Key findings
42.7%
Month-to-month churn rate vs just 2.8% on two-year contracts
0.838
AUC-ROC — model ranks a churner above a non-churner 84% of the time
53%
New customers churn in first 6 months — most critical retention window
45.3%
Electronic check churn rate vs 15% for auto-pay customers
496
High-risk customers identified for immediate retention outreach
$236K
Estimated annual revenue protected at 30% retention success rate
Resources
Live interactive dashboard
7,043
Customers
26.5%
Churn Rate
0.838
AUC-ROC
$236K
Annual Savings
Churn by contract type
Month-to-month churns 15x the two-year rate
Churn by tenure group
First 6 months: 53% churn rate
Churn by payment method
Electronic check 3x auto-pay churn rate
ROC curve — model performance
AUC = 0.838 · better than random by a wide margin
Customer risk tiers — intervention guide
Based on predicted churn probability from logistic regression model
| Risk tier | Probability | Customers | % of base | Recommended action |
|---|---|---|---|---|
| High Risk | >70% | 496 | 20.6% | Immediate outreach — retention offer or account review |
| Medium Risk | 40–70% | 1,521 | 63.1% | Proactive check-in — contract upgrade incentive |
| Low Risk | <40% | 392 | 16.3% | Standard service — monitor for changes in behavior |
| Annual revenue protected (30% retention) | ~$236,000 | |||
Krenz Analytics | IBM Telco Customer Churn Dataset | Diego Krenz, May 2026