"Churn Prediction for Video Streaming Company" is a repository dedicated to implementing predictive models and data analytics to understand customer churn in a video streaming company.
This repository contains code and resources for predicting customer churn in a video streaming company.
When it comes to a video streaming company or any other subscription-based business, the term "churn" is used to describe the action of customers ending or canceling their subscription and ceasing to use the company's services.
Subscription cancellation can happen for a multitude of reasons, including:
- the customer completes all content they were interested in, and no longer needs the subscription
- the customer finds themselves to be too busy and cancels their subscription until a later time
- the customer determines that the streaming service is not the best fit for them, so they cancel and look for something better suited
The project focuses on understanding the likelihood of individual customers churning in their subscriptions, enabling the company to allocate resources effectively and take proactive measures to retain valuable customers.
The repository includes data preprocessing, feature engineering, and model-building scripts to develop an accurate churn prediction model, aiding the company's efforts in customer retention and support.