By analysing trends and patterns, we were able to identify customers who were willing to switch early on and reduce the cancellation rate with special offers.
Initial situation and objectives
- Reduction of the termination rate and early identification of endangered customer relationships
Approach
- Comprehensive analysis of historical customer data with the aim of uncovering trends and patterns with regard to termination behaviour
- Identification of special risk phases within the customer journey
- Definition of churn indicators and derivation of change probabilities per customer cluster
- Forecast of the change probabilities per single customer in a Churn Cockpit
- Development of customer-specific retention and win-back products and development of an offer function within the Churn Cockpit
- Integration of the quotation function of the Churn Cockpit into the CRM system of the customer.
Results
- Early identification of customers willing to switch, enables our customer to proactively and successfully manage their churn with special offers to avoid termination or win back customers.