Skill: ivangdavila/retention (version 1.0.0)

--- name: Retention description: User retention strategy, cohort analysis, churn prevention, and reactivation campaigns metadata: category: product skills: ["retention", "churn", "cohorts", "engagement", "lifecycle"] --- ## Core Metrics | Metric | Formula | Healthy Range | |--------|---------|---------------| | Day 1 retention | Users active day 1 / signups | 40-60% | | Day 7 retention | Users active day 7 / signups | 20-35% | | Day 30 retention | Users active day 30 / signups | 10-20% | | Weekly retention | WAU this week / WAU last week | 85-95% | | Churn rate | Lost customers / start customers | <5%/month | | NRR (Net Revenue Retention) | (Start MRR + expansion - churn) / Start MRR | >100% | ## Cohort Analysis Track by signup week, not calendar week: - **Horizontal axis**: weeks since signup (0, 1, 2, 3...) - **Vertical axis**: signup cohort (Jan W1, Jan W2...) - **Cell value**: % of cohort still active Identify: - Which cohorts retain better (product changes, marketing source) - At which week users drop off (week 2 cliff = aha moment too late) - Seasonal patterns (holiday signups retain worse) ## Churn Signals Early warning indicators (flag before churn): - Login frequency drops 50%+ from baseline - Core feature usage stops - Support tickets spike then go silent - Billing page visits without upgrade - Team member removals - Data export requests ## Engagement Loops Retention requires habit formation: | Loop Type | Trigger | Action | Reward | |-----------|---------|--------|--------| | Personal | Email digest | Review updates | Progress visible | | Social | Notification | Respond to team | Recognition | | Content | New content alert | Consume | Knowledge gained | | Progress | Streak reminder | Complete task | Streak maintained | Design for variable rewards - predictable = boring. ## Lifecycle Stages | Stage | Timeframe | Goal | Tactics | |-------|-----------|------|---------| | Activation | Day 0-3 | Reach aha moment | Onboarding, setup wizard | | Engagement | Week 1-4 | Build habit | Usage nudges, tips | | Retention | Month 1+ | Maintain value | Feature discovery, check-ins | | Expansion | Ongoing | Increase usage | Upsell, team invites | | Reactivation | After churn | Win back | Campaigns, incentives | ## Reactivation Campaigns Timing matters: - **7 days inactive**: Soft nudge ("We miss you") - **14 days inactive**: Value reminder + what's new - **30 days inactive**: Incentive offer (discount, extended trial) - **90 days inactive**: Last chance + feedback ask Message formula: ``` [Acknowledge absence] + [New value added] + [Easy re-entry CTA] "Your dashboard is waiting. We added [feature]. One click to resume →" ``` ## Feature Stickiness Measure which features predict retention: - **Usage correlation**: Users of feature X retain 2x better - **Time to feature**: Users who reach feature X in day 1 retain 3x - **Feature breadth**: Users of 3+ features retain 5x vs 1 feature Double down on sticky features in onboarding. ## Churn Prevention When churn signal detected: 1. **Immediate**: In-app message acknowledging drop ("Need help?") 2. **Day 3**: Email from founder (personal, not marketing) 3. **Day 7**: Offer call or live support 4. **Before renewal**: Proactive outreach with usage summary Cancel flow optimization: - Ask reason (required, 4-5 options) - Offer pause instead of cancel - Show what they'll lose (data, history, price lock) - Easy return policy ("reactivate anytime, data saved 90 days") ## Retention Benchmarks by Model | Business Model | Good D30 | Good Monthly Churn | |----------------|----------|-------------------| | B2C freemium | 10-15% | N/A (free) | | B2C subscription | 8-12% | 5-7% | | B2B SMB | 15-25% | 3-5% | | B2B Enterprise | 25-40% | 1-2% | ## Common Mistakes - Measuring retention from signup, not activation - Treating all churned users the same (voluntary vs involuntary) - Reactivation emails without new value proposition - Ignoring payment failures as churn (30-40% of churn is involuntary) - No segmentation in cohort analysis (power users mask problems)


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)