This Cohort Report Will Change How You See Growth
Cohort reports group users by signup week (or month) and track behavior over time. They answer the question aggregate metrics can't: are newer users retaining better than older ones? US teams that add cohort analysis often discover their "growth" was masking a retention problem.**
Growth can be an illusion. MAU goes up. Signups increase. Revenue grows. Everything looks good.
Then you run a cohort report. You see that Week 4 retention has been flat, or declining, for months. Your "growth" is just acquisition. You're on a treadmill. The moment you stop adding users, the numbers collapse.
Cohort reports change how you see growth. They separate acquisition from retention. They show whether your product is getting better or you're just adding more users who leak out the bottom.
What a Cohort Report Shows
The Basic Structure
| Cohort (Week) | Week 0 | Week 1 | Week 2 | Week 3 | Week 4 | |---------------|--------|--------|--------|--------|--------| | Feb 3 (n=500) | 100% | 42% | 31% | 25% | 21% | | Feb 10 (n=520) | 100% | 45% | 34% | 28% | - | | Feb 17 (n=480) | 100% | 48% | 38% | - | - |
Each row is a signup cohort. Each column is a subsequent week. The number is % of that cohort who returned. Reading across: of the Feb 3 cohort, 42% came back in Week 1, 31% in Week 2, and so on. Reading down: are newer cohorts retaining better? If Feb 17 has 48% Week 1 vs. Feb 3's 42%, your product is improving.
What You Learn
- Retention trend: Are newer cohorts better? If yes, product improvements are working.
- Retention floor: Does retention eventually flatten? If yes, you have a stable "sticky" base.
- Retention cliff: Does a specific week show a drop? Trial end? Paywall? Bug?
- Scale vs. quality: Are you adding volume or adding retention? Cohort reports tell you.
The Growth Illusion
Scenario 1: The Treadmill
- Month 1: 1,000 signups, 200 retained
- Month 2: 1,200 signups, 240 retained
- Month 3: 1,400 signups, 280 retained
MAU is "growing." But if each cohort retains at 20%, you're just adding more users who churn at the same rate. The moment acquisition slows, growth stalls. Cohort report makes this obvious: flat retention across cohorts.
Scenario 2: Real Improvement
- Jan cohort: 35% Week 4 retention
- Feb cohort: 42% Week 4 retention
- Mar cohort: 48% Week 4 retention
Each newer cohort retains better. Your product is improving. Acquisition + improving retention = compound growth. Cohort report confirms it.
Scenario 3: Hidden Degradation
- MAU is up (acquisition increased)
- Cohort report: Week 4 retention dropped from 40% to 28%
You're adding users faster, but they're sticking less. Quality is degrading. Without cohorts, you'd miss it. With them, you know to fix the product before scaling acquisition.
How to Run Cohort Reports
What You Need
- User identity (consistent across sessions)
- Signup or first event date (to define cohorts)
- Return event (any event = "returned" for retention)
Tools
SingleAnalytics generates cohort reports automatically. Define cohorts by first event. Any subsequent event = return. Filter by source, device, activation. The report updates as new data flows in.
Best Practices
- Weekly cohorts for fast-moving products, monthly for slower cycles
- Segment by acquisition source: do paid cohorts retain like organic?
- Compare retention of activated vs. non-activated users
- Watch the curve: does it flatten? That's your "natural" retention floor
Real Impact
A US startup saw MAU growing 15% month-over-month. Leadership was happy. The product team ran cohort reports. They found: Week 4 retention had dropped from 38% to 25% over 6 months. They were adding users faster, but each cohort was sticking less. Growth was masking a retention crisis.
They paused acquisition spend. Fixed onboarding. Improved activation. Retention improved. Then they scaled again. The cohort report had saved them from scaling a leaky bucket.
Ready to see growth for what it really is? Run cohort reports with SingleAnalytics and change how you think about your numbers.