Business Problem — Customer Churn Analysis¶
Company Context¶
TelcoMax is a mid-size telecommunications company offering mobile, broadband, and streaming TV services in three UK regions. Monthly Revenue Recurring (MRR) is £4.2M, with 12,000 active customers.
The problem: The head of customer success has noticed that monthly churn (customers cancelling their contract) has risen from 5.1% six months ago to 8.2% this month. At this rate, TelcoMax will lose 30% of its customer base within a year.
The CFO has approved a £200,000 retention budget. Before spending it, the team needs to know:
- Who is churning? Which customer segments have the highest churn rate?
- Why are they churning? Which service features or interactions predict churn?
- When do they churn? Is there a critical window — a point in the customer journey where intervention is most effective?
- Which customers are at risk right now? Who should the retention team call this week?
Business Questions to Answer¶
Q1 — Overall Churn Landscape¶
- What is the current monthly churn rate?
- How has churn rate changed over the last 6 months?
- What is the revenue impact of current churn (MRR lost)?
Q2 — Customer Segmentation¶
- Do churn rates differ by contract type (month-to-month vs 1-year vs 2-year)?
- Do churn rates differ by service bundle (mobile-only vs broadband vs both)?
- Which tenure bucket has the highest churn? (< 6 months / 6-24 months / 24+ months)
- Do churn rates differ by payment method?
Q3 — Service and Behaviour Signals¶
- Do customers with more service add-ons churn less?
- Does having tech support or online security reduce churn?
- Do customers with paperless billing churn differently?
- How does monthly charge correlate with churn probability?
Q4 — At-Risk Customer Identification¶
- Which active customers show the same profile as recently churned customers?
- Can we build a simple churn score based on key features?
Success Metrics¶
| Metric | Current | Target |
|---|---|---|
| Monthly churn rate | 8.2% | < 5.0% |
| MRR lost to churn | £34,400/month | < £21,000/month |
| Retention intervention rate | 0% (reactive) | 40% of at-risk identified proactively |
| At-risk model recall | — | > 70% (catch 70% of actual churners) |
Stakeholders¶
| Stakeholder | Interest | What they need from the analysis |
|---|---|---|
| Head of Customer Success | Reduce churn | At-risk customer list, playbook for retention calls |
| CFO | ROI on £200k budget | Revenue impact, cost per retained customer |
| Product Manager | Feature adoption | Which features reduce churn, what to build next |
| Marketing | Campaign targeting | Segments with highest churn propensity for win-back campaigns |