Structured Data for Ecommerce: Product Schema, Offers, Reviews and FAQ Schema

1. 01

   Product schema is JSON-LD that states a product's facts outright (brand, GTIN, price, stock, shipping, returns, ratings, variants) so crawlers don't infer them from your layout.

2. 02

   Google uses it for two rich result types: merchant listings on pages where people buy, and product snippets on pages that review or compare products.

3. 03

   Treat schema as a promise about your product. It pays off only when it matches the visible page and your Merchant Center feed, field for field.

4. 04

   FAQ rich results disappeared from Google Search on May 7, 2026. Keep the FAQ content anyway, because shoppers now put those exact questions to AI assistants.

5. 05

   No special markup gets you into AI Overviews or ChatGPT. Complete product data that says the same thing everywhere does.

The schema types a product page needs

Product and Offer: the required core

The required list is short. Google's merchant listing documentation asks for name, image and offers on the Product, plus price (above zero) and priceCurrency (ISO 4217) on a single Offer.

Most themes stop there. The recommended list is where catalogs differ: brand.name, description, color, material, pattern, size, sku, mpn, a GTIN (gtin8 to gtin14), and on the offer availability, itemCondition and url. Shoppers filter on them; agents match against them. An empty material field costs more than a missing star rating.

Two details catch European stores. price takes a dot as decimal separator and no currency symbol, so "89.00" is valid and "89,00 €" isn't. And GTINs that pass through Excel lose their leading zero, turning a 12 digit UPC into an 11 digit string that fails the check digit. If a product has no GTIN at all, leave the field out and send mpn with brand, as our guide to GTINs and what to do without them explains.

AggregateRating and Review: the aggregate rating schema rules

Google's review snippet rules require ratingValue and at least one of ratingCount or reviewCount on AggregateRating, and an author plus reviewRating.ratingValue on each Review. Stores that lose their stars usually broke one of these:

• The rating and count must be visible on the page.
• Never aggregate ratings from other websites.
• Rate one specific item, never a category or list, so category pages carry no aggregate rating.
• Keep the markup count in step with the widget shoppers see.

Shipping and returns follow a different logic. Google recommends defining hasMerchantReturnPolicy and shippingDetails under your Organization, with offer-level versions only as overrides. Check the precedence order before debugging: return settings in Merchant Center or Search Console override your markup.

Product page schema checklist

• One primary Product per page

  The main entity is the product you sell, and name matches the H1

• No duplicate Product blocks

  Theme and review app both output it, so keep one

• Real GTIN or MPN with brand

  Most specific GTIN type, valid check digit, omitted if none is assigned

• Price matches the page

  Same value and currency, dot decimal, no symbol inside price

• Attributes are filled

  color, material, size, pattern and audience wherever they apply

• Ratings only when visible

  AggregateRating shows the same score and count as the page

• JSON-LD in the initial HTML

  Server-rendered, so Shopping crawls read it reliably

For the copy and UX on that same page, read Product Page Optimization. Once the markup is clean, run the full product page checklist for AI readiness.

Product schema example: single product JSON-LD

An illustrative example for a fictional merino sweater sold in the US.

{
  "@context": "https://schema.org",
  "@type": "Product",
  "name": "Northvale Merino Crew Neck Sweater, Navy",
  "description": "Midweight crew neck sweater knitted from 100% extra-fine merino wool. Regular fit, ribbed cuffs and hem, machine washable on wool cycle.",
  "image": [
    "https://www.example.com/img/merino-crew-navy-1x1.jpg",
    "https://www.example.com/img/merino-crew-navy-4x3.jpg"
  ],
  "sku": "NV-MCS-NAV-M",
  "gtin13": "5901234123457",
  "brand": {
    "@type": "Brand",
    "name": "Northvale"
  },
  "color": "Navy",
  "material": "Merino wool",
  "size": "M",
  "aggregateRating": {
    "@type": "AggregateRating",
    "ratingValue": 4.7,
    "reviewCount": 212
  },
  "offers": {
    "@type": "Offer",
    "url": "https://www.example.com/products/merino-crew-navy?size=m",
    "price": 89,
    "priceCurrency": "USD",
    "availability": "https://schema.org/InStock",
    "itemCondition": "https://schema.org/NewCondition",
    "shippingDetails": {
      "@type": "OfferShippingDetails",
      "shippingRate": {
        "@type": "MonetaryAmount",
        "value": 0,
        "currency": "USD"
      },
      "shippingDestination": {
        "@type": "DefinedRegion",
        "addressCountry": "US"
      },
      "deliveryTime": {
        "@type": "ShippingDeliveryTime",
        "handlingTime": {
          "@type": "QuantitativeValue",
          "minValue": 0,
          "maxValue": 1,
          "unitCode": "DAY"
        },
        "transitTime": {
          "@type": "QuantitativeValue",
          "minValue": 3,
          "maxValue": 5,
          "unitCode": "DAY"
        }
      }
    },
    "hasMerchantReturnPolicy": {
      "@type": "MerchantReturnPolicy",
      "applicableCountry": "US",
      "returnPolicyCategory": "https://schema.org/MerchantReturnFiniteReturnWindow",
      "merchantReturnDays": 30,
      "returnMethod": "https://schema.org/ReturnByMail",
      "returnFees": "https://schema.org/FreeReturn"
    }
  }
}

The offer url preselects size M, so the markup describes exactly what a shopper lands on. Shipping and returns sit inside the offer only to keep the example self-contained; on a real store we'd define them once on Organization.

Product structured data for variants: ProductGroup JSON-LD

Google has supported product variant markup since 2024. The ProductGroup holds the shared facts plus a productGroupID (the parent SKU). variesBy lists the attributes that change, and each variant is a full Product under hasVariant. Google accepts six variesBy values: color, size, material, pattern, suggestedAge, suggestedGender.

{
  "@context": "https://schema.org",
  "@type": "ProductGroup",
  "name": "Northvale Merino Crew Neck Sweater",
  "url": "https://www.example.com/products/merino-crew",
  "brand": {
    "@type": "Brand",
    "name": "Northvale"
  },
  "productGroupID": "NV-MCS",
  "variesBy": [
    "https://schema.org/size",
    "https://schema.org/color"
  ],
  "hasVariant": [
    {
      "@type": "Product",
      "sku": "NV-MCS-NAV-M",
      "gtin13": "5901234123457",
      "name": "Northvale Merino Crew Neck Sweater, Navy, M",
      "image": "https://www.example.com/img/merino-crew-navy.jpg",
      "color": "Navy",
      "size": "M",
      "offers": {
        "@type": "Offer",
        "url": "https://www.example.com/products/merino-crew?color=navy&size=m",
        "price": 89,
        "priceCurrency": "USD",
        "availability": "https://schema.org/InStock"
      }
    },
    {
      "@type": "Product",
      "sku": "NV-MCS-OAT-L",
      "name": "Northvale Merino Crew Neck Sweater, Oatmeal, L",
      "image": "https://www.example.com/img/merino-crew-oatmeal.jpg",
      "color": "Oatmeal",
      "size": "L",
      "offers": {
        "@type": "Offer",
        "url": "https://www.example.com/products/merino-crew?color=oatmeal&size=l",
        "price": 89,
        "priceCurrency": "USD",
        "availability": "https://schema.org/OutOfStock"
      }
    }
  ]
}

This is the template we find broken most often. The theme outputs one Product with a single Offer for the whole family, so every size shares one price, and the GTIN belongs to whichever variant loaded first.

Single-page or multi-page variants

Variants can also point back to the group with isVariantOf or inProductGroupWithID. Either way, mirror the grouping in your feed with item_group_id. We use the same value as productGroupID.

How to validate product structured data

1. 1

   Test the template

   Run a URL or code snippet through the Rich Results Test. Fix errors first, then look at warnings for GTIN, brand or shipping.

2. 2

   Inspect the rendered page

   Use URL Inspection and read the tested HTML. Google advises Product markup in the initial HTML, since JavaScript-generated markup can make Shopping crawls less frequent and reliable.

3. 3

   Monitor the reports

   Watch the Merchant listings and Product snippets reports for items falling out of the valid count.

4. 4

   Cross-check Merchant Center

   Issues such as "Mismatched value (page crawl) [price]" show exactly where feed and page disagree.

5. 5

   Re-test after every release

   Theme updates and new apps often duplicate or break JSON-LD.

Don't treat every warning as urgent. An optional priceValidUntil can wait. A missing GTIN on an advertised product can't.

Common product schema errors and how to fix them

Schema vs feed consistency: one product, one truth

Google reads your product facts on the page, in the JSON-LD and in the Merchant Center feed. With automatic item updates switched on (it's the default), Google uses landing page data, structured data included, to correct price and availability in Shopping ads and free listings. If the feed says $4 and the page says $3, Google uses $3. Too many mismatches can mean disapprovals or switch the automation off.

AI agents add more readers. ChatGPT reads merchant feeds built on OpenAI's product feed spec (title, description, gtin, brand, price, availability) and sends shoppers to the product url. Every disagreement erodes trust.

For crawling and indexing, see Ecommerce SEO. Feed hygiene has its own guide in Product Feed Optimization.