shahriar-rahman/Netflix-Customer-Retention-using-GPR
Forecasting Netflix Customer Retention based on Gaussian Process Regression
This project helps businesses understand how long their customers are likely to stay subscribed, also known as Customer Lifetime Value (CLV). It takes detailed customer activity data, cleans and analyzes it, and then uses a machine learning model to predict future retention. The output is a clear forecast of customer retention, useful for subscription-based businesses like streaming services.
No commits in the last 6 months.
Use this if you manage a subscription-based service and need to predict how long customers will remain active to inform marketing and retention strategies.
Not ideal if you're looking for an off-the-shelf, plug-and-play solution without any data science expertise, as this is a research-oriented machine learning model.
Stars
14
Forks
1
Language
Python
License
MIT
Category
Last pushed
Jul 22, 2023
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/shahriar-rahman/Netflix-Customer-Retention-using-GPR"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
retentioneering/retentioneering-tools
Retentioneering: product analytics, data-driven CJM optimization, marketing analytics, web...
iterative/demo-bank-customer-churn
Demo DVC project training a classification model on tabular data
junfengn-ctrl/uplift-modeling-customer-retention
End-to-end uplift modeling pipeline for customer retention using T-Learner and X-Learner with...
gattsu001/Telecom-Churn-Predictor
Predicts which telecom customers are likely to churn with 95% accuracy using engineered features...
himanshu-03/Customer-Churn-Prediction
The Customer Churn table contains information on all 7,043 customers from a Telecommunications...