What it does
Queries Amplitude for cohort retention metrics, creates charts, and uses AI to explain what changed, why it matters, and which experiments to try next.
Why I recommend it
Everyone talks about retention but few teams review it regularly. Automating the analysis ensures you spot churn issues early and celebrate improvements.
Expected benefits
- Consistent visibility into WAU/MAU retention
- Actionable commentary instead of raw charts
- Faster experimentation decisions
- Historical archive for board decks and fundraising
How it works
Scheduled job runs Amplitude cohort query (by signup month, plan, or persona) -> fetch data/PNG charts -> Claude writes summary (top deltas, hypotheses, suggested actions) -> package emailed to stakeholders + stored in Notion with trendline.
Quick start
Export a cohort table manually and drop it into Claude asking for “3 insights + actions.” Use the feedback to tune prompts before building the recurring automation.
Level-up version
Segment by geography or pricing plan, pull in qualitative signals (NPS, support tickets), tie to lifecycle messaging, and alert owners when a cohort falls below SLA thresholds.
Tools you can use
Analytics: Amplitude, Mixpanel, Heap
Automation: Zapier, Workato, Airflow
Docs: Notion, Coda, Google Slides
AI: Claude
Also works with
E-commerce repeat purchase cohorts, SaaS onboarding funnels, marketing attribution cohorts.
Technical implementation solution
- No-code: Amplitude scheduled export -> Google Sheet -> Apps Script -> Claude summary -> email + Notion update.
- API-based: Airflow DAG -> Amplitude Export API -> Python + Claude -> PDF deck stored in Drive, Slack digest posted.
Where it gets tricky
Ensuring cohorts remain consistent when product analytics schemas change, handling very large datasets without timeouts, and giving enough context so AI commentary is trustworthy and not repetitive.
