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Predict Churn for a Telecom Company using Logistic Regression Classification in R

Data Science Project in R- Predict the churn customer of telecom sector and find out the key drivers that lead to churn. Learn how the logistic regression model using R can be used to identify the customer churn in telecom dataset.
What are the prerequisites for this project?
  • This data science project will be executed in R programming language.

What will you learn

  • Understand the customer behavior
  • Understand reasons for churn
  • What are the top factors
  • How to retain customers
  • Apply multiple classification models

Project Description

Customer churn refers to a decision made by the customer about ending the business relationship. It is also referred to the loss of clients or customers. Customer loyalty and customer churn always add up to 100%. If a firm has a 60% loyalty rate, then their loss or churn rate of customers is 40%. As per 80/20 customer profitability rule, 20% of customers are generating 80% of revenue. So, it is very important to predict the users likely to churn from the business relationship and the factors affecting the customer decisions. Here we are going to show how logistic regression model using R can be used to identify the customer churn in the telecom dataset.

Instructors

 
Pradeepta

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