Churn Mitigation ML Models


Identify customers likely to churn and mitigate customer churn.

Identify customers likely to churn (either directly by predicting the churn event or indirectly by analyzing network experience) and mitigate customer churn by contacting customers for each marketing campaign.

Example of Churn Mitigation for Telecommunications: 

Use Case Highlights
  • Applied machine learning to identify customer behavior that led to churn
  • Personalized churn reduction treatment for Tier-1 global wireless telecommunications service provider

Business Impact
  • Reduced churn: Achieved 20+ bps annual churn lift
  • Revenue lift: Achieved $145MM/year in revenue lift or approx. $2/subscriber across targeted base
  • Results A/B tested against existing efforts: Churn and lift are relative to existing campaigns
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