Analytics
Propensity Modeling
Propensity modeling uses statistical techniques to predict the likelihood that a customer will take a specific action, such as purchasing, churning, or upgrading. It assigns a probability score to each individual, enabling marketers to prioritize outreach and allocate resources effectively.
Examples
An insurance company uses propensity modeling to identify policyholders with a high probability of lapsing and targets them with personalized renewal campaigns.
Best Practices
Validate your propensity models with holdout testing, refresh them regularly as customer behavior evolves, and combine scores with qualitative insights for best results.