MARKETING

Agentic UTM Taxonomy Steward: Detect, Explain, and Propose Fixes

An agent reviews the full backlog of campaign links in Airtable, reasons about taxonomy drift beyond rigid rules, drafts standardized replacements for malformed UTMs.

CategoryMarketing
Enginepaperclip
Difficultyadvanced
Triggerschedule
Steps5
Setup~25 min

How it runs

The automated pipeline, trigger to output.

  • TriggerWeekly taxonomy review schedule fires
  • ActionFetch all active campaign links from AirtableAirtableAirtable
  • LogicAgent reasons over taxonomy and channel consistencyOpenAI
  • ActionStage corrected URLs and rationale as proposals in AirtableAirtableAirtable
  • OutputSend batched approval request to SlackSlack

What it does

Goes past mechanical linting: an agent pulls the campaign link inventory from Airtable, evaluates each link against your UTM taxonomy and naming conventions, and judges fuzzy issues a regex cannot — like a source value that is technically valid but inconsistent with the campaign's channel. It drafts corrected URLs, writes its reasoning, and sends a batched approval request to Slack.

When to use it

Use it when your UTM problems are about consistency and judgment, not just syntax — sprawling taxonomies, multiple teams inventing their own source names, or a backlog that needs cleanup with rationale a human can trust. The agent explains why each link is off and what it should become.

How it works

  1. 1A scheduled trigger kicks off a weekly taxonomy review.
  2. 2The agent fetches all active campaign links from Airtable.
  3. 3It reasons over each link against taxonomy rules and channel context, flagging both hard violations and soft inconsistencies.
  4. 4For each issue it drafts a standardized corrected URL with a written rationale and stages it in Airtable as a proposal.
  5. 5A batched approval message is delivered to Slack so the steward can accept or reject the fixes.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect AirtableBases, tables, views, automations.
  2. 2
    Connect SlackChannels, DMs, threads, mentions.
  3. 3
    Connect OpenAIModels, embeddings, files.
  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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