Predicting Customer Lifetime Value
-
Updated
Jun 23, 2020 - Python
Predicting Customer Lifetime Value
Trained a Probabilistic Model to forecast the frequency of purchases and how likely a customer is to churn in a given time period using their historical transaction data.
The purpose of this project is to recommend personalized products for segments by finding product associations.
A python package to train & evaluate Customer Lifetime Value(CLTV) models using Neural Networks & ZILN loss(developed by google)
Buy Till You Die and Customer Lifetime Value statistical models in Python.
Bayesian marketing toolbox in PyMC. Media Mix (MMM), customer lifetime value (CLV), buy-till-you-die (BTYD) models and more.
Add a description, image, and links to the customer-lifetime-value topic page so that developers can more easily learn about it.
To associate your repository with the customer-lifetime-value topic, visit your repo's landing page and select "manage topics."