What is Retention Rate?
Retention rate measures the percentage of users who return to your app on a specific day after installation. D1 retention means returning on day 1, D7 means day 7, and so on. It's the fundamental metric that determines whether your app can sustain growth.
Retention Formula
Why Retention is King
Retention is the most important metric because it:
- Determines LTV ceiling (low retention = low LTV)
- Affects CAC payback period
- Indicates product-market fit
- Drives organic growth through engaged users
- Compounds—small improvements have massive impact
Retention Benchmarks by Category
| App Category | D1 | D7 | D30 |
|---|---|---|---|
| Hyper-Casual Games | 30-35% | 8-12% | 2-4% |
| Casual Games | 35-45% | 15-20% | 5-8% |
| Midcore Games | 30-40% | 12-18% | 4-7% |
| Social Apps | 35-50% | 20-30% | 10-15% |
| E-commerce | 20-30% | 10-15% | 5-8% |
| Fitness/Health | 25-35% | 15-22% | 8-12% |
Understanding the Retention Curve
Early Drop-off (D0-D1)
Biggest drop happens immediately. Users who don't return on D1 rarely come back. Focus on first session experience.
Flattening Phase (D7-D30)
Curve should flatten as you reach core users. Steep continued decline indicates fundamental issues.
Long-term Plateau (D30+)
Surviving users become stable core audience. These users drive LTV and should be your focus for monetization.
The 40-20-10 Rule
A healthy consumer app typically shows 40% D1, 20% D7, and 10% D30 retention. Games often see lower D30 due to content exhaustion. Social apps with network effects can exceed these significantly.
Improving Retention
- Optimize onboarding: First session determines D1
- Create daily habits: Daily rewards, streaks, notifications
- Deliver core value fast: "Aha moment" within minutes
- Progressive engagement: Unlock features over time
- Social features: Friends increase retention 2-3x
- Smart notifications: Re-engage without annoying
Retention Analysis Best Practices
- Segment by acquisition source (organic vs. paid)
- Analyze by user cohort, not aggregate
- Track both classic and rolling retention
- Combine with behavioral data
- A/B test retention features