MARKETING

Weekly AI Cohort Churn Brief With Recommended Actions

Each Monday, an agent reads cohort open/click decay from BigQuery, writes a plain-English brief explaining which cohorts are at risk and why, recommends a specific play per cohort.

CategoryMarketing
Enginepaperclip
Difficultyadvanced
Triggerschedule
Steps6
Setup~25 min

How it runs

The automated pipeline, trigger to output.

  • TriggerMonday weekly schedule
  • ActionQuery cohort open/click trendsGoogle BigQueryBigQuery
  • LogicRank cohorts by risk and infer causes
  • LogicDraft recommended play per at-risk cohort
  • ActionPublish full brief to NotionNotionNotion
  • OutputPost top-risk summary to SlackSlack

What it does

This is an analyst-style workflow, not just a threshold alert. An agent pulls per-cohort open and click trends from BigQuery, interprets which cohorts are decaying and how fast, and produces a written brief: who is at risk, the likely pattern (e.g., a content shift that lost a recent cohort), and a recommended action per cohort such as a subject-line test or a pause. The brief is published to Notion for the record and summarized to Slack for visibility.

When to use it

Use it when raw flags aren't enough and you want narrative judgment — prioritization and a recommended next step — delivered weekly to a growth or lifecycle lead who has to decide where to spend effort.

How it works

  1. 1A Monday schedule triggers the agent.
  2. 2The agent queries BigQuery for open and click trends grouped by cohort and recent sends.
  3. 3It reasons over the trends to rank cohorts by churn risk and infer probable causes.
  4. 4It drafts a brief with a recommended play for each at-risk cohort.
  5. 5The full brief is created as a Notion page.
  6. 6A short summary with the top risks is posted to Slack linking the Notion page.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect BigQueryDatasets, queries, schemas.
  2. 2
    Connect NotionPages, databases, comments.
  3. 3
    Connect SlackChannels, DMs, threads, mentions.
  4. 4
    Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
  5. 5
    Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
  6. 6
    Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.

Run this workflow in your colony.

14-day trial. No DevOps. No Sales call. Provisioned in under a minute.