Telecom Intelligence
Churn & Retention
Churn rates, at-risk segments and retention programme effectiveness.
Executive summary
Churn rose for the fourth consecutive month, concentrated in high-value urban prepaid following competitor promotions. Save rates are improving but not offsetting volume.
Key indicators
Involuntary churn
1%
0ppvs prior month
Save rate
34%
+4ppvs prior month
Issues requiring attention
High-value urban prepaid churn up 0.5pp in 30 days
high priorityUSD 6.8M revenue at risk (annualised scope not independently confirmed)
Owner: Head of Retention
Drill downCompetitor 2x data offer
high priorityUrban port-outs +22% vs 30-day average.
Owner: Head of Retention
Drill downCongestion-driven churn
medium priorityTop churn cells overlap with congested sites.
Owner: CTO
Drill downPerformance analysis
Monthly churn (%)
Monthly actuals, Apr–Sep
Churn reasons (%)
Source unavailable — this breakdown has no stored record.
Actual vs prior and target
Current period, KPIs measured in %
Monthly churn trend
Monthly churn by month, Apr–Sep (%)
AI Advisory
- Prioritise capacity in top-20 churn cells
- Targeted retention bundle for at-risk high-value users
Value realization
| Metric / outcome | Value type | Baseline → target KPI | Expected | Actual | Variance | Realization | Status |
|---|---|---|---|---|---|---|---|
High-value churn reduction FY2026 H2 · Head of Retention | Revenue protected | 3.2 → 2.6 KPI for: High-value churn reduction | USD 2.1MConditional projection · Method unavailable | USD 780kLegacy recorded amount — excluded from current reporting | Not verified | Not verified | At risk |
Evidence
48k high-value subscribers scored above 60% churn propensity.
Source: CRM (illustrative model output)
Methodology
- Segment churners by value, region and tenure
- Correlate churn with network and competitor signals
- Score base for churn propensity