CRM

HubSpot Duplicate Merge Guardian with Field-Survivorship Review Queue

Detects likely-duplicate HubSpot contacts, builds a field-by-field survivorship proposal (which value wins per field).

CategoryCRM
Enginesim
Difficultyintermediate
Triggerevent
Steps6
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerHubSpot contact created or updatedHubSpotHubSpot
  • ActionSearch HubSpot for duplicate candidates by email, phone, nameHubSpotHubSpot
  • LogicBranch: exit if no strong match, else build survivorship proposal
  • ActionPost per-field merge proposal to Slack review queueSlack
  • ActionOn approval, call HubSpot merge APIHubSpotHubSpot
  • OutputLog surviving record and merge decision

What it does

It watches HubSpot for newly created or updated contacts, finds probable duplicates, and turns the messy merge decision into a clean approval. Instead of auto-merging and silently destroying data, it produces a per-field survivorship proposal and routes it to a human queue.

When to use it

Use it when your team imports lists or captures leads from multiple sources and you want clean records without risking data loss from a blind auto-merge. Ideal for RevOps teams that need an audit trail for every merge decision.

How it works

  1. 1A new or updated HubSpot contact fires the trigger.
  2. 2The flow searches HubSpot for matches on normalized email, phone, and name to find duplicate candidates.
  3. 3A logic step branches: if no strong match, it exits quietly; if matches exist, it continues.
  4. 4For each conflicting field (name, title, owner, lifecycle stage), it picks a winner using recency and completeness rules and assembles a survivorship proposal.
  5. 5The proposal posts to a Slack channel with Approve/Reject actions and a clear before/after diff.
  6. 6On approval the flow calls the HubSpot merge API and logs the surviving record.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect HubSpotCRM, deals, marketing, support.
  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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