ASO - AGENTIC COMMERCESEO · AEO · ASO · AGENTIC READINESS
How your store appears in Agentic Commerce.
Legacy e-commerce sites are built for human eyes, not machine logic. When autonomous agents hit unstructured product data or schema drift, they flag the transaction as a risk and abort.
What you'll get
A 0–100 score with transactable threshold marked at 70 and peer benchmark.
Diagnosis of 6 areas, 6 shopping agents, access gates, and emerging protocols.
Failing products with Before / After JSON-LD code snippets you can verify.
Prioritized what-to-fix list ordered by impact, each opening with the direct action.
How your store appears in Agentic Commerce
This is the report for your store. It shows whether AI agents can verify your products and complete a purchase on your site.
How to read this report
Your score says whether agents can transact here. 70 or above means an agent can transact on that area. Below 70 needs work. Each area below shows its score. Then you see the products that fail, worst first. Then the fixes, in order, each starting with the action.
Send this report to yourself or someone else
Prioritize the fixes in this report to start climbing.
Orientative benchmark based on aggregate audits.
Want to talk through these findings?
6 areas scored
Each bar marks 70, the transactable threshold.
Red means critical, amber means needs work, green means transactable.
Will agents buy from you?
Estimated from your readiness signals. This is not a measured walkthrough rate. The reference-agent walkthrough attempts a real purchase path and reports where it aborts.
The fixes below move these. Agents that can only buy as a human will still buy blind until the data is machine-readable.
Can agents get in and find things
Two gates decide whether agents can enter: robots.txt and bot protection. Two discovery aids tell them what is here: llms.txt and the product sitemap.
Protocol readiness
Yes means agents using that protocol can transact here. No means they cannot yet.
These move as the fixes land. UCP moves first, with the product data fixes.
Products that fail
Open one to see exactly where its data fails, and what the fix looks like.
What to fix, in order
Each fix opens with what the scan found, then the steps. Fixes are ordered by severity: all critical failures first.
How the fixes map to your store: fixes 1 through 5 address catalog-wide data requirements that agents look for before executing checkouts.
Top fixes shown in detail. The full list unlocks when you connect your store.
Get these fixed
These fixes require integration with your store. Connect your store to apply them.
Connecting creates your account automatically, no signup form required. If you do not own the store, forward the connect link to your store owner.
Send this report to yourself or someone else. We will email a link to the report.
After the fixes: Create your Brand Agent
A Brand Agent is an AI shopping agent on your own site, under your own brand. It answers shoppers' questions and helps them buy, using your product data. The fixes above make that data readable and trustworthy, so the agent gives correct prices and stock instead of guessing. It holds context for your customer on your channels and over messaging platforms.
