Industry

Energy & Utilities

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