MARKETING

Sync Engagement-Decay Subscribers Into a HubSpot Suppression List

Twice weekly, identifies subscribers whose combined open and click engagement has decayed past a churn threshold in BigQuery and adds them to a HubSpot active list so marketing…

CategoryMarketing
Enginesim
Difficultyadvanced
Triggerschedule
Steps5
Setup~25 min

How it runs

The automated pipeline, trigger to output.

  • TriggerTwice-weekly schedule
  • ActionPull recent open/click activity per subscriberGoogle BigQueryBigQuery
  • LogicScore engagement and flag decayed subscribers
  • LogicDiff flagged set against current list membership
  • OutputSync additions and removals to HubSpot listHubSpotHubSpot

What it does

This workflow keeps a HubSpot list continuously in sync with who is going cold. It computes a blended engagement score per subscriber from recent open and click behavior in BigQuery, identifies those whose score has decayed below your churn threshold, and pushes them into a designated HubSpot list. From there, your existing HubSpot automation can reduce send frequency or enroll them in a recovery sequence — no manual exports.

When to use it

Use it when HubSpot is your system of record for campaigns and you want decay signals to drive list membership automatically. Useful for protecting deliverability by quieting sends to disengaged contacts before they hurt your sender reputation.

How it works

  1. 1A twice-weekly schedule starts the run.
  2. 2BigQuery returns each subscriber's recent open and click activity over the scoring window.
  3. 3A logic step computes a blended engagement score and flags those past the decay threshold.
  4. 4A logic step diffs the flagged set against current list membership to find additions and removals.
  5. 5Flagged subscribers are added to the HubSpot active list, and recovered ones are removed, keeping the list accurate.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect BigQueryDatasets, queries, schemas.
  2. 2
    Connect HubSpotCRM, deals, marketing, support.
  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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