Does your product page tell an assistant the right price?
Enter your store. The check reads your public catalogue and one product page, then compares the numbers an assistant would quote: price, stock, SKU, image and description. No account and no email address.
What this compares
- The price and stock state your store charges
- The price and stock state your product page tells a machine
- Whether the description, image, brand and SKU are there at all
Two sources, one answer
Every row below is either your public catalogue or the structured data on a page anyone can fetch. Nothing about your business data is used, which is why this is free.
Price agreement
The price in your structured data against the price in your public catalogue. A mismatch is reported with both numbers.
Stock state
Whether the page says in stock, out of stock or nothing at all. Nothing at all is how an assistant offers a sold out item.
Product name
Whether the name reads as a product in an answer, rather than a fragment cut off by a template.
Description
Length of the copy in the markup, because short copy gets paraphrased and paraphrasing is where invented details start.
Image
Whether a result has an image to show, or nothing.
SKU and brand
The identifiers that tie a page to an order, a stock level and the right company.
Catalogue quality
Across the products your store exposes: how many carry a usable description, an image and a SKU.
Nothing inferred
Rows that could not be measured are marked and left out of the score. A shop that refuses scripts is not graded zero.
An assistant does not read your shop the way a customer does
A customer sees the page: the photograph, the size guide, the review stars, the shipping note. An assistant sees text and structured data, and it treats the structured data as the facts. When the two disagree, the assistant quotes the structured one, because that is the part that was written for it.
Product markup goes stale in a specific way. A theme is updated, a price is changed in the admin, and the structured data keeps rendering from a template that was copied once and never touched again. Nothing looks wrong on the page, because the page is a browser render and the mismatch lives in the layer only a machine reads.
Fixing that layer is a one-time job. The ongoing question is different: what is actually true about this product right now, across stock, orders, returns and ads. CorpusIQ answers that from the systems that hold it, inside ChatGPT and Claude, and names the source it used.
The product data check, answered
- What does this free product data check compare?
- Two sources. It reads the public catalogue a store exposes, then the structured data on one product page, and compares the numbers that matter: price, stock state, name, description, image, SKU and brand. Where the two disagree, both values are printed.
- Why does a price mismatch matter more than a missing tag?
- Because a price is a promise. An assistant that reads a stale price from the page will quote it to a customer, and the customer will hold the shop to it. A missing tag costs visibility; a wrong number costs money and trust.
- My shop is not on Shopify. Does this still work?
- The product page half works on any shop that carries schema.org Product markup. The catalogue half reads /products.json, which Shopify exposes publicly; other platforms usually do not, and that row is marked not measured rather than failed.
- Is the check really free, and do you store my domain?
- Yes, free, with no account and no email address. The domain is used for the requests in that one check and the result goes back to your browser. The domain and the result are not written to a database.
- Is a good score enough to be quoted correctly?
- No. Clean markup makes a page quotable. It cannot tell an assistant what your margin is, which products actually sell, what is about to run out, or what a customer was promised in an email. Those answers need your own systems, which is what CorpusIQ connects.
Quotable is the start. Correct is the point.
Connect Shopify, Stripe or your inbox, ask a real question about a real product, and check the answer against the system it came from.
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