From gtm-skills
Provides frameworks for customer success and retention: onboarding flows, health scoring, churn prevention, upsells, dunning, re-engagement, and LTV maximization.
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Comprehensive framework for customer success, retention, and lifetime value maximization.
Reduces SaaS churn with cancel flows, dynamic save offers, dunning for failed payments, and retention strategies. Use for voluntary/involuntary churn scenarios.
Reduces voluntary and involuntary SaaS churn with cancel flows, save offers, dunning, win-back tactics, and retention strategies. Use for rising cancellations, failed payments, or retention improvement.
Diagnoses churn, maps customer journeys, and designs upsells/cross-sells to maximize LTV and build recurring revenue using Hormozi frameworks. For subscription retention strategies.
Share bugs, ideas, or general feedback.
Comprehensive framework for customer success, retention, and lifetime value maximization.
| Situation | Use This Skill For |
|---|---|
| Designing onboarding flows | Onboarding Excellence |
| Reducing churn | Churn Prevention & Recovery |
| Building health monitoring | Health Score Models |
| Improving LTV | Retention & Ascension |
| Cancel flow optimization | Cancel Flow Design |
| Payment failures | Dunning & Recovery |
The faster users get value, the more likely they stick. Measure and optimize time to first value moment. Remove every obstacle between signup and aha moment.
Reach out before problems escalate. Health scores predict churn before it happens. Intervention when metrics dip is worth 10x intervention after cancellation request.
Not all customers are the same. High-touch for enterprise, tech-touch for SMB, self-serve for individuals. Match effort to customer value and needs.
Revenue is a lagging indicator. Track: engagement, feature adoption, support tickets, NPS changes.
Upselling should feel like helping, not selling. When customers outgrow their tier, expansion is a solution.
| Milestone | Target Time | D30 Retention Impact |
|---|---|---|
| Account created | T+0 | Baseline |
| Profile complete | T+5 min | +8% |
| First core action | T+24 hr | +15% |
| First value experience | T+3 days | +25% |
| 3-day active streak | T+7 days | +35% |
| Approach | Best For | Risk |
|---|---|---|
| Product-first | Simple products, B2C | Blank slate overwhelm |
| Guided setup | Products needing personalization | Friction before value |
| Value-first | Products with demo data | May not feel "real" |
| Dimension | Weight | Signals |
|---|---|---|
| Usage frequency | 25% | DAU/MAU ratio, sessions, last login |
| Feature depth | 20% | Feature adoption %, core feature use |
| Engagement | 20% | Time on app, actions per session |
| Satisfaction | 15% | NPS, CSAT, support sentiment |
| Growth | 10% | Seat additions, plan upgrades |
| Relationship | 10% | Community participation, referrals |
| Score | Status | Action |
|---|---|---|
| 80-100 | Healthy | Upsell opportunities |
| 60-79 | Stable | Monitor |
| 40-59 | At Risk | Automated intervention |
| 0-39 | Critical | Human outreach |
| Level | Score | Action |
|---|---|---|
| Low | 0-29 | Continue normal engagement |
| Medium | 30-49 | Automated re-engagement |
| High | 50-69 | Personalized intervention |
| Critical | 70+ | Human outreach (call/email) |
| Type | Cause | Solution |
|---|---|---|
| Voluntary | Customer chooses to cancel | Cancel flows, save offers, exit surveys |
| Involuntary | Payment fails | Dunning emails, smart retries, card updaters |
Voluntary churn is typically 50-70% of total. Involuntary is 30-50% but easier to fix.
| Signal | Risk Level | Timeframe |
|---|---|---|
| Login frequency drops 50%+ | High | 2-4 weeks before cancel |
| Key feature usage stops | High | 1-3 weeks before cancel |
| Support tickets spike then stop | High | 1-2 weeks before cancel |
| Billing page visits increase | High | Days before cancel |
| Team seats removed | High | 1-2 weeks before cancel |
| Data export initiated | Critical | Days before cancel |
| NPS score drops below 6 | Medium | 1-3 months before cancel |
| Trigger | Intervention |
|---|---|
| Usage drop >50% for 2 weeks | "We noticed you haven't used [feature]. Need help?" email |
| Approaching plan limit | Upgrade nudge |
| No login for 14 days | Re-engagement email with product updates |
| NPS detractor (0-6) | Personal follow-up within 24 hours |
Trigger → Survey → Dynamic Offer → Confirmation → Post-Cancel
| Reason | What It Tells You |
|---|---|
| Too expensive | Price sensitivity, may respond to discount |
| Not using it enough | Low engagement, may respond to pause/onboarding |
| Missing a feature | Product gap, show roadmap |
| Switching to competitor | Competitive pressure |
| Technical issues | Product quality, escalate to support |
| Temporary / seasonal | Usage pattern, offer pause |
| Cancel Reason | Primary Offer | Fallback Offer |
|---|---|---|
| Too expensive | Discount (20-30% for 2-3 months) | Downgrade |
| Not using | Pause (1-3 months) | Free onboarding |
| Missing feature | Roadmap preview | Workaround guide |
| Competitor | Competitive comparison + discount | Feedback session |
| Technical issues | Escalate to support | Credit + priority fix |
Pre-dunning → Smart retry → Dunning emails → Grace period → Hard cancel
| Decline Type | Retry Strategy |
|---|---|
| Soft decline | Retry 3-5 times over 7-10 days |
| Hard decline | Don't retry — ask for new card |
| Authentication required | Send customer to update payment |
| Timing | Content | |
|---|---|---|
| 1 | Day 0 | "Your payment didn't go through. Update your card." |
| 2 | Day 3 | "Quick reminder — update your payment." |
| 3 | Day 7 | "Your account will be paused in 3 days." |
| 4 | Day 10 | "Last chance to keep your account active." |
| Trigger | Condition | Channel | Max Frequency |
|---|---|---|---|
| Early dormancy | 3-7 days inactive | Push | 4×/month |
| Mid dormancy | 7-14 days inactive | 2×/month | |
| Onboarding drop | Incomplete onboarding | 3×/month | |
| Feature discovery | Unused high-value feature | In-app | 1×/month |
| Streak at risk | Streak expires in 6 hours | Push | As needed |
| Phase | Goal | Examples |
|---|---|---|
| Trigger | Create the cue | Push notifications, email digest |
| Action | Minimum viable behavior | One-click action, simple daily task |
| Variable Reward | Unpredictable value | Social recognition, progress unlocks |
| Investment | User commits something | Profile data, settings, connections |
LTV = (Average Revenue Per Customer × Average Customer Lifespan) - CAC
To maximize LTV:
Level 1: Entry Offer → Solves first problem
↓
Level 2: Core Offer → Deeper solution
↓
Level 3: Premium Offer → Advanced/faster results
↓
Level 4: Done-For-You → They pay you to do it
↓
Level 5: Ongoing Relationship → Retainer/subscription
| Metric | Formula | Target |
|---|---|---|
| Monthly churn rate | Churned / Start-of-month | <5% B2C, <2% B2B |
| Revenue churn (net) | (Lost MRR - Expansion) / Start MRR | Negative |
| Cancel flow save rate | Saved / Total cancel sessions | 25-35% |
| Dunning recovery rate | Recovered / Total failures | 50-60% |
| Time to cancel | Days from signal to cancel | Track trend |
Segment by:
├── Enterprise (high-touch)
│ ├── Dedicated CSM
│ ├── Custom success plans
│ └── Executive sponsors
├── Mid-market (mid-touch)
│ ├── Pooled CSM model
│ ├── Templated playbooks
│ └── Regular check-ins
└── SMB (tech-touch)
├── Automated journeys
├── Self-service resources
└── Trigger-based outreach