CLTV-Prediction-Customer-Lifetime-Value-Prediction-BG-NBD-GammaGamma-CLTV

CLTV Analysis using BG-NBD and Gamma-Gamma Models Customer Lifetime Value Prediction

Overview

This project aims to predict Customer Lifetime Value (CLTV) using BG/NBD and Gamma-Gamma models. It analyzes customer purchasing behavior and revenue to estimate future CLTV.

Features • Predicts the expected number of transactions per customer using the BG/NBD model. • Calculates the expected average profit per customer using the Gamma-Gamma model. • Segments customers based on predicted CLTV.

Usage 1. Prepare the data and run the script. 2. After training the models, you can obtain CLTV predictions and customer segments.

Results

The project estimates the expected number of transactions and revenue per customer. Customers are segmented based on their CLTV scores.

Dependencies • Pandas • Matplotlib • Lifetimes