GitHub - knownbymanoj/Customer_Attrition: EDA and ML model prediction for Customer Churn in a US Telecommunication industry.

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EDA and ML model prediction for Customer Churn in a US Telecommunication industry.

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Name		Name	Last commit message	Last commit date
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.ipynb_checkpoints		.ipynb_checkpoints
Readme.txt		Readme.txt
Telco-Customer-Churn.csv		Telco-Customer-Churn.csv
Telecom Churn Analysis.ipynb		Telecom Churn Analysis.ipynb

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Problem statement:
Predict behavior to retain customers. You can analyze all relevant customer data and develop focused customer retention programs

Scenario:
Looking at statistics from the European Business Review, it is astounding to see that telecommunications companies lose about $65 million a month due to client attrition. Isn't it much too expensive?

The power of data & statistics may be used to analyze the factors that impact customer attrition, identify customers who are most likely to churn, and offer them some discounts.