MARKETING

Sync Weekly CAC Results into UTM Tracking Sheet

Reads the prior week's spend and conversions per UTM campaign from BigQuery and writes computed CAC, ROAS, and a status flag into the Airtable UTM tracking base…

CategoryMarketing
Enginesim
Difficultyintermediate
Triggerschedule
Steps5
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerWeekly schedule fires
  • ActionQuery spend and conversions per UTM campaignGoogle BigQueryBigQuery
  • LogicCompute CAC, ROAS, and status per campaign
  • LogicMatch rows to Airtable by UTM key
  • OutputUpsert metrics into Airtable UTM baseAirtableAirtable

What it does

This workflow keeps your Airtable UTM tracking base current. Weekly, it pulls spend and conversions joined on utm_source / utm_medium / utm_campaign from BigQuery, computes CAC and ROAS per campaign row, and upserts those numbers back into Airtable along with a green/amber/red status against target. Marketers stop hand-copying numbers and the sheet everyone references stays trustworthy.

When to use it

Use it when your UTM taxonomy lives in Airtable but the actual performance numbers live in the warehouse, and the two are perpetually out of sync. Ideal for teams who treat the Airtable base as the single source of truth for campaign tagging and budget.

How it works

A weekly schedule triggers the sync. The workflow queries BigQuery for per-UTM-campaign spend and converted customers over the trailing week. A logic step computes CAC, ROAS, and a status flag per campaign and matches each to its Airtable record by UTM key. Existing rows are updated in place and any new campaigns seen in the warehouse are created as fresh records, leaving a fully reconciled tracking base.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect BigQueryDatasets, queries, schemas.
  2. 2
    Connect AirtableBases, tables, views, automations.
  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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