SD005 – Duplicate SKU Detection
Overview
Ensures each product has a unique, non-empty SKU. Detects missing SKUs, empty SKUs, and duplicate SKUs across Product and hasVariant items.
Probability that AI systems use this signal: Crawlers and generative AI pipelines consume structured and visible page signals for training and inference. Assessment-specific signals (e.g. schema, canonicals, trust cues) affect how likely a page is indexed and surfaced. The probability that this assessment's signal influences AI behavior is high when the page is in a product or compliance context.
Impact on geo compliance: Passing this assessment supports geo compliance by ensuring machine-readable and visible content meet standards that reduce the risk of wrong locale, pricing, or trust in AI-generated answers. Failing can lead to non-compliant or misleading surfacing.
What We Check
- SD001 passed. JSON-LD extracted; all Product objects collected (including from ProductGroup.hasVariant).
- For each product, `sku` is read (string strip); empty string treated as missing.
- **Missing SKU:** count of products without SKU; −50 per product missing.
- **Empty SKU:** count of products with empty SKU; −50.
- **Duplicates:** SKUs that appear for more than one product; −50 and one issue per duplicate SKU listing product names.
Pass / Fail and Score
- **PASSED** if score >= 60.
- **Score:** 100 minus penalties (50 for missing SKU, 50 for empty SKU, 50 for any duplicates). Details include product count, SKU count, unique SKU count, duplicate count.
How to Fix When It Fails
- Add SKU field to all Product schemas.
- Ensure SKU is not empty.
- Ensure each product has a unique SKU.
Common Issues
- One or more products missing SKU.
- One or more products with empty SKU.
- Same SKU used for multiple products (duplicate).
Dependencies
SD001.
How to Verify
- List all Product (and variant) sku values; ensure unique and non-empty.
Additional Resources
- schema.org Product.sku: https://schema.org/Product#sku