Analyze user retention by cohort

Analyze user retention and engagement by cohort

Measuring product retention and engagement trends by user cohort to guide onboarding improvements and feature prioritization.

• · CSV/spreadsheet (user_id, signup_date, activity_date, event_type)
• · Or: description of analysis needed (channel, plan tier, feature)

• · Cohort retention table (markdown + CSV)
• · Retention curves by cohort
• · Key findings (best/worst cohort, trend, benchmarks)
• · Recommendations + follow-up SQL queries

• · Python (pandas) for cohort table generation
• · SQL (optional, if data integration needed)

• · User-level data with signup_date + activity_date
• · Cohort definition chosen (week/month/channel/tier)
• · Retention event defined (login/core action/purchase)

• · Cohort definition too vague → results hard to interpret
• · Early cohorts may look different (founder bias)
• · Seasonal effects can masquerade as trends
• · Incomplete data (missing sign-ups or activities) skews retention

• · Pandas-based cohort table generation
• · Retention curve visualization
• · By-cohort comparison (best/worst/stable)
• · Benchmark comparisons
• · Follow-up SQL templates for deeper investigation