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ChurnGuard, a subscription service platform, has developed a binary classification model to predict customer churn, aiming to reduce churn rates and improve retention. Recently, the F1 score has been reported to be 0.65, raising concerns about the model's effectiveness in balancing precision and recall.
| Metric | Current Value | Previous Value | Change |
|---|---|---|---|
| Precision | 0.70 | 0.75 | -6.7% |
| Recall | 0.60 | 0.55 | +9.1% |
| F1 Score | 0.65 | 0.65 | 0% |
| AUC-ROC | 0.78 | 0.80 | -2.5% |
| Churn Rate | 15% | 12% | +3% |
Despite a stable F1 score, the decline in precision and the increase in churn rate indicate potential issues with the model's ability to identify at-risk customers accurately. The product team is concerned about the implications of these metrics for customer retention strategies.