Create a free account, enter your store URL, and Appario does the scan.
We check three things: whether AI agents can find your products, whether they’re allowed to understand and use your commerce data, and whether your product information is strong enough to earn a recommendation. Every check maps to something you can actually fix.
Why AI shopping is different.
30 seconds on what changed, what AI agents look for, and what a store score actually tells you.
Layer 1 — Discovery Readiness
AI shopping agents don’t browse your store the way a human does. They read structured data — the machine-readable signals embedded in your pages that tell them what a product is, what it costs, whether it’s in stock, and whether it’s worth recommending.
We check whether those signals exist, whether they’re complete, and whether they’re consistent. A price mismatch between your schema markup and your product page, for example, is enough for an agent to skip you entirely.
What we look at: Schema.org Product and Offer markup, JSON-LD block completeness, structured data consistency across price and availability, product description quality for conversational retrieval, image quality and alt text, and brand and identifier data (GTIN, MPN).
Layer 2 — Protocol Readiness
ChatGPT Instant Checkout and Google’s Universal Commerce Protocol run on specific technical handshakes. Your store either speaks that language or it doesn’t.
Think of it like a restaurant that wants to be listed on a delivery app. The food might be great — but if you haven’t set up the integration, you’re invisible to every order that comes through the platform.
We check whether your store has published the right manifest files, whether AI crawlers are permitted in your robots.txt, whether your product feed is formatted correctly and refreshing often enough, and whether your checkout configuration signals are in place.
What we look at: ACP manifest presence and validity, UCP file presence and validity, AI crawler permissions (ChatGPT-User, Google-Extended), product feed format and refresh rate, and Stripe agentic checkout configuration signals.
Layer 3 — Competitive Positioning
When an AI agent is deciding what to recommend, it’s comparing your product data against every other merchant selling the same thing. Completeness wins.
Missing variant data, no return policy, vague shipping information — these aren’t just gaps, they’re reasons for an agent to recommend someone else. We check how your data holds up against what AI agents need to make a confident recommendation.
What we look at: Product data completeness, variant handling (color, size, group attributes), shipping and fulfilment data, seller trust signals (return policy, privacy policy, terms), and marketplace seller attribution where applicable.
Your score
Every check produces a weighted result. We combine them into a single score out of 100, ranked by impact — so you always know what to fix first.
A score isn’t a grade. It’s a map. A 31 means the biggest gains are still ahead of you. A 74 means you’re well-positioned with a few things left to close. A 91 means you’re in the top tier — and we’ll tell you how to stay there.
What you get
Free scan — your score out of 100 and your top 3 issues, ranked by impact. A free account is required so your scan can be saved and monthly unpaid scan limits can be enforced.
Full Report ($49) — every issue on the ranked list, platform-aware remediation steps, drop-in prompts for AI assistants, and a downloadable PDF saved to your account.