By Steve Merrill, Founder of WRKNG Digital | September 27, 2026
The attributes that most influence AI recommendations are GTIN, brand, category, and the specific traits assistants match against: material, color, size, price, availability, and condition. These are the hooks an AI uses to decide you're the right answer. Here are the ten that carry the most weight.
1. GTIN and MPN
These identifiers verify your product is real and match it to known catalogs. Without them, an assistant treats your listing as unconfirmed. They're the first thing to fill.
2. Brand
Brand anchors trust and powers brand-specific queries. A blank brand field makes your product generic and harder to match. Populate it on every SKU.
3. Product category
Correct category placement tells the assistant where your product belongs. Google's product taxonomy is the reference most feeds use, and assistants rely on it to filter results.
4. Material
Material is a top match attribute for apparel, home, and gear. "Stainless steel," "organic cotton," "cast iron." Shoppers ask by material, and assistants can only match what's in the feed.
5. Color
Color is one of the most common query filters. Specific, standardized color values let an assistant match "navy blue" without guessing. Vague color names cost you precise queries.
6. Size
Size and dimensions decide fit-based recommendations. Structured size data lets an assistant match "size 10" or "queen" exactly. Missing size drops you from any sized query.
7. Price
Assistants filter by budget and won't recommend an unpriced item. Accurate price and currency keep you eligible for "under $50" style requests. Keep it synced.
8. Availability
An assistant won't send a shopper to something out of stock. Real-time availability keeps you in the running. Google's Merchant Center spec treats it as required, and AI reads it the same way.
9. Condition
New, used, or refurbished changes what the assistant recommends and to whom. It's required in most feed specs. Leaving it blank creates ambiguity.
10. Detailed description
A specific, structured description gives the assistant extra matchable context: use case, features, compatibility. Generic marketing copy adds little. Detail earns the match.
How We Chose This List
We ranked these by how directly each attribute drives an AI match in the audits we run. Identifiers and required fields come first, then the specific traits shoppers actually query.
FAQ
Q: Which attribute matters most for AI recommendations?
GTIN. It verifies your product is real. Without it, assistants often skip the listing as unconfirmed.
Q: How many attributes should my feed include?
As many specific, accurate ones as apply. More structured attributes mean more queries you can match. Prioritize identifiers, required fields, then descriptive traits.
Q: Where do I store extra attributes in Shopify?
Use metafields and product options, then map them into your feed. That's how you get material, compatibility, and other traits into the data assistants read.
Q: Do these attributes help both AI and Google Shopping?
Yes. The same structured attributes drive Google Shopping and AI recommendations, so improving them helps both.
Want a ranked audit of your feed attributes? Start at WRKNG Digital's agentic commerce readiness page.
