AI shopping agents parse structured data before they parse prose. If your schema is incomplete, shopping agents fill in the blanks — or skip your product entirely. Install the StoreSteady app to find metafields and attributes that exist in your store but never reach your schema.
Start with a product URL, collection page, or homepage. We inspect the structured data your public storefront serves.
The scanner looks for missing product fields, weak offer details, and policy markup gaps that create trust issues.
You see which schema fields matter most for AI visibility, Merchant Center alignment, and buyer confidence.
AI agents move fast. When the underlying markup is incomplete or inconsistent, they stop trusting the page.
Missing brand, category, variant, and identifier fields make it harder for AI agents to understand what the product is and when to show it.
When price, availability, or shipping data in structured markup does not match the visible page — or what is actually true in your Shopify catalog — AI agents treat the offer as unreliable.
FAQ, return policy, and shipping details often live in copy alone. Without structure, AI agents cannot extract those answers confidently.
Use these help articles when you want the step-by-step fix path behind the scan.
Missing or inconsistent product condition data weakens Google’s understanding of your offer.
If Google cannot read a return policy from settings or markup, your offer trust signals stay weaker.
Google believes your product has a GTIN, but the submitted product data says identifier exists is false.
Run the free schema audit to surface the missing product, offer, FAQ, and policy signals keeping your markup from doing its job.
