Your Guide to Data Standards: Setting the Baseline for Your Health Check
A three-step, self-serve workbook for the Claravine Data Health Check — find where your campaign data lives, export an honest sample, and write down the data standards you actually want, so the gaps become measurable.
Workbook
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Where to look, what to export and how to write down the standards you want, sent to your inbox.
Most marketing teams already know their data could be better. The UTMs are inconsistent. The naming conventions are a “work in progress.” The tracking spreadsheet has a tab labeled “Do Not Touch.”
But knowing things are messy is very different from seeing how messy, and that gap is exactly where the fear lives. Messy data isn’t a performance review. It’s a starting line.
This workbook prepares you for the Data Health Check, which turns a vague, uncomfortable problem into a measurable, manageable one. It’s a three-step, self-serve process: no system integrations, no consultants on standby, no judgment.
Inside, you’ll work through
- Where to look: identify the platforms where your campaign data, UTMs and tracking links live, and pull a representative sample into one CSV.
- What good looks like: a data standards checklist covering naming conventions, required fields, channel and source taxonomy, AI-ready structure and cross-team alignment.
- Hand it over: what the Claravine team analyzes offline, and the plain-language summary you get back.
You don’t need to fix everything today. You just need to see what’s actually there.
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