GigaCommerce

Free template

Catalog Attribute Coverage Audit

A per-SKU scoring grid for catalog data quality — identifier, schema, rendering and attribute coverage — with three worked examples showing how the scoring works.

CSV · 15 columns · 3 worked examples

Who it's for: Anyone with a catalog big enough that "our product data is fine" is a guess rather than a fact.

No sales call, no drip sequence. We use your email to send the file and nothing else unless you tick the box.

What's in it

Exactly what you're getting.

  • 115 columns covering identifier presence, brand consistency, taxonomy discipline, attribute coverage, server-side rendering, schema validity and reviews.
  • 2Boolean columns scored 1/0 so you can average a whole column and get a real catalog-level number.
  • 3A coverage_pct formula that pairs with the Critical rows from the product attribute schema template.
  • 4Three worked example rows showing what a passing, failing and mixed SKU look like — including the most expensive failure, a script-rendered price.
  • 5A gap_notes column, because the specific gap is what gets fixed, not the score.

How to use it

The order that actually works.

Most of these templates fail the same way — filled in completely, applied to nothing. This is the sequence we'd follow.

  1. 1Export your catalog and paste one row per SKU. Delete the three example rows once you've read them.
  2. 2Sort by revenue, not by score. Fixing your top 20 sellers beats fixing 200 long-tail SKUs, and it's the fastest route to a measurable change.
  3. 3Average each boolean column to get catalog-level numbers you can report — "61% of SKUs have a GTIN" is a sentence a CFO understands.
  4. 4Re-score the same SKUs after the fixes so you have a before and after.

The thinking behind it

Catalog Debt: Measuring What Incomplete Data Costs You

The full guide this template came out of. No email required — it's just on the site.

Would rather we just ran it?

The free AI Shelf Check does the measurement side for you — whether ChatGPT, Perplexity and Gemini recommend your products or a competitor's. No call required.

Weighing whether to do this in-house? Compare the approaches