Churn Modelling for Mobile Telecommunications

What is Churn Modelling 

  • Churn represents the loss of an existing customer to a competitor
  • A prevalent problem in retail:
    • Mobile phone services
    • Home mortgage refinance
    • Credit card
  • Churn is a problem for any provider of a subscription service or recurring purchasable
    • Costs of customer acquisition and win-back can be high
    • Much cheaper to invest in customer retention
    • Difficult to recoup costs of customer acquisition unless customer is retained for a minimum length of time
  • Churn is especially important to mobile phone service providers
    • easy for a subscriber to switch services
    • Phone number portability will remove last important obstacle

Predicting Churn: Key to a Protective Strategy

  • Predictive modelling can assist churn management
    • By tagging customers most likely to churn
  • High risk customers should first be sorted by profitability
    • Campaign targeted to the most profitable at-risk customers
    • Typical retention campaigns include
      • Incentives such as price breaks
      • Special services available only to select customers
  • To be cost effective retention campaigns must be targeted to the right customers
    • Customers who would probably leave without the incentive
    • Costly to offer incentives to those who would stay regardless

 
Here, We have a sample telecom data on which we will run Churn Modelling using R code.

Loading data directly from web

Fitting a Model

How does the linear model perform

 

How does the Logistic Regression perform

 

How does the Decision Tree perform

 

How does the Random Forest perform

 

Conclusion:

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