost) .

"Business Insights from Transaction Data" is a Python project for e-commerce and financial services to optimize customer funnel and KPIs. It involves creating synthetic data to model realistic transaction and customer data, which is then analyzed and visualized to support data-driven decision making.

Bootcamp Women in Data - Bogotá, COL