Catalog & data

Constraint query

Definition

A shopping request framed by conditions the answer must satisfy — a device it must fit, a system it must work with, a situation it must handle — rather than by a product category alone.

Defined in Compatibility Data: The Attributes AI Agents Rely On Most.

Related terms

Product catalog enrichment: The process of turning product facts into structured, validated fields (attributes, identifiers, variant data, offer and policy data) and keeping them accurate across every channel that reads them, so people and AI systems can filter, compare and quote them.
Structured attribute: A named, machine-readable field with a discrete value — material: leather, sleeve_length: short — as opposed to the same fact buried in a marketing sentence.
Category metafield: A Shopify metafield tied to a category in the Standard Product Taxonomy (where it's called a product attribute), such as size, color or material, with predefined values that can be linked to variant options and reused across products.
GTIN: The GS1 identifier behind UPC (GTIN-12), EAN (GTIN-13) and ITF-14 barcodes. It identifies a specific trade item, so the same product can be matched across retailers, marketplaces and shopping engines.
Shopify metafield: A custom structured field on a Shopify product, collection, or variant — the mechanism most mid-market merchants use to add attributes without a separate PIM.
Category attribute template: A fixed, reusable list of the attribute fields every SKU in a given category must carry — e.g. every hiking boot gets material, closure, waterproof rating, sole type, weight — built once per category and then applied to every SKU in it.

All 164 terms

Put a number on your catalog debt

What missing attributes, thin copy and bad variants cost you in lost conversions each year.

Calculate catalog debt Product Data Enrichment for AI