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Marketing Ops workflow library

Marketing Ops campaign QA

Check campaign intake, consent, segmentation, tracking, personalization, approval evidence, and post-send reporting.

This is a complete workflow library with 5 individual skills. Download the full library or pick the specific skill folder your team needs first.

Download full library ZIP See individual skills
Individual skills in this library

Use one skill at a time, or keep the full workflow together.

Some AI tools expect one skill folder per upload. Download the full library when you want the whole workflow, or download an individual skill when you only need one job done.

Skill 1

Campaign intake safety check

Use when raw campaign briefs, segment notes, lists, launch tickets, or personalization ideas need screening before AI-assisted campaign QA starts.

Download individual skill GitHub source
Skill 3

Tracking and personalization QA

Use when UTMs, attribution assumptions, personalization tokens, links, test sends, or A/B test setup must be checked before scheduling.

Download individual skill GitHub source
Skill 4

Launch approval packet builder

Use when campaign launch readiness must be summarized across consent, segment logic, tracking, personalization, risk, blockers, and signoff owners.

Download individual skill GitHub source
Skill 5

Post-send evidence summary

Use when delivery, engagement, A/B test, attribution, or pipeline results need a safe post-send summary without overclaiming causality.

Download individual skill GitHub source
Security fit check

Is the public Marketing Ops campaign QA library enough, or does this need deeper review?

Use the public library when the workflow is low-risk, the inputs are already sanitized, and a team member can review the output before it reaches a buyer or customer.

Do deeper review when this workflow touches real tools, data sources, role ownership, approval paths, or customer-facing output.

Campaign QAMarketing OpsDemand GenerationRevOps

Good deeper-review trigger signals

  • The workflow touches customer, prospect, CRM, proposal, security, pricing, or campaign data.
  • Different teams disagree on the approved source of truth.
  • The AI output could become customer-facing, revenue-impacting, or compliance-sensitive.
  • You need reusable eval checks before asking more people to use the workflow.
Review workflow examples