1. Churn Data Collection

1. Ask the user for their current churn metrics—monthly churn rate, total churned customers, and revenue lost in last 3-6 months.
   • Example: "What's your monthly churn rate percentage, how many customers canceled recently, and how much MRR/ARR did you lose?"
2. Ask the user about cancellation reasons—do you collect exit feedback, conduct surveys, or track stated reasons?
   • Example: "Do you know why customers cancel—exit survey data, support tickets, cancellation reason tracking, or anecdotal feedback?"
3. Ask the user about different customer segments—does churn vary by plan tier, customer size, industry, acquisition channel, or tenure?
   • Example: "Is churn evenly distributed or higher in certain segments—free-to-paid users, specific plan tiers, industries, or new vs. long-term customers?"
4. Ask the user about customer health indicators before churn—usage patterns, support tickets, feature adoption, payment issues.
   • Example: "What signals appear before cancellation—declining login frequency, low feature usage, unresolved support issues, failed payments, or complaints?"

2. Churn Segmentation Analysis

Break down churn by multiple dimensions:

By Cancellation Reason:

• Price too high / budget constraints
• Not using enough / low engagement
• Missing features / functionality gaps
• Switched to competitor
• Poor support experience / bugs
• Achieved goal / temporary need
• Payment failures (involuntary churn)

Calculate % of churned customers and lost revenue per reason.

By Customer Segment:

• Plan tier (Starter vs. Pro vs. Enterprise)
• Company size (solo, small team, mid-market, enterprise)
• Tenure (churned in first 30/60/90 days vs. long-term customers)
• Acquisition channel (paid ads, organic, referral, sales-led)

Identify high-churn segments that need targeted retention strategies.

By Customer Lifecycle Stage:

• Onboarding churn (first 30 days): Setup friction, poor first experience
• Early-stage churn (30-90 days): Failed to reach activation or see value
• Mid-stage churn (3-12 months): Unmet expectations or better alternatives
• Late-stage churn (12+ months): Outgrew solution or needs changed

3. Revenue Impact Quantification

Calculate the true cost of churn:

Direct Revenue Loss:

• Monthly lost MRR from churned customers
• Annualized ARR impact
• Projected lifetime value lost per churned customer

Opportunity Cost:

• Acquisition cost wasted (CAC for churned customers was spent but not recovered)
• Potential expansion revenue lost (churned customers never upsold)
• Referral value lost (they won't refer others)

Retention ROI Modeling:

• If you reduce churn by 10/20/30%, what's the revenue impact?
• What's the break-even investment in retention initiatives?
• Calculate: "Every 1% churn reduction = $X additional annual revenue"

Show scenarios:

• Current state: X% churn = $Y annual revenue loss
• If we reduce churn to X-5%: Save $Z annually
• If we reduce churn to X-10%: Save $Z*2 annually

4. Root Cause Identification

For top 3-5 churn reasons, dig deeper:

Price/Budget Concerns:

• Are customers churning to cheaper alternatives or stopping entirely?
• Is value perception the issue or actual affordability?
• Does pricing structure misalign with usage patterns?

Low Engagement/Usage:

• Did customers complete onboarding?
• Which key features indicate activation—are churners missing these?
• Do they lack time, knowledge, or motivation to use product?

Missing Features:

• Are feature requests consistent across churners?
• Are these must-haves or nice-to-haves?
• Do competitors offer these features?

Competitor Switching:

• Which competitors are winning your customers?
• What do they offer that you don't?
• Is it features, pricing, service, or something else?

5. Retention Strategy Recommendations

Provide actionable fixes prioritized by impact potential:

Quick Wins (30-60 days):

• Fix involuntary churn: Update payment retry logic, dunning emails
• Improve onboarding: Simplify setup, add activation checkpoints
• Proactive support: Reach out to at-risk customers showing churn signals

Strategic Initiatives (90-180 days):

• Build missing features driving competitive losses
• Create pricing tiers that better match customer segments
• Implement customer success program for high-value segments

Long-term Programs:

• Predictive churn modeling: Score customers by churn risk, intervene early
• Product-led retention: In-app guidance, usage nudges, value showcases
• Community building: Create customer engagement beyond product usage

For each recommendation:

• Expected churn reduction (%) and revenue saved
• Implementation effort and timeline
• Success metrics to track

Present complete churn analysis report with:

• Executive summary of key findings
• Detailed churn breakdown by reason and segment
• Revenue impact quantification
• Root cause analysis
• Prioritized retention strategies
• 90-day action plan to reduce churn

Invite discussion on findings, especially if data reveals surprising patterns or difficult trade-offs.