Your Churn Threshold Is a Pricing Decision

Using a default 0.5 probability threshold in churn prediction models is a significant financial error, as it wrongly assumes the cost of losing a customer equals the cost of a retention offer. In reality, the cost of failing to identify a customer who is about to leave can be over 13 times greater than the cost of unnecessarily targeting a loyal customer with a discount. A more profitable approach involves calculating the true dollar cost of each misclassification by using survival analysis to accurately estimate customer lifetime value and foregone revenue. By optimizing the classification threshold based on these real-world unit economics, businesses can avoid millions in recoverable costs that are otherwise lost by default modeling practices.