Ecommerce · Structured data · Practical guide

A practical Product JSON-LD checklist for ecommerce

A product page may be easy for a shopper to read while missing structured details that search and shopping systems use. This checklist helps merchants identify common data-quality gaps. It does not guarantee rich results, AI recommendations, sales, or any particular ranking.

1. Check for Product structured data

Inspect the product page HTML for a JSON-LD block with @type: Product. A page can also expose structured data in other supported formats; this quick guide focuses on JSON-LD.

2. Connect a real Offer

For products you sell, check the nested offers object. Price, currency and availability should agree with the visible product page and actual store state. Don't invent availability, reviews or pricing.

<script type="application/ld+json">
{
  "@context": "https://schema.org",
  "@type": "Product",
  "name": "Example Notebook",
  "image": ["https://example.com/notebook.jpg"],
  "description": "Fictional demonstration item",
  "offers": {
    "@type": "Offer",
    "price": "19.00",
    "priceCurrency": "USD",
    "availability": "https://schema.org/InStock",
    "url": "https://example.com/notebook"
  }
}
</script>

3. Check consistency with your feed

On-page schema and submitted product feeds are not interchangeable. Compare product identifiers, price, currency, inventory and landing URLs across your store and any feed you provide. Use platform-specific documentation for eligibility and delivery.

4. Validate the live result

Start with Google's Rich Results Test and Merchant Listing documentation. If you are considering ChatGPT product feeds, read OpenAI's product-feed specifications; direct feed onboarding may require partner approval.

What the free checker cannot do

It cannot fetch a URL, validate all schema requirements, assess Merchant Center approval, evaluate AI ranking, or prove sales. Treat it as a first-pass checklist before running official validators and platform-specific checks.