Churn Prediction

Success Stories

Churn Prediction
Sasken Solution

Scope

  • Churn is a huge problem for the client. Example – Two-cycle churn is between 60 & 75%:
    • Cannot optimize wholesale cost as it is too risky to place on bundles
    • Loss of revenue
    • Reduced predictability of business
  • Churn problem compounded by pre-paid model as there is no way to contact the customer after he has churned and attempt a win back

Solution

Adopted a phased-approach for delivery of churn management solution

  • Phase 1 involved data collection, aggregation & analysis, development of statistical models to predict churn & manual generations of campaign lists
  • Phase 2 was focused on automation
  • Phase 3 is about global roll out (work-in-progress)

Impact

  • Added competitive advantage by predicting the possibility of churn in advance; possible to take measures to prevent churn
  • Churn prediction & management will also help ensure effective spend of marketing in the context of base management

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