Your best shoppers are arriving through agents. Can the agents read your store?
AI-referred shoppers are becoming the highest-intent traffic a store sees — but only when agents can discover, trust, and transact with the storefront. Cartograph shows retail teams exactly where that breaks, using evidence from what agents actually do on your store.
What's at stake for retailers
The discovery and comparison step is moving inside AI agents, off your analytics. A shopper now often arrives pre-qualified by an agent — or never visibly arrives at all. If your store is hard for an agent to read, you don't lose a click; you simply never enter the consideration set, and you can't see it happening in your funnel.
Where retail storefronts break
- Product variants agents can't disambiguate — size, color, bundle, and configuration.
- Availability that's stale or inconsistent across feed, page, and structured data.
- Return and shipping policies a human can read but an agent can't parse.
- Bot controls that block legitimate shopping agents alongside scrapers.
- Analytics that can't separate AI-referred, agent-assisted, bot, and human activity.
What Cartograph shows you
The same Read / Trust / Transact read from the homepage, applied to your storefront — and grounded in observed agent behavior, not a surface checklist.
- Read — can agents actually parse your products, structured data, sitemaps, and policies?
- Trust — when your feed, page content, and structured data disagree, do agents lose confidence and drop you from consideration?
- Transact — can an agent-like session move through cart, tax, shipping, and payment surfaces without failing?
Who owns this on a retail team
- Ecommerce leaders — see where AI-mediated journeys break before cart or checkout.
- Product data and merchandising — find the missing attributes, ambiguous variants, and feed gaps that cause agents to misread products.
- Analytics — classify AI-referred, agent-like, bot, and human commerce activity with evidence labels.