Telecom-Customer-Churn-Prediction and Telecom-Churn-Prediction

Maintenance 0/25
Adoption 4/25
Maturity 16/25
Community 15/25
Maintenance 0/25
Adoption 4/25
Maturity 16/25
Community 13/25
Stars: 7
Forks: 4
Downloads:
Commits (30d): 0
Language: Jupyter Notebook
License: MIT
Stars: 8
Forks: 2
Downloads:
Commits (30d): 0
Language: Jupyter Notebook
License: MIT
Stale 6m No Package No Dependents
Stale 6m No Package No Dependents

About Telecom-Customer-Churn-Prediction

usmanbvp/Telecom-Customer-Churn-Prediction

The "Telecom Customer Churn Prediction " GitHub repository is a project focused on analyzing and predicting customer churn.

This project helps telecom companies predict which customers are likely to cancel their subscriptions or switch providers. By inputting historical customer data, service usage, and churn status, you get a prediction of whether a customer is at risk of leaving. This tool is ideal for customer retention managers and marketing strategists in the telecom sector.

telecom-churn-prediction customer-retention telecom-marketing customer-analytics subscription-management

About Telecom-Churn-Prediction

ChaitanyaC22/Telecom-Churn-Prediction

In this project, data analytics is used to analyze customer-level data of a leading telecom firm, build predictive models to identify customers at high risk of churn, and identify the main indicators of churn. The project focuses on a four-month window, wherein the first two months are the ‘good’ phase, the third month is the ‘action’ phase, while the fourth month is the ‘churn’ phase. The business objective is to predict the churn in the last i.e. fourth month using the data from the first three months.

This project helps telecom companies predict which high-value prepaid customers are likely to switch providers. By analyzing past customer usage and recharge data, it identifies individuals at high risk of churn, providing insights that allow for targeted retention efforts. It's designed for business analysts and customer retention teams in the telecom sector to proactively address customer attrition.

telecom-churn-prediction customer-retention prepaid-customers customer-analytics mobile-network-operations

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