abanoub-ashraf/indie-app-analytics

Indie App Analytics Skill

Analytics and metrics framework for indie iOS/macOS developers. Use this skill when the user wants to understand app metrics, set up analytics, interpret retention data, calculate LTV/CAC, perform cohort analysis, or make data-driven decisions about their indie app.

When to Use This Skill

Trigger on phrases like "analytics setup", "track metrics", "retention rate", "LTV calculation", "churn rate", "cohort analysis", "user engagement", "DAU/MAU", "conversion funnel", "which metrics should I track", or any questions about measuring app performance.

Core Metrics Framework

Revenue Metrics

Lifetime Value (LTV): The total revenue you expect from a single customer over their entire relationship with your app.

LTV = ARPU × Gross Margin ÷ Churn Rate

For subscription apps:

LTV = Average Monthly Revenue Per User × Average Customer Lifespan (months)

Customer Acquisition Cost (CAC): Total cost to acquire a new paying customer.

CAC = Total Marketing Spend ÷ New Customers Acquired

LTV:CAC Ratio Benchmarks:

• Below 1:1 = Losing money on every customer (unsustainable)
• 1:1 to 2:1 = Inefficient, barely breaking even
• 3:1 = Healthy target for sustainable growth
• 5:1+ = May be underinvesting in growth

CAC Payback Period: Time to recover acquisition cost. Target under 12 months.

CAC Payback = CAC ÷ Monthly Revenue Per Customer

Monthly/Annual Recurring Revenue (MRR/ARR):

MRR = Number of Active Subscribers × Average Revenue Per Subscriber
ARR = MRR × 12

Retention Metrics

Churn Rate: Percentage of users who stop using your app or cancel subscriptions.

Monthly Churn = (Users at Start - Users at End) ÷ Users at Start × 100

Benchmarks for subscription apps:

• Excellent: <1% monthly churn
• Good: 1-3% monthly churn
• Acceptable for early startups: 3-5% monthly churn
• Concerning: >5% monthly churn

Retention Rate Benchmarks (2025):

Day 1 (D1) Retention:

• Typical: 25-40%
• Exceptional: 35%+
• Gaming apps: 45%+

Day 7 (D7) Retention:

• iOS average: 6.89%
• Android average: 5.15%
• Gaming apps: 20%+

Day 30 (D30) Retention:

• iOS average: 3.10%
• Android average: 2.82%
• Gaming apps: 10%+
• Overall average: 6%

Day 90 (D90) Retention:

• Good: 10-30%

Subscription Retention by Plan Type:

• Yearly plans: 44-47% retention at 12 months
• Monthly plans: 17-18% retention at 12 months
• Weekly plans: <6.5% retention (function as trials, not sustainable long-term)

Engagement Metrics

DAU/MAU Ratio (Stickiness): Measures how often users return.

Stickiness = Daily Active Users ÷ Monthly Active Users × 100

Benchmarks:

• Below 10% = Low engagement, users visit rarely
• 10-20% = Average engagement
• 20-30% = Good engagement
• Above 30% = Strong engagement, highly sticky product
• 50%+ = Exceptional (social apps, daily utilities)

Session Metrics:

• Sessions per user per day
• Average session duration
• Time between sessions

Conversion Metrics

Trial-to-Paid Conversion: Varies significantly by category.

Category benchmarks (2025):

• Travel apps: 48.7%
• Media/Entertainment: 43.8%
• Health & Fitness: 25-35%
• Productivity: 20-30%
• Overall average: 15-25%

Key insights:

• 80%+ of trial conversions happen on Day 0 (first day)
• Higher prices often correlate with higher trial conversion (9.8% vs 4.3% for low prices)
• Early cancellations (within minutes) indicate "free sample" seekers
• 10%+ of churned monthly subscribers re-subscribe within 12 months

Cohort Analysis

Cohort analysis groups users by a shared characteristic (usually signup date) to track behavior over time.

Setting Up Cohorts

By Install Date: Track how users acquired in week 1 behave differently from week 2, etc.

By Acquisition Source: Compare organic vs paid users, or different ad campaigns.

By Plan Type: Monthly vs yearly subscribers often have very different retention curves.

By Onboarding Completion: Users who complete onboarding vs those who don't.

Minimum Sample Sizes

• At least 30 users per cohort for statistical validity
• Ideally 100+ users for confident conclusions
• Watch for seasonality effects when comparing cohorts across different time periods

What to Look For

• Do newer cohorts retain better? (Product improvements working)
• Which acquisition sources produce highest-LTV users?
• At what point do users typically churn? (Identify "danger zones")
• Does onboarding completion predict long-term retention?

Analytics Tools for Indie Developers

Revenue & Subscription Analytics

RevenueCat (Recommended for subscriptions):

• Subscription-specific: MRR, ARR, churn, trial conversion
• Real-time dashboards
• Cross-platform (iOS, Android, web)
• Free tier for <$2,500 MTR
• Integrates with most analytics tools

Product & Behavior Analytics

PostHog (Open-source, privacy-friendly):

• Event tracking and funnels
• Cohort analysis and retention dashboards
• Feature flags for A/B testing
• Self-hosted option available
• Generous free tier

Mixpanel:

• User behavior and funnel analysis
• Excellent cohort analysis
• Good for understanding user journeys
• Free tier available

Amplitude:

• Product optimization focus
• Machine learning insights
• Identifies users at risk of churning
• Enterprise pricing can be high

Platform-Native Analytics

App Store Connect Analytics:

• Downloads, impressions, conversion rate
• User acquisition sources
• Crash reports
• Free, built into Apple's platform

Firebase Analytics:

• Event tracking
• User properties
• Integrates with Google ecosystem
• Free for most use cases

Attribution & ROI

Singular:

• Attribution tracking
• ROI measurement
• Fraud prevention
• Enterprise-focused

Implementation Checklist

Phase 1: Foundation (Week 1)

1. Set up RevenueCat for subscription tracking (if applicable)
2. Implement basic event tracking:
   • App launch
   • Key feature usage
   • Paywall views
   • Purchase events
3. Track user properties:
   • Install date
   • Acquisition source
   • Device type

Phase 2: Retention Focus (Week 2)

4. Set up retention cohort tracking
5. Identify and track "aha moment" events (when users discover core value)
6. Create funnel for onboarding completion
7. Set up churn event tracking

Phase 3: Revenue Optimization (Week 3+)

8. Track trial start/conversion events
9. Set up LTV calculation
10. Create dashboard for key metrics:
    • Daily: Active users, new trials, revenue
    • Weekly: Retention by cohort, conversion rates
    • Monthly: LTV, CAC, churn trends

Key Insights for Indie Developers

What Actually Matters

For pre-revenue apps:

• Focus on D1 and D7 retention first
• Track which features correlate with retention
• Don't overthink metrics—ship and iterate

For revenue-generating apps:

• LTV:CAC ratio is your north star
• Monitor churn rate weekly
• Segment users by engagement level

Common Mistakes

• Tracking too many events (leads to analysis paralysis)
• Not setting up analytics before launch
• Ignoring qualitative feedback in favor of pure numbers
• Comparing your metrics to VC-funded companies

Quick Wins

• Users who complete onboarding retain 2-3x better
• Yearly plans have 2-3x better retention than monthly
• Push notification opt-in correlates with higher retention
• Users active in first 24 hours are most likely to convert

References

• RevenueCat State of Subscription Apps 2025
• Mixpanel Product Benchmarks 2025
• PostHog Startup Metrics Guide
• App Store Connect Analytics Documentation