Identifiers
Missing and duplicate product IDs, brand coverage and absence of both GTIN and MPN.
PRODUCT CATALOG AUDIT
Product catalog audit for cleaner ecommerce data
Find incomplete, duplicated and inconsistent product records before they spread into shopping feeds, marketplaces and advertising channels.
- ✓ Free initial scan
- ✓ Up to 100,000 products
- ✓ No store connection
- ✓ No account required
A bad feed often starts with bad catalog data
Catalog→Feed export→Google Shopping→Meta and marketplaces→Comparison engines
When several destinations reuse the same product table, a missing ID, malformed price or empty brand is multiplied by every export. Repair the originating field or mapping rather than patching each destination separately.
Catalog fields measured by the production ruleset
Names and descriptions
Missing or very short titles and descriptions. Duplicate content is not currently scored.
Destinations and assets
Presence and HTTP/HTTPS syntax of product and primary image URLs, without per-URL crawling.
Commerce
Positive price plus currency and one of the supported availability values.
Taxonomy
Presence of category, product_type or google_product_category.
Rows and structure
XML product nodes or CSV rows, header integrity, product totals and repeated rule failures.
What a catalog-level problem looks like
EXAMPLE FINDINGIllustrative example — not a customer result.
Issue
Duplicate product ID
Impact38 / 12,400 products
PriorityCritical
- Why it matters
- Repeated identifiers make product updates ambiguous across exports.
- Recommended action
- Generate one persistent source ID for each catalog record and keep it stable between exports.
EXAMPLE FINDINGIllustrative example — not a customer result.
Issue
Missing brand
Impact1,204 / 12,400 products
PriorityMedium
- Why it matters
- Brand coverage supports product identity, but applicability and the correct value must come from the source catalog.
- Recommended action
- Populate the manufacturer or brand at source when applicable; do not infer it from unrelated text.
Decisions that still need catalog owners
Variant relationships
The current normalized model does not audit item groups, size or color relationships.
Duplicate real-world products
Different IDs may describe the same item, but that requires domain context beyond duplicate-ID detection.
Factual classification
A present category can still be wrong. The scanner currently measures presence, not taxonomy correctness.
Measure first, repair upstream
METHODOLOGY & SOURCES
Deterministic checks, documented limits
Product Feed Scan parses public XML and CSV feeds incrementally, applies versioned rules to supported fields and groups failures by impact. It does not predict platform policy decisions, modify feeds or guarantee channel approval.
Product catalog audit questions
VISIBLE FAQ
Questions about this guide
What is the difference between a catalog audit and a feed audit?+
A catalog audit focuses on upstream product records and mappings. A feed audit examines one exported representation of that catalog. The same source problem may appear in several feeds.
Does Product Feed Scan connect to a PIM or ecommerce database?+
No. It audits a public XML or CSV export. Teams use the findings to correct the source system or export mapping themselves.
Does the current audit detect duplicate products?+
It detects duplicate product IDs. It does not currently decide whether different IDs represent the same real-world product or automatically classify duplicate titles.
Can the report be shared with developers?+
The private report, full affected-products CSV and PDF provide issue codes, affected rows and recommendations suitable for an implementation handoff.
FREE PRODUCT FEED SCAN
Check your feed →Measure the catalog before fixing it.
Scan a public XML or CSV feed, review the free score and unlock the complete private report only if you need every affected product.