Default Churn Thresholds Waste $86 per Customer
90% of 36 IBM Telco churn analyses use F1 and a 0.5 threshold, assuming equal costs for false positives and negatives. That is wrong by 13x, burning $86 per customer, or $8.6M at 100k subscribers. Swap accuracy for profit curves tied to LTV and CAC.
A review of 36 IBM Telco churn analyses finds 90% report F1 or accuracy with a default 0.5 threshold, treating false positives and negatives as equally costly. The real asymmetry is 13 to 1: missing a churner is 13 times more expensive than over-treating a loyalist. Default thresholds burn $86 per customer, or $8.6 million at 100,000 subscribers. Fewer than 15% include a profit curve, and none compute LTV via survival analysis.
Read the original → Towards Data Science
- #churn
- #mlops
- #classification
- #unit economics
- #threshold tuning
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