MARKETING

Daily BigQuery UTM audit with a Slack offender report

Each morning, queries yesterday's session UTMs in BigQuery, finds links that break the naming taxonomy, and posts a ranked Slack report of the worst offenders by traffic volume.

CategoryMarketing
Enginesim
Difficultyintermediate
Triggerschedule
Steps5
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerScheduled daily run after data settles
  • ActionQuery yesterday's UTM tuples and session countsGoogle BigQueryBigQuery
  • LogicFilter to taxonomy violations, rank by volume
  • LogicFormat top offenders into a digest
  • OutputPost offender report to SlackSlack

What it does

This workflow scans the previous day's tracked sessions in BigQuery, flags every UTM combination that violates your taxonomy (unknown sources, mixed-case mediums, off-pattern campaign names), and ranks the offenders by how much traffic they pulled in. It then posts a digest to Slack so the highest-impact mistakes get fixed first.

When to use it

Use it when UTM data already lands in BigQuery and you want a standing daily check that surfaces taxonomy drift while the campaigns are still live and the numbers still matter.

How it works

  1. 1A scheduled trigger runs every morning after the prior day's data has settled.
  2. 2A BigQuery action queries distinct UTM tuples and their session counts for yesterday.
  3. 3A logic step matches each tuple against the taxonomy and keeps only violations, sorted by volume.
  4. 4A logic step formats the top offenders into a readable digest with the rule each one broke.
  5. 5A Slack message posts the report to the marketing-ops channel.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect BigQueryDatasets, queries, schemas.
  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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