Agentic commerce is what happens when AI systems stop being search tools and start being buyers. Instead of surfacing options for humans to evaluate, AI agents set a goal, process structured data, and complete a transaction end to end.
You’ve already seen the early version of this: people asking ChatGPT or Gemini what to buy. The next step — agents that actually complete the purchase on your behalf — is being actively built right now by Google, OpenAI and others.
When that shift lands at scale, the discovery-to-checkout journey stops being about capturing human attention. It becomes about being machine-readable, structured and surfaceable by an agent making fast, logic-based decisions.
Why this matters for marketplace brands
If you sell on Amazon, bol.com, Zalando or any other major marketplace, you’re already operating in an environment where algorithms mediate discovery. That’s not new. What is new is the depth of that mediation.
Today, a shopper searches, scrolls and decides. Tomorrow, an agent searches, filters against a set of criteria — price, availability, delivery speed, product specifications, return policy — and makes the call without any human in the loop.
Two things follow from this:
1. Unstructured product data becomes a competitive liability.
An AI agent can’t interpret a vague bullet point or read brand equity into a lifestyle photo. It reads structured attributes: category, dimensions, materials, certifications, compatibility, return window. Brands with clean, complete, well-structured product data will be surfaced. Brands without it will be invisible, not penalised, just absent from the agent’s decision.
2. Price becomes the default arbiter — unless you give agents something better to work with.
If all an agent can see is price and availability, it will optimise on price. Brands that have invested in differentiated content, loyalty structures, premium positioning and service attributes (fast shipping, extended returns, sustainability credentials) will only benefit from that investment if those attributes are structured and machine-readable.
The brands that win in agentic commerce are the ones whose data was already ready.
The marketplace-specific challenge
Marketplaces add a layer of complexity here. Your product data doesn’t live solely on your own website it lives inside platform ecosystems that each have their own data standards, content requirements and algorithmic logic.
On Amazon, Rufus (Amazon’s AI shopping assistant) is already influencing product discovery through conversational search. It surfaces answers based on structured listing data, reviews, Q&A content and seller attributes. If your listing can’t answer a shopper’s question – asked conversationally, not as a keyword – you lose the recommendation.
On Zalando, product content standards are tightening. More granular attributes, more complete size and fit data, more precise materials information. This isn’t arbitrary admin overhead. It’s platform infrastructure being built for a world where agents need clean data to make decisions.
The pattern is consistent across platforms: richer structured data leads to better placement. Agentic commerce accelerates that dynamic, it doesn’t create it from scratch.
What brands should actually do now
This isn’t a call to panic or to rip apart your current setup. It’s a call to prioritise the right things.
Audit your product data quality. Not just whether it’s filled in, but whether it’s accurate, complete and structured to answer the questions shoppers actually ask. If an agent asked “what is this made of?” or “will this fit a 180cm person?” Could it find the answer in your listings?
Align your content to platform requirements, fully. Optional attributes are becoming de facto required ones. Brands that treat attribute completion as a box-ticking exercise will find themselves outcompeted by brands that treat it as a commercial priority.
Think about what makes you defensible beyond price. Service quality, sustainability data, compatibility information, warranty terms — anything that adds decision-relevant value beyond the lowest number in the price column. Structure it. Expose it.
Watch how major platforms evolve their AI features. Amazon’s Rufus, Zalando’s AI-powered search, TikTok Shop’s discovery layer… these are all early signals of where agentic commerce lands in the marketplace context. Pay attention.
The window is now
Agentic commerce at full scale is still a few years out. But the foundations — structured data, complete listings, machine-readable content — are things you should be building today regardless. They improve your performance now, in existing search and recommendation systems. And they position you to compete in the environment that’s coming.
The brands that lose in agentic commerce won’t have done anything wrong. They’ll just have waited too long to do the right things.
At Avanty, our marketplace team within naYan, helping brands get their marketplace content and data strategies right is exactly what we do. If you want to understand where your product data stands – and what it would take to make it agent-ready – get in touch.
