Structured data markup on your product pages gives Google a machine-readable version of your product information. Since April 2026, Google's AI verification system actively cross-checks your Merchant Center feed data against the Schema.org markup it finds on your pages. If those two sources disagree, you get a data quality disapproval. This guide covers what markup is required, how to implement it, and how to prevent mismatches that cause suspensions.
When Google crawls your product pages, it reads two things: the visible HTML content and any structured data markup embedded in the page. Structured data (using Schema.org vocabulary in JSON-LD format) tells Google exactly which element is the price, which is the availability status, and which numbers are GTINs or product IDs.
Without structured data, Google has to infer product details from the page HTML, which introduces more errors and slower crawl cycles. With complete and consistent structured data, Google can verify your feed data faster and with more accuracy. Since 2026, this verification happens at the account level: stores with systematic markup-to-feed mismatches get flagged for misrepresentation even if no individual product is wildly wrong.
For a product page to fully satisfy Google's Merchant Center requirements, your JSON-LD markup should include these properties:
The offers.availability value must use Schema.org vocabulary: https://schema.org/InStock, https://schema.org/OutOfStock, or https://schema.org/PreOrder. Do not use plain text like "in stock" or "available". Google maps these to the values in your feed and a format mismatch causes unnecessary flags.
<script type="application/ld+json">
{
"@context": "https://schema.org",
"@type": "Product",
"name": "Blue Running Shoe - Men's Size 10",
"image": "https://example.com/images/blue-shoe-10.jpg",
"description": "Lightweight running shoe for daily training.",
"sku": "SHOE-BLUE-10",
"gtin13": "0123456789012",
"brand": {"@type": "Brand", "name": "YourBrand"},
"offers": {
"@type": "Offer",
"url": "https://example.com/products/blue-shoe-10",
"priceCurrency": "USD",
"price": "89.99",
"availability": "https://schema.org/InStock",
"seller": {"@type": "Organization", "name": "Your Store"}
}
}
</script>
The most common mismatch that causes disapprovals is the availability conflict. If your feed sends availability=in_stock and your page schema says OutOfStock, Google sees two conflicting data sources and flags a data quality issue. This happens frequently during flash sales when inventory runs out faster than the feed updates.
Price mismatches are the second most common problem. If your offers.price in the schema differs from the price in your feed, Google may show the schema value in the ad or flag the discrepancy as a potential misrepresentation. This is especially common when stores use dynamic pricing tools that update the page price without updating the feed simultaneously.
GTIN conflicts are less common but more serious. If your schema includes a GTIN and your feed also has a GTIN, and they differ, Google may pull the wrong product listing data from the product catalog, causing your item to appear under a different product's listing with different pricing or images.
The GMCSuspension Googlebot Simulator crawls your product page as Google does and shows exactly what structured data it detects, including the price, availability, and GTIN values. Use it to confirm your markup before submitting an appeal or after updating your schema.
Two tools are essential for validating product markup:
If Rich Results Test shows your markup correctly but Merchant Center still flags a mismatch, the issue is usually timing: Google has not yet re-crawled the updated page. Trigger a re-crawl by using the URL Inspection tool in Google Search Console and clicking "Request indexing."
Shopify automatically generates Product structured data for all product pages. The data is injected by Shopify's theme layer, not by your feed app. If you recently changed themes or updated your Shopify plan, check whether the new theme outputs complete JSON-LD markup or whether it has reverted to Microdata, which is harder for Google to parse reliably.
WooCommerce outputs structured data via the Yoast SEO or Schema Pro plugins in most setups. If you update the plugin or change your product pricing logic, re-validate a sample of product pages to confirm the schema still matches your feed. WooCommerce's variable products (products with size/color variants) sometimes output the lowest price variant instead of the selected variant, which can mismatch against a variant-specific feed entry.
The free GMCSuspension audit checks your store's structured data against 52+ policy requirements, including schema-to-feed consistency. It takes about 60 seconds and shows you exactly what to fix before you appeal.
Start Your Free AuditNot technically required, but it is strongly recommended. Since 2026, Google's AI verification layer cross-checks your feed data against the markup it finds on your pages. Consistent markup reduces data quality flags and speeds up the re-crawl cycle after feed updates.
Google recommends Product schema in JSON-LD format with: name, image, description, sku or mpn, gtin, brand, and an Offer object containing price, priceCurrency, availability, and url. Use Schema.org vocabulary for the availability value, not plain text strings.
Google compares your feed data with what it reads in the page markup. If the price, availability, or GTIN in your schema differs from your feed, it flags a data quality issue. Systematic mismatches across many products escalate to an account-level misrepresentation review.
Use Google's Rich Results Test to validate individual pages. Check Merchant Center's Diagnostics tab for account-wide data quality flags. The GMCSuspension Googlebot Simulator shows what properties Google detects when it crawls your URL, including schema values.
Yes. If your feed sends in_stock, your schema should include availability="https://schema.org/InStock". Conflicting values between the feed and the markup are the most common source of data quality disapprovals, especially during stock changes or promotions.
For more on preventing data mismatches, read the guide to product data mismatch fixes and the full disapproved products guide. If your account is suspended, the suspension checklist covers every check you need to run before appealing.