Definition
Using machine learning to identify customers who are likely to stop purchasing within a defined period. Fundle's churn models monitor declining visit frequency, reducing basket size, narrowing category breadth, and disengagement signals to predict churn 30 days before it happens.
Why Churn Prediction Matters in Retail
Understanding and implementing churn prediction is critical for modern retail operations. Brands and mall operators that leverage churn prediction effectively see measurable improvements in customer retention, revenue attribution, and operational efficiency.
Fundle.ai's platform includes built-in churn prediction capabilities as part of its AI-powered retail intelligence stack — no additional tools or integrations required.
Related resources
Looking for more? Open the Industries menu to browse playbooks by sector, brand or mall.
