MARKETING

Bounce-Rate Spike Detector with Auto-Pause

Checks each active email sequence's rolling bounce rate every hour, and when a sequence crosses your hard-bounce threshold it automatically pauses sending and alerts the growth…

CategoryMarketing
Enginesim
Difficultyintermediate
Triggerschedule
Steps5
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerHourly schedule fires
  • ActionQuery bounce rate per active sequencePostgreSQLPostgres
  • LogicFilter sequences over bounce threshold
  • ActionSet offending sequences to pausedPostgreSQLPostgres
  • OutputAlert deliverability channel in SlackSlack

What it does

This workflow watches the hard-bounce rate of every active outbound sequence and acts the moment one goes bad. Instead of finding out at the end of a campaign that you torched your sender reputation, it pauses the specific sequence within the hour and tells the team exactly which one and why.

When to use it

Run this when you send sequenced cold or lifecycle email and store send/bounce events in Postgres. It is the safety net for list-quality regressions: a stale import, a bad enrichment batch, or a typo-heavy form fill that suddenly spikes invalid addresses.

How it works

1. An hourly schedule fires the check. 2. A Postgres query computes hard-bounce rate per active sequence over the trailing 1,000 sends. 3. A logic step filters to sequences exceeding the configured threshold (default 4%). 4. For each flagged sequence, a Postgres update sets its status to paused so no further sends go out. 5. A Slack message posts the sequence name, bounce rate, sample size, and a pause-confirmation to the deliverability channel. If no sequence breaches the threshold, the run ends silently with no noise.

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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