Key Data Inputs for Churn Prediction Models
Key Data Inputs for Churn Prediction Models
Explains the types of data used by AI to predict churn, such as policy history, claims experience, interaction frequency, and payment behaviors. It highlights how richer, multidimensional datasets improve model accuracy. This underscores the importance of data quality and integration for effective predictions.