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AI agent for product analysts

Cohort Retention Report Agent

A correct, comparable monthly retention report with clear findings

Cohort Retention Report Agent: what goes in, what the agent does and what you get

What it does

Retention numbers drive big product decisions, so a small data error can send a team in the wrong direction. Each month this agent builds retention cohorts by signup week and by key segments such as channel, plan and first feature used. It applies the agreed active-user definition and excludes test and internal accounts. It then checks totals against the user table and the last report, and flags cohorts that changed after the fact. If numbers do not reconcile, it finds the cause, such as late-arriving events or a filter gap, and rebuilds. It writes findings: which cohorts improved, which segments retain best, and what changed after recent releases. The analyst reviews before sharing. Edge case: a cohort too small for a reliable rate is shown but greyed out.

How it works

Follow the arrows from top to bottom. The orange dashed arrow is the loop: when a check fails, the agent goes back and tries again.

Start and resultWhat it doesA check on its own workWaits for your OKGoes back and retries
Yes, continueApprovedNo 1 STARTS WHEN Monthly report run 2 USES A TOOL Query cohorts by signup week and segment 3 DOES Apply active definition and exclude internalaccounts 4 CHECKS THE RESULT Do totals reconcile with the user table and lastreport? If not: find late or missing events and rebuild. Back tostep 2. 5 DOES Compare cohorts and segments 6 USES A TOOL Draft report with findings 7 YOU APPROVE Analyst reviews before sharing 8 RESULT Report published
Read the steps as a list
  1. Monthly report run
  2. Query cohorts by signup week and segment
  3. Apply active definition and exclude internal accounts
  4. Do totals reconcile with the user table and last report?If not: find late or missing events and rebuild. Back to step 2.
  5. Compare cohorts and segments
  6. Draft report with findings
  7. Analyst reviews before sharingThe agent waits here for your OK.
  8. Report published

How it decides

It uses one fixed active-user definition and only calls out changes larger than normal cohort-to-cohort spread.

  • Cohorts under 200 users are greyed out
  • Exclude internal and test accounts
  • Changes must exceed normal spread to be called out

Make it yours

Every agent is a starting point. You choose these settings for your own situation.

  • Active user definition
  • Segments
  • Minimum cohort size
  • Report format

What keeps you in control

It always asks you first

  • Publishing the report

Hard limits

  • Never edits source data
  • Never changes the active definition without approval

It stops when

  • Done: report published
  • Stop: event data incomplete

Set it up

We guide you through the set-up, step by step

Members get the full set-up guide for this agent. No technical skills needed: you copy, paste and upload.

10 minto set it up in your AI
5 AIsChatGPT, Claude, Copilot, Gemini, Grok
  • One set of instructions to paste into your AI, with the clicks for ChatGPT, Claude, Microsoft 365 Copilot, Gemini and Grok
  • The agent then walks you through connecting your own data, one source at a time
  • A downloadable copy with the flow chart, the rules and the full guide
Get access to this agent

An example run

What happensIn the June report, week-4 retention for May cohorts showed 41%, up from 34%. The reconciliation check failed: 2,100 internal QA accounts were not excluded after a domain change. The agent fixed the filter and rebuilt. Retention was 35%, within the normal spread, so it reported no real change. The analyst approved the report.

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