Feedonomics pushes AI data enrichment to keep product catalogs visible

Feedonomics says brands need enriched, structured product data to show up in AI-driven discovery, not just traditional search. The company points to a phased rollout at Euro Car Parts that expanded AI data enrichment across nearly 25,000 products.

Why it matters: - AI agents are changing how shoppers discover products. - Brands that rely on keyword-era SEO and basic feed fields risk being left out of AI-generated results. - Enriched product data can improve visibility across commerce channels and search experiences.

What happened: - Business Reporter published an article featuring Feedonomics and its view on scaling AI data enrichment across a full product catalogue. - Sharon Gee, SVP, Product and AI at Commerce, said: “AI reads your data and it decides. If your catalogue isn’t in the mind of the agent, you’re invisible.” - Feedonomics said brands should add structured Schema.org information, make content readable by humans and machines, and keep product data accurate and consistent across the catalogue.

The details: - Feedonomics described traditional feed management and SEO as built for a keyword-driven search environment with fixed product attributes and manually optimized listings. - The company said data enrichment expands basic labeled attributes into fuller descriptions that match how customers search in natural language. - Modern feed management platforms can ingest data from multiple sources, standardize and enrich it, and sync updates across commerce channels. - Feedonomics said its platform combines those functions with AI Data Enrichment to help brands scale product optimization while maintaining data quality and accuracy. - Euro Car Parts used a phased rollout, starting with a small number of products before expanding AI data enrichment across nearly 25,000 products. - The article links to more information.

Between the lines: - The message is that AI visibility now depends as much on data structure as on keywords. - A phased rollout suggests brands may need to test enrichment on a limited set of products before expanding across larger catalogs. - Feedonomics is positioning feed management as infrastructure for both traditional commerce and AI-driven discovery.

What's next: - Brands are likely to keep adding structured metadata and enrichment as AI search becomes more common. - Feed management platforms may compete more on automation, data quality and channel synchronization. - The article argues that broader catalog coverage will matter as AI agents become a larger source of product discovery.

The bottom line: - Product data that is enriched, structured and consistent is becoming a prerequisite for being found by AI agents.