Find and fix Category Attribute Gaps

Plans: Pro or Unlimited
 

What this finds

For products that already have a Shopify Standard Product Taxonomy category, Data Doctor finds empty Category metafields (taxonomy attributes such as material, color, or size type—usually under the shopify namespace in Admin).

Blank values and empty lists count as gaps.

This does not assign a category to products that have none. Use a coverage scan’s missing-category CSV or AI Category Suggestions for that.

Step 1 — Run the gaps scan

1. Open Data Doctor → Category Attribute Gaps.
2. Start a new completeness scan.
3. Wait for the scan to finish (background job; email when complete).

You will get:

• A gaps CSV (import-oriented columns such as product handle, namespace, key, type, value).
• When AI suggestions are enabled for your shop: a recommended CSV with suggested values for many text / choice-list attributes.

Note: Measurement / dimension-style attributes are typically manual—suggestions may not fill those.

Large catalogs are capped per run (server-configured). If you have more products than the cap, run again after fixing a batch, or contact support.

Step 2 — Review & apply (recommended path)

Do not rely on auto-write. Use the in-app review flow:

1. From the completed scan report, open Review & apply (or the Category Attribute import entry point linked from the report).
2. Preview the table of suggested rows.
3. Set Apply to Yes only on rows you accept.
4. Correct suggested values if needed (choice lists should match taxonomy options).
5. Confirm to write values with metafieldsSet.
6. Keep the job result / journal so you can revert if something looks wrong.

If AI suggestions are off

You can still download the gaps CSV, fill values yourself, and import via the app’s CSV import tools or Admin.

Related articles

• Run a metafield coverage scan
• AI Category Suggestions
• Understanding Data Doctor reports and CSVs
• Import and export metafields (CSV format)