Customer churn analysis
Identify why customers leave and where to intervene.
Most SaaS churn is preventable — it happens because teams don't see the warning signs. This diagram shows the churn funnel from the moment engagement drops: you notice, you send a campaign, the customer either responds or you discover a billing issue, support intervenes or doesn't, and the customer either renews or leaves.
Each box in the funnel is an intervention point. Missing engagement? Email the user. No response? Check if their payment method is expired. Payment failed? Send support. No fix? The customer churns. By mapping these paths, product teams spot where they're losing customers and where a small action — a re-engagement email, a billing reminder — prevents churn.
When to use this template
- Retention strategy planning — work backward from your churn reasons and design interventions for each path.
- Setting up churn alerts — this diagram becomes the ruleset for your monitoring: watch for low engagement, flag expired payment methods, track re-engagement response rates.
- Cross-team reviews — show product (engagement), marketing (campaigns), and billing (payment health) how their work feeds into one churn decision tree.
How to adapt it
Start by labeling the decision diamonds with your actual churn triggers: "Low API usage?", "Premium feature disabled?", "Support tickets open?". Then add your interventions:
- Add a feature-request gate — if customers request features you're building, send a roadmap update and measure if it reduces churn.
- Layer in discount offers — some teams add a "offer discount" node in the billing-failure path to recover at-risk renewals.
- Track time-to-churn — annotate the path with how many days pass between each decision so you know your window to intervene.
Visual edits regenerate clean code, so you can sketch interventions and A/B test which paths have the biggest churn impact.
Mermaid code
Copy it anywhere Mermaid is supported — GitHub, Notion, or your docs.
flowchart TD
A[Active subscription] --> B{Low engagement?}
B -->|Yes| C[Email re-engagement campaign]
C --> D{Responds?}
D -->|No| E{Payment fails?}
D -->|Yes| F[Return to usage]
B -->|No| G[Renewal approaching]
E -->|Yes| H[Send billing support alert]
E -->|No| I[Loss reason unknown]
H --> J{Issue resolved?}
J -->|Yes| K[Charge succeeds]
J -->|No| L[Churn]
G --> M{Renews?}
M -->|Yes| N[Retention]
M -->|No| L
F --> N
K --> N
Frequently asked questions
- What is a churn analysis diagram?
- It maps the decision tree a customer goes through before churning — engagement drops, a campaign runs, a payment fails, support reaches out. Each path represents an intervention point where your team can prevent churn. It makes the retention funnel and churn reasons visible in one view.
- Why show re-engagement campaigns and payment failures separately?
- Churn has multiple causes: customers forget about your product (engagement loop) or they want to cancel for budget reasons (billing loop). This diagram shows both paths so product, marketing, and billing teams see where their work impacts retention. Addressing only one ignores the other reason people churn.
- How do I measure if an intervention works?
- Annotate each edge with conversion rates: 'Email re-engagement — 15% respond', 'Payment retry — 60% resolve'. Then calculate the churn impact of each path. If 5% of active subscriptions go through the billing loop and 60% are saved, that loop prevents ~3% churn. Use the numbers to prioritize interventions.
- What metrics should I track alongside this diagram?
- NRR (Net Revenue Retention), time-to-churn (weeks from engagement drop to cancellation), intervention response rates (% who respond to re-engagement email), and per-cohort churn rate. Layer these onto the diagram so the team sees both the process and the numbers driving your retention story.