BigCommerce and Feedonomics Ship Catalog Enrichment for Agentic Commerce

On September 29, 2026, Commerce, the NASDAQ listed parent company of BigCommerce, Feedonomics, and Makeswift, announced two separate AI driven catalog enrichment tools, one at the Feedonomics layer and one native inside BigCommerce itself. Sharon Gee, SVP Product for AI at Commerce, framed the motivation in a single sentence worth repeating exactly: "AI agents can only answer questions about your products as well as your data allows." That is the entire thesis behind this release, and it is worth taking seriously even if you already have a structured data strategy, because the two tools being announced solve different parts of the problem and most merchants currently running one have not evaluated the other.

Two tools, two different jobs

The distinction that matters here is not AI generated content versus hand written content. It is where the enrichment happens and how far downstream it reaches. Feedonomics enrichment is built for a merchant who is already managing a multi channel feed, pushing the same catalog to several advertising and marketplace destinations, and who needs the enriched content to propagate consistently across all of them. BigCommerce's native tool is built for a merchant whose primary need is a better product page and better underlying structured data inside the platform itself, without standing up a separate feed management workflow at all.

Why this matters beyond SEO

We have written previously about what a catalog has to look like to be legible to an AI shopping agent at all, and the core argument there still holds: an agent that cannot parse your product into structured attributes does not surface it as an option, and there is no equivalent of a low search ranking to warn you that it happened. What this announcement adds is a concrete, vendor shipped answer to the "how do we actually produce that structured content at catalog scale" problem, rather than leaving every merchant to solve it with custom tooling or manual content work. A catalog with ten thousand SKUs and incomplete feature bullets on eight thousand of them is not a problem a content team fixes by hand in a reasonable timeframe. Automated enrichment at the platform or feed layer is the only way most catalogs close that gap before it costs them agent visibility.

The build versus buy question this actually raises

If you are running headless commerce on BigCommerce or already use Feedonomics for multi channel feed management, the practical question these tools raise is whether vendor side automated enrichment is good enough to replace a custom enrichment pipeline you may have already built, or whether it is a baseline layer you run underneath your own refinements. The honest answer depends on three things worth checking before you decide either way. First, whether the generated content actually reflects your brand voice and factual accuracy at the level your QA process requires, since automated generation at catalog scale will produce some percentage of content that needs a human review pass regardless of which vendor generates it. Second, whether the taxonomy mapping Feedonomics applies matches the categorization your advertising and marketplace accounts already depend on, since a mismatch here can silently break campaign structure that took real time to build. Third, whether your existing export and import workflow, if you built one before this native tool existed, is actually more expensive to maintain than switching to the native path, which is a real migration cost that should not be assumed away just because the new tool is more convenient on paper.

What a headless merchant should actually verify before adopting either tool

A headless storefront already separates presentation from the underlying commerce and catalog data, which means adopting either enrichment tool should not require a storefront rebuild. What it does require is confirming that your storefront's data layer actually consumes the enriched fields these tools produce, structured data, feature bullets, FAQ content, rather than only the legacy title and description fields your templates were originally built against. A common failure mode with this kind of catalog upgrade is the backend enrichment shipping correctly while the frontend template never renders the new fields, which means the AI visibility improvement these tools are meant to deliver silently does not reach the actual rendered page or feed output. Confirm this with a handful of test SKUs before rolling enrichment out across a full catalog, not after.

When this applies to your stack

If you are running BigCommerce or a Feedonomics managed multi channel feed and have not evaluated whether your product data is actually structured well enough for an AI agent to represent it accurately, this release is a reasonable forcing function to run that audit now rather than later. Contra Collective's headless commerce and platform migration work includes exactly this kind of catalog data audit and enrichment pipeline design for enterprise merchants moving to or already running on composable commerce architecture.

FAQ

Do I need both Feedonomics enrichment and BigCommerce catalog enrichment, or just one? It depends on your channel footprint. If you only need better product content inside your BigCommerce storefront itself, the native tool is simpler and avoids an export and import cycle. If you are pushing the same catalog to multiple advertising and marketplace destinations and need consistent enriched content across all of them, Feedonomics enrichment is built for that multi channel propagation in a way the native tool is not.

Does AI generated product content need human review before publishing? Yes, treat it the same way you would treat any automated content generation at scale. Spot check a representative sample for brand voice and factual accuracy before applying enrichment across a full catalog, and budget for an ongoing review process rather than assuming generation quality is uniform across every SKU category.

Which AI platforms does Feedonomics enrichment target? The announcement names Google, Meta, Amazon, and eBay as advertising and marketplace destinations, plus Gemini, ChatGPT, and Copilot as AI platform destinations for the enriched, structured content.

Will enrichment actually show up on my storefront if I do not update my templates? Not necessarily. Confirm that your storefront's data layer and templates actually render the newly enriched fields, structured data, feature bullets, FAQ content, rather than only the original title and description fields, before assuming the enrichment is reaching your live pages or feeds.