Product data AI assistants understand
Have hundreds or thousands of product pages and want the content to make sense to AI assistants? That is a data quality project, not a magic SEO trick. Laup shows you what is missing, and measures whether the fixes work.
Stores with large catalogs
The more product pages, the less can be fixed by hand. This page is for ecommerce leads and development teams who have to make a whole catalog readable to AI, and who need to know where to start and how to measure progress.
Machine-readable, not just good-looking on screen
An AI agent does not read the store the way customers do. It needs structured data and content that exists in the HTML itself. These are the four things the scan checks on your product pages.
- A complete Product schema
- The Product markup is assessed against ten fields AI agents need, among them price, currency, availability and GTIN.
- Content visible without JavaScript
- Up to ten product pages are fetched both as raw HTML and through a real browser, and the content is compared. What an AI crawler cannot see, it cannot recommend.
- Access for AI bots
- robots.txt is checked against 14 AI bots, among them GPTBot, ClaudeBot and Google-Extended. A blocked bot reads no product data at all.
- Discoverable product pages
- Sitemap coverage and lastmod dates decide whether new and changed products get found in the first place.
Want the full requirements? Read the methodology behind the scan. Not sure whether product data should come before tracking? See the order that is worth the money.
From unknown state to measurable progress
- A field-by-field assessment
- The scan shows which schema fields are present and which are missing, for each product page it checks.
- Prioritized gaps
- The gaps are sorted by what matters most, so a large catalog project can start at the right end.
- Daily measurement of the effect
- Tracking shows whether the AI assistants actually start naming and recommending the store once the data is fixed.
Wherever the product data lives
Shopify, WooCommerce, Magento or a custom build: the scan reads the public product pages the way an AI crawler does, with no integration or access. Where the Product schema is controlled varies (theme, app or plugin), but the findings are the same on every platform. Stores in English and Norwegian are supported, and the report itself is in English.
Fix, rescan, measure
Scan the store
The scan checks a sample of product pages and shows the state of schema, visibility and access.
Fix the gaps where they are controlled
Most gaps are fixed in one place (theme, app or feed) and then apply to the whole catalog.
Rescan
Run the scan again and see the score move before you go on to the next gap.
Measure that AI actually recommends you
Start the trial (14 days, no card): daily measurements show whether the AI assistants start naming the store.
Start free, then a fixed monthly price
The scan is free and needs no signup. Tracking is a monthly subscription you can cancel at any time. See the full pricing.
Tool first, help when you need it
Laup is a Norwegian company, and the core is a product you use yourself: you see the same data we do, measured every day with an open methodology. Your development team or agency can work straight from the report, and when the catalog is large and you would rather have hands-on help, our advisory covers that separately.
How AI-ready are your product pages?
Scan the store for free and get the answer in under a minute.
No signup. Read more about the scan.