Customer Prioritization to Prevent Churn
Challenge
With increasing price pressure in the insurance market, competition in the area of car insurance increased. Stakeholders expressed the need to reduce the churn rate in this category. We successfully identified a subset of customers with high churn risk. Targeted marketing measures were initiated to effectively address this segment.
Achievements
- Analysis and preparation of previous customer cancellations for training purposes
- Training, testing, and evaluation of a highly effective machine learning model
- Prioritization model applied on 1.5 million car insurance customers
- Pilot marketing activities launched to prevent churn in 100k high-risk customers
Benefits
- 15+ possible use cases for similar models
- Early warning system for identifying churn-risk customers
- Active communication of prevention measures