CRM
Airtable Staging Table Batch Dedupe with Manual Survivorship Review
On a nightly schedule, clusters duplicate contacts in an Airtable CRM table, writes one survivorship-resolved candidate row per cluster into a staging table.
How it runs
The automated pipeline, trigger to output.
- TriggerNightly schedule
- ActionRead all contacts from Airtable CRM tableAirtable
- LogicCluster duplicates and keep groups with 2+ members
- ActionWrite survivorship candidate rows to Airtable staging tableAirtable
- ActionCommit approved survivors and archive duplicate source rowsAirtable
- OutputReport clusters merged and rows archived
What it does
It runs a scheduled sweep over an Airtable contacts table, groups records that look like the same person or company, and computes a single merged candidate per group. Rather than overwriting live data, it stages each proposed survivor in a separate review table where a human approves or edits it.
When to use it
Use it when your CRM lives in Airtable and duplicates accumulate from forms, imports, and manual entry. Best for teams that prefer a batch, end-of-day cleanup with a clear staging area instead of real-time merges.
How it works
- 1A nightly schedule trigger starts the run.
- 2The flow reads all contacts and clusters them by fuzzy email and normalized company name.
- 3A logic step keeps only clusters with two or more members.
- 4For each cluster it builds a survivorship row (longest non-empty value per field, newest owner) and writes it to a Staging table with a Status of Needs Review.
- 5A reviewer sets Status to Approved in Airtable.
- 6On the next pass, approved survivors are written back to the main table and the duplicate source rows are archived.
Set it up
What you configure once, before turning it on.
- 1Connect AirtableBases, tables, views, automations.
- 2Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
- 3Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
- 4Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.
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Run this workflow in your colony.
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