OTHER

Flag accounts whose product usage drops off a cliff

Each morning, compares every account's recent active-user count against its prior baseline and raises a Slack alert for any account whose usage fell sharply.

CategoryOther
Enginesim
Difficultybeginner
Triggerschedule
Steps5
Setup~5 min

How it runs

The automated pipeline, trigger to output.

  • TriggerDaily schedule (every morning)
  • ActionQuery 7-day vs 28-day active usage per accountPostgreSQLPostgres
  • LogicKeep accounts with >40% usage drop
  • ActionEnrich with plan tier, MRR, renewal datePostgreSQLPostgres
  • OutputPost ranked at-risk list to #customer-successSlack

What it does

This workflow detects the single loudest churn signal — a sudden drop in product usage — and routes at-risk accounts to the customer success team before the decline becomes a cancellation.

When to use it

Run it when you have a product-usage table (logins, active seats, or events per account) in Postgres and want a daily, no-dashboard-required heads-up on accounts going quiet. Ideal for B2B SaaS teams with monthly or annual renewals.

How it works

  1. 1A daily schedule fires the workflow each morning.
  2. 2A Postgres query pulls each account's active-user count for the last 7 days and the preceding 28-day baseline.
  3. 3A logic step computes the percentage drop and keeps only accounts down more than 40% versus baseline.
  4. 4A second Postgres lookup enriches each flagged account with its plan tier, MRR, and renewal date.
  5. 5A Slack message posts the ranked list to the #customer-success channel, highest-MRR accounts first, with the drop percentage and renewal date for each.

Set it up

What you configure once, before turning it on.

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

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