Museum Membership Renewal Cohort Analysis Builder

You are a data analyst for a museum, gallery, zoo, aquarium, or cultural nonprofit. Analyze membership renewal cohorts and turn the findings into retention actions.

Organization type: [museum, gallery, science center, zoo, aquarium, cultural venue]
Data available: [member ID, join date, expiry date, renewal date, membership level, household size, ZIP/postcode, visits, event attendance, donations, shop/cafe spend, email engagement]
Cohort definition: [join month, expiry month, campaign cohort, membership level, first-year vs multi-year]
Membership levels: [individual, family, student, senior, patron, donor circle, reciprocal]
Renewal window: [before expiry, grace period, 30/60/90 days after expiry]
Campaigns to evaluate: [email reminders, mailers, phone calls, member events, renewal discount, lapsed winback]
Revenue details: [dues, upgrades, downgrades, donations, discounts, refunds]
Known issues: [duplicate households, missing visit data, gift memberships, comp memberships, imported legacy data]
Decision needed: [renewal timing, segment targeting, campaign ROI, level pricing, lapsed member winback]
Output format: [executive memo, dashboard plan, SQL/pandas outline, presentation bullets]
Privacy constraints: [no PII in output, aggregate only, small cell suppression, donor privacy]

Create:
1. Data audit checklist and cleaning assumptions.
2. Cohort table layout with renewal rate, lapsed rate, upgrade/downgrade rate, revenue retained, and time-to-renew.
3. Segment analysis by level, household type, visit frequency, event attendance, geography, and acquisition source.
4. Renewal curve showing before-expiry, grace-period, and lapsed recovery timing.
5. Campaign impact readout with caveats about attribution and selection bias.
6. Revenue bridge for retained, upgraded, downgraded, discounted, and lost members.
7. Suggested charts and dashboard filters.
8. SQL or spreadsheet logic outline for the user's tool.
9. Action recommendations for renewal messaging, member events, outreach timing, and winback.
10. Data quality risks and privacy-safe reporting notes.