Sample report
A product data audit that shows the evidence, not just the score.
This sample shows the paid ProductProof deliverable: storefront facts, structured data, repeated risk patterns, and fix-ready guidance. The demo store is synthetic.
Readiness score
68
Needs fixes
Executive summary
Three template-level issues should be fixed before scaling paid traffic.
Northline Goods has a strong storefront, but product data is inconsistent across price, shipping, and return-policy signals. The safest next step is to fix shared templates, then rescan a sample set.
Commercial decision
Yes. This store needs a deeper audit before more traffic spend.
The audit found issues that are understandable to a merchant and actionable for a developer: mismatched offer data, missing policy markup, and thin product facts.
Product Data Passport
What machines can reliably read
Critical
Merchant Center
Visible price does not match structured price on 12 products
Why it matters
Price mismatches can create Merchant Center issues and reduce confidence in product offer data.
Evidence
Visible page price: $49.00. Product JSON-LD price: $59.00. Found on the Bottle product template.
Recommended fix
Use the same source of truth for visible price, Product JSON-LD, and feed price. Rescan after template cache clears.
High
Structured Data
Offer.shippingDetails is missing across the product template
Why it matters
Shipping details help shopping systems understand delivery cost and region signals.
Evidence
Shipping text is visible in the page footer, but OfferShippingDetails was not found in Product/Offer markup.
Recommended fix
Add OfferShippingDetails where appropriate, or connect merchant-level shipping settings and validate supported fields.
High
Trust & Policies
Return policy is visible but not connected through MerchantReturnPolicy markup
Why it matters
Return policy data can help systems interpret post-purchase terms consistently.
Evidence
Footer links to a 30-day returns page, but no hasMerchantReturnPolicy field was detected.
Recommended fix
Add MerchantReturnPolicy markup at Organization or Offer level where appropriate.
Medium
Product Content
18 product descriptions are too thin for AI shopping summaries
Why it matters
Thin descriptions make product attributes, use cases, and buyer fit harder to extract.
Evidence
Several descriptions are under 80 characters and repeat the product title.
Recommended fix
Add material, dimensions, compatibility, use case, and care attributes where relevant.
Fix preview
Example Shopify JSON-LD guidance
{
"@type": "Offer",
"price": "{{ product.selected_or_first_available_variant.price | money_without_currency }}",
"priceCurrency": "{{ cart.currency.iso_code }}",
"availability": "https://schema.org/InStock",
"shippingDetails": {
"@type": "OfferShippingDetails",
"shippingDestination": { "@type": "DefinedRegion", "addressCountry": "US" }
}
}ProductProof provides implementation guidance where applicable. It does not guarantee approval, rankings, rich results, revenue, or AI inclusion.