MARKETING

Nightly UTM Drift Audit from BigQuery

Each night scans the day's live click traffic in BigQuery for UTM values that violate the naming registry.

CategoryMarketing
Enginesim
Difficultyintermediate
Triggerschedule
Steps5
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerNightly schedule after analytics data lands
  • ActionQuery distinct UTM tuples and session counts in BigQueryGoogle BigQueryBigQuery
  • ActionLoad approved naming registry from CodaCodaCoda
  • LogicFlag off-convention tuples, rank by sessions affected
  • OutputPost ranked drift digest to SlackSlack

What it does

Finds UTM tagging mistakes that already made it into production. It queries yesterday's sessions in BigQuery, extracts the distinct UTM combinations actually being recorded, and checks each against the approved registry. Anything off-convention is surfaced with how many sessions it polluted, so you fix the highest-impact leaks first.

When to use it

Run it daily for analytics and growth teams who care about clean attribution. It catches drift that preflight validation misses: links built outside the official tooling, vendor-appended parameters, and stale campaign names that slipped back into rotation.

How it works

  1. 1A scheduled trigger fires once nightly after data lands.
  2. 2A BigQuery query pulls distinct UTM tuples and session counts from the prior day.
  3. 3The naming registry is loaded from Coda for comparison.
  4. 4Logic flags every tuple whose source, medium, or campaign value isn't in the registry, ranking by sessions affected.
  5. 5A Slack digest posts the top offenders with traffic volume and the likely correct value; clean nights post a short all-clear.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect BigQueryDatasets, queries, schemas.
  2. 2
    Connect CodaDocs, packs, automations.
  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.

Run this workflow in your colony.

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