Cohort Retention Analysis — User Lifecycle

Perform a cohort-based retention analysis for [product/app].

**Data available:**
[describe your data: user signups, events/actions, timestamps, user properties]

**Analysis deliverables:**

1. **Cohort table**: Weekly or monthly cohorts showing % retained at Day 1, 7, 14, 30, 60, 90
2. **Retention curve**: Describe the shape — is there a "cliff" or gradual decay? Where does it flatten?
3. **Best vs worst cohorts**: What's different? (seasonality, feature launches, channel mix)
4. **Churned user profile**:
   - What did churned users NOT do that retained users did?
   - Time to first value action (retained vs churned)
   - Feature usage patterns
5. **Activation metric validation**:
   - Which early action best predicts Day 30 retention?
   - Suggested "aha moment" definition
6. **Intervention strategies** (3):
   - Timing: when to intervene (which day/hour)
   - Channel: email, push, in-app, human outreach
   - Message: what to say/show
7. **SQL/Python code** to generate the cohort table from raw event data

**Retention target**: [what's the current D30 retention and what's the goal?]
**Product type**: [B2B SaaS / Consumer app / Marketplace]