Product feed enrichment
Product feed enrichment is the process of adding structured attributes to a product catalog beyond what merchants enter by hand — fit, silhouette, fabric behavior, occasion, style descriptors — so search engines, AI answer engines, and recommendation systems have real data to reason about.
In context
Most product feeds carry a title, a price, a category, and a few photos. Everything a shopper actually asks about — does it run small, will it work for a garden wedding, does it pair with wide-leg trousers — lives in the images and nowhere else. Enrichment extracts those traits into structured fields. Veristyle does this with computer vision, tagging 200+ style, fit, and color traits per product automatically.
Enrichment is upstream of everything: on-site AI product discovery needs the traits to match shoppers to products, and GEO needs them so answer engines can recommend the product for intent-shaped questions.
Related
Two nearly identical products — only one gets recommended by AI shows enrichment’s effect in practice; semantic product data is the output format that makes it machine-readable.