Industry
Company Profile
- >€80bn annual revenue
- Multinational manufacturer and distributor of electricity and gas
- Employs 70,000 people worldwide and operates in about 30 countries
Situation and Objectives
- Understand reasons for contract termination based on extensive ERP/CRM data analysis
- Develop detailed model for measuring risk of churn
Project Set-up

Results
- Analyzed the most important influencing factors for contract termination
- Selected an appropriate statistical model for quantifying churn risk (logistic regression)
- Implemented a logistic regression model to identify essential risk factors
- Calculated churn risk for each customer
Impact
- Increase of customer base through significant reduction of churn