Agent-commerce readiness starts with observable merchant surfaces.
The planned retailer view is designed to organize merchant-side evidence from product, policy, request, cart, and checkout surfaces. It does not infer what an external model understood, preferred, recommended, or decided.
What's at stake for retailers
Merchant logs may contain request-level evidence for automated and AI-referred traffic that standard on-site analytics may not preserve or expose with the same request-level provenance. Cartograph is being built to organize evidence from server, CDN, origin, product, policy, cart, and checkout surfaces. It cannot observe decisions made off property.
Where retail storefronts break
- Variant identifiers or attributes missing across named product surfaces.
- Availability values that materially conflict across a feed, page, and structured data within the observation window.
- Shipping or return policies that the defined scanner or collector cannot fetch or parse.
- A recorded bot-control challenge or block on a request carrying agent-related evidence, without treating that evidence as proof of legitimate AI-agent traffic.
- Analytics views that omit log-origin request evidence for automated and AI-referred traffic.
How the planned retailer view is organized
The same Readable / Consistent / Transactable framework from the homepage, applied to your storefront. This is planned; no merchant is measured or scored today.
- Readable — can the defined scanner or collector fetch and parse your product pages, structured data, sitemaps, and policies? Not whether an external model understood, cited, or recommended them.
- Consistent — do your feed, page content, and structured data materially agree within a defined observation window and comparison policy? Not whether an external agent trusted, preferred, or rejected you.
- Transactable — do merchant-observed events, or a separately authorized synthetic diagnostic, show progression through the exact cart or checkout milestones in scope? Not proof of a complete journey or an order.
Who owns this on a retail team
- Ecommerce leaders — prepare to review the last merchant-observed milestone before cart or checkout.
- Product data and merchandising — prepare to compare named surfaces for missing attributes, ambiguous variants, inaccessible policies, and material conflicts.
- Analytics — prepare to evaluate the five v0.1 evidence labels and the planned request-level Unidentified Traffic metric when complete log coverage is available.