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Audit

You ask: “why did AI skip this product?”

Find what AI cannot read on your product pages

AEOsome reads every tracked product page the way an AI engine does, then lists the missing details, broken structured data and content gaps that keep a product out of answers.

Free scan, no account. Or start free

The Audit screen: what AI can and cannot read on each product page
Look at: the tiles. They count the pages that are healthy and the pages with issues found.

Answers checked in

  • ChatGPT
  • Google AI Mode

The moment

You know a product is missing from AI answers. You do not know why. The title is fine, the photos are fine, the page ranks on Google. But the engine could not find the material, the fit, or the answer to "is it waterproof", so it named a store that wrote those things down. The audit finds the sentence your page is missing.

Why this matters

AI engines do not rank pages, they pick products they can describe. A product with missing attributes or broken structured data is harder to describe, so it is passed over before price or reviews are weighed.

+693.4%

Traffic to retail sites from generative AI tools rose 693.4% year over year, 1 Nov to 31 Dec 2025.

Adobe, 2026-01-07

Adobe's own caveat applies here too: AI is a small share of traffic today. The pages that are readable now are the ones that get named as that share grows.

What you see in Audit

Which page should I open first?

Each page gets a score out of 100 from the checks AI shopping answers depend on, so the list starts with the page that costs you most.

A row of product pages, each photo carrying that page's audit score out of 100
Look at: the number on each photo. It is that page's score out of 100.

How many pages need work?

Every audited page counts as healthy or as one with issues, and the critical ones are counted apart. You see how big the job is before you open a single page.

The Audit tiles: how many product pages are healthy, how many have issues and how many are critical
Look at: Healthy, Issues Found and Critical.

What exactly is wrong on this page?

Each page lists its findings by severity, with the missing attributes and structured data problems behind them, split into Data, Content and Meta.

One audited product page: its Data, Content and Meta scores and its findings by severity
Look at: the Data, Content and Meta scores, then the coloured counts of high, medium and low findings.

Which questions should this product answer?

We map the questions shoppers ask AI to each product, so a gap reads as a lost answer, not a lint error.

How it works

What is read
The product's attributes, its structured data, and whether the page answers the questions shoppers ask AI about it
How often
Re-audited on a schedule that depends on your plan. On Free, every 7 days.
What it changes
Nothing. The audit only reads your pages.
Score
Out of 100, from Data, Content and Meta checks
Free check
The AI shopping readiness scan, from your store address, no account

Example store: Halden Outfitters

The Women's Fell Dasher Relay page scores 79 out of 100 in the audit.

Four steps, in order

  • Step 1

    Monitor

    Which products AI recommends, and who it names instead

    Previous step: Monitor

  • Step 2

    Audit

    What AI cannot read on each product page

    You are here

  • Step 3

    Optimize

    The exact change, ready to copy or apply

    Next step: Optimize

  • Step 4

    Verify

    The same questions asked again after a fix

    Next step: Verify

Ask your AI assistant instead

The same answers over the MCP server and the command line, on every plan, Free included.

Set up the MCP server or command line

Questions merchants ask

about Audit.

Find out which AI answers name your store

Enter your store address. We ask AI assistants the questions your shoppers ask, then show which answers name you, which name a competitor, and what to fix first.