Bayesian marketing toolbox in PyMC. Media Mix (MMM), customer lifetime value (CLV), buy-till-you-die (BTYD) models and more.

Predicted clv making it easier for the auto-insurance companies to decide on the premiums of their incoming clients and thus balance the total risk in the market

R-Package for estimating CLV

Preprocessing and analyzing data to segment customers and predict their lifetime value for a specific online retail dataset

Led exploratory data analysis for a wireless mobile network company using Python, Pandas, Numpy and data visualization - Matplotlib, Seaborn, uncovering key drivers of customer churn and implementing strategies that improved retention and boosted customer lifetime value.

The case study is based on how a subscription-based e-commerce business employed customer-centric strategies to reduce churn and increase customer lifetime value. How companies are Maximizing customer spending and loyalty while minimizing subscription cancellations to enhance profits and long-term business sustainability in an e-commerce model.

Oat : Hi !

Buy Till You Die and Customer Lifetime Value statistical models in Python.

Customer lifetime value analysis is used to estimate the total value of customers to the business over the lifetime of their relationship. It helps businesses make data-driven decisions on how to allocate their resources and improve their customer relationships.

A Python project examining customer lifetime value (CLV) for Door Bell, Inc. This analysis investigates the influence of autopay on customer retention, providing valuable insights for strategic marketing decisions.

🎓📚📈 Collection of scientific publications that explore, model and predict customer churn and lifetime value (CLV)

This project predicts Customer Lifetime Value (CLV) for e-commerce. It aims at forecasting the revenue a business can expect from a customer over time. I did an explatory analysis. From Linear Regression to Neural Networks, explore how different models perform in predicting CLV.

Explore the world of data-driven customer analysis and lifetime value estimation. This project dives into customer segmentation, geographic analysis, time series insights, stock trends, and product descriptions. Join us on our journey of data exploration and optimization.

BG/NBD and Gamma Gamma probabilistic models to evaluate and predict customer churn, retention, and lifetime value of an e-commerce business

Built a customer lifetime value (CLV) model using parametric models.

A python package to train & evaluate Customer Lifetime Value(CLTV) models using Neural Networks & ZILN loss(developed by google)