A shopper can now put price range, size, material, compatibility, intended use, and delivery date into one AI prompt. The merchant who sells the exact match still gets skipped if the product page does not make those specs easy to find and verify. Practical Ecommerce published a five-test guide on September 20, 2026, that walks merchants through checking whether AI-driven shoppers can find their products.
The first test is identification. Can an AI shopping agent or chat understand the item? The guide says a listing needs a product name, brand, category, SKU, and when applicable a GTIN, UPC, EAN, or manufacturer part number. Variants for size, color, model, or configuration belong on the page too. Establish what the product is before asking an AI system to recommend it.
The guide then moves to proof, verification, and two further checks. A merchant should list shoppers' likely questions and answer them in the product description. Google Merchant Center specifies a [product_highlight] attribute for important characteristics and common consumer questions, which Google says helps customers discover information across AI-driven surfaces like AI Mode in Google Search.
Lantern runs daily scans across ChatGPT, Claude, Gemini, and Perplexity. It scores presence, position, and sentiment for every brand mention. When a product page fails the identification test, Lantern flags it and produces AI-ready fixes. Lantern scans public-facing storefront pages only and returns results in seconds.
What this means for brands in AI shopping
AI shopping agents cannot recommend a product they cannot parse. The merchant's job is to make specs easy to find and verify. A free AI readiness scan shows where your catalog stands today and what to fix next.
For a deeper look at making product pages legible to AI shopping agents, see Make product pages legible to AI shopping agents.