MARKETING

Weekly UTM Hygiene Audit Against Warehouse

Compares the campaigns logged in the Airtable UTM base against the utm_campaign values actually seen in BigQuery sessions, flags untracked, orphaned, and malformed tags.

CategoryMarketing
Enginesim
Difficultyintermediate
Triggerschedule
Steps5
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerWeekly schedule triggers audit
  • ActionRead registered campaigns from Airtable UTM baseAirtableAirtable
  • ActionQuery distinct utm_campaign values from BigQueryGoogle BigQueryBigQuery
  • LogicDiff sets and validate naming convention
  • OutputPost cleanup checklist to SlackSlack

What it does

Dirty UTM tags quietly corrupt every CAC number downstream. This workflow audits hygiene weekly: it lists the campaigns your team has registered in the Airtable UTM base and the distinct utm_campaign values BigQuery actually recorded, then reconciles the two. It flags live campaigns missing from the sheet, sheet entries with zero recent traffic, and tags that violate your naming convention — and reports them to Slack so they get cleaned before the next budget review.

When to use it

Use it when your CAC and ROAS figures feel untrustworthy because of inconsistent or stray UTM tagging. Run it ahead of the weekly reallocation so decisions rest on clean attribution.

How it works

A weekly schedule triggers the audit. It reads the registered campaign list from the Airtable UTM base and queries BigQuery for distinct utm_campaign values with recent sessions. A logic step diffs the two sets and validates each tag against your naming pattern, bucketing issues into untracked, orphaned, and malformed. The categorized findings are posted to Slack as an actionable cleanup checklist.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect AirtableBases, tables, views, automations.
  2. 2
    Connect BigQueryDatasets, queries, schemas.
  3. 3
    Connect SlackChannels, DMs, threads, mentions.
  4. 4
    Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
  5. 5
    Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
  6. 6
    Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.

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