Free tool
Product schema generator
Enter a product name, description, brand, price, currency, availability and rating, and get valid Product JSON-LD with a nested Offer. Structured product data feeds search rich results and, increasingly, the AI shopping surfaces that assemble product answers from machine-readable facts rather than marketing prose.
product-schema.html
<script type="application/ld+json">
{
"@context": "https://schema.org",
"@type": "Product",
"name": "Product name"
}
</script>
Product data is how machines shop
When a buyer asks an assistant for the best option under a budget, the engine needs prices, stock and ratings as data, and prose is a lossy place to find them. Product markup with an Offer states the facts machine-readably: price as a number, priceCurrency as an ISO 4217 code, and availability from schema.org's fixed list, such as InStock or OutOfStock.
The surfaces reading this data keep multiplying. Google's merchant listings pull price and stock straight into search results. ChatGPT rolled out shopping results in 2025 that draw on structured product information and merchant feeds, and Perplexity runs shopping answers of its own. Clean product markup is the shared entry ticket to all of them.
How to use the output
Paste the script tag into the product page and keep it truthful in real time. A price in markup that contradicts the visible page is worse than none, since mismatches can void rich result eligibility. On stores where prices move, generate the markup from platform data rather than editing by hand; most platforms, including Shopify, already emit product schema you can audit against this tool's output.
Ratings deserve extra care. aggregateRating must reflect reviews you actually collected. Invented review counts violate Google's structured data policies, and fake reviews themselves became explicitly illegal in the United States under the FTC rule finalized in 2024, with civil penalties per violation.
Honest limits
Markup earns eligibility, never placement. Google decides when merchant listings appear, and AI shopping surfaces blend structured data with feeds, reviews and crawled text you control only partly. When assistants compare products, third-party evidence like review sites and community threads often outweighs anything on your own domain.
So ship the markup as the data layer, then check the outcome that matters: when buyers ask an assistant what to buy in your category, whether your product is in the answer. Reachroller tracks exactly that, with a free 3-day trial and plans from $29 a month.
Frequently asked questions
Which availability values are valid?+
Use schema.org's ItemAvailability values, written as full URLs in the output: InStock, OutOfStock, PreOrder, BackOrder, LimitedAvailability and Discontinued are the common ones. Pick the one that reflects reality right now and update it when stock changes, because stale availability is a fast way to lose rich result eligibility.
Can I include a rating with only a few reviews?+
Yes, if the reviews are real. A 4.7 from nine genuine customers is legitimate markup. What you cannot do is inflate counts or invent scores: that violates Google's structured data policies and, since the FTC's 2024 rule on fake reviews, carries legal risk in the United States on top of the ranking risk.
Do AI shopping results actually read this markup?+
Structured product data is one of their inputs. ChatGPT's shopping experience uses product metadata and merchant feeds, Perplexity ingests merchant data for its shopping answers, and Google's merchant listings depend on Product markup or Merchant Center feeds. None of them publishes exact weights, so treat markup as necessary table stakes.
How do I keep markup in sync with changing prices?+
Automate it. Have your ecommerce platform or templates render price and availability from the same source of truth as the visible page, so the two cannot drift apart. Use this generator to see what correct output looks like, then audit your live pages with Google's Rich Results Test after price changes.
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