What's the full GEO and AEO checklist for an online store?

What actually belongs on a GEO/AEO checklist (and why most checklists get it backwards)

A real GEO/AEO checklist ranks fixes by whether they help an AI model parse, trust, and quote your page — not by how impressive they look in a generic SEO audit. Most "AI SEO checklists" floating around right now are old technical-SEO checklists with "AI" pasted on top, and they miss that answer engines read a page differently than a classic search crawler does.

We built StoreCited by scanning Shopify and DTC stores against exactly the criteria below, so this list is ordered the way we've actually seen it move a store's AI Visibility Score: schema and product-data gaps first, because they block AI from reading you at all. Authority and freshness signals come later — they only decide who gets picked once two stores are saying roughly the same thing.

Work through the eight sections below in order. Each one names the fix and, more importantly, why an AI model specifically cares — not just "Google likes this."

1. Structured data: the non-negotiable foundation

Without machine-readable schema, an AI crawler has to guess your price, stock status, and rating from rendered HTML — and it frequently guesses wrong, or skips your page for a competitor's cleaner one. This is the single highest-leverage fix on the entire checklist.

Check for:

• Product schema on every product page — price, currency, availability, SKU, brand. schema.org/Product defines the required and recommended fields.
• FAQPage schema on any page answering real buyer questions (schema.org/FAQPage).
• Organization schema on the homepage, naming your brand as a distinct entity.
• BreadcrumbList schema so AI systems can understand your category structure.

Our own audit of 24 Shopify DTC brands found that only 4% emit FAQ schema at all — see the full methodology in our research. If you've never checked, assume you're in the 96%. Start with adding product schema on Shopify and the deeper structured-data guide for Shopify before moving on.

2. Product-data completeness AI can actually quote

Schema only works if the underlying data is specific — a Product schema wrapped around a two-line, adjective-only description gives an AI model nothing concrete to repeat back to a shopper. Completeness beats cleverness here.

Fill in, per product:

• A full description with specifics — materials, dimensions, what it's actually for — not "premium quality, you'll love it."
• GTIN/MPN/UPC where you have one. It's both a trust signal and a matching key across catalogs.
• Size, material, and care details in visible text, not only inside an image or size-chart graphic AI can't read.
• Price and shipping terms stated in text, not rendered exclusively via a JavaScript widget.

If an AI shopping assistant can't tell what a product is made of or who it's for from your page text, it either drops the detail or quotes a competitor who spelled it out.

3. Reviews AI models can actually read

Star ratings are worthless to an AI answer engine unless they're marked up as AggregateRating and Review schema — if reviews only render as star icons inside a third-party widget, machines can't see them at all, no matter how many five-star reviews you have.

This is the biggest gap we've found in the wild. Across the 24 brands in our research, 88% displayed star ratings to human visitors, but 0% exposed them as structured data. That's not a minor technical miss — it's an entire trust signal that never reaches the model reading your page.

Checklist:

• AggregateRating schema with a real rating value and review count.
• Individual Review entries where you can add them, not just an aggregate number.
• Confirm your reviews app renders schema server-side — some only inject it via client-side JS a crawler may never execute.

Walk through the fix in how to add review schema on Shopify.

4. Comparison and "alternative to" pages

When a shopper asks an AI assistant "X vs Y" or "best alternative to X" and you have no page answering that exact question, the AI defaults to whoever does have one — usually a competitor, or a third-party roundup site, never you.

Build honest comparison content for:

• Your top three to five direct competitors, framed plainly as "[Your Brand] vs [Competitor]."
• "Alternative to [bigger, incumbent brand]" if you compete against a category leader.
• Real pros and cons on both sides. An AI model — and a skeptical shopper — can tell when a comparison page is one-sided marketing copy, and it quietly undermines trust in everything else on your site.

We hold our own comparison pages to that same honesty bar, and it's the reason people trust them enough to cite.

5. Authority and trust signals (E-E-A-T for AI)

AI systems weigh whether a source is trustworthy before quoting it over a competitor saying the same thing, and that judgment leans heavily on entity signals: who you are, whether you're linked from elsewhere, whether your "About" page reads as real.

Minimum bar:

• Organization schema with sameAs links to your genuine social profiles and any press mentions.
• An actual About page — not a stock paragraph, a real explanation of who runs the store and why it exists.
• Findable contact information, not just a form with no other detail behind it.
• No fabricated reviews, invented "as seen in" badges, or made-up author personas. These erode trust fast once discovered, and AI systems are only getting better at cross-checking claims.

This is the slowest section to fix, and the one most stores skip entirely. It's also disproportionately what separates a 90+ AI Visibility Score from a 60.

6. Freshness signals

When two pages say roughly the same thing, AI systems tend to lean toward the one that looks recently maintained — a page last touched in 2022 loses to a competitor's page dated this quarter, even if yours is genuinely more thorough.

• Add dateModified to Article/BlogPosting schema, and keep it honest — don't fake it on unchanged content.
• Show a visible "last updated" date to human readers too, not only buried in schema.
• Put key pages — guides, comparisons, pricing — on a quarterly refresh cadence instead of "publish and forget."

7. llms.txt and AI crawler access

llms.txt is a simple root-level file that points AI systems to your most important, crawlable content. Think of it as a signpost, not a ranking boost — and it does nothing if the crawlers can't reach your site to begin with.

Before anything else, confirm access:

• robots.txt isn't quietly blocking GPTBot, ClaudeBot, PerplexityBot, or Google-Extended. This is the single most common silent killer we see.
• Cloudflare or another CDN's bot-fight rules aren't lumping AI crawlers in with spam bots and 403-ing them.
• sitemap.xml exists, is current, and is submitted in Google Search Console.
• An llms.txt file exists at your root, pointing to your best guides, product categories, and FAQ pages.

Google documents how AI features interact with crawling and indexing if you want the primary source, and OpenAI's site is the place to confirm current crawler behavior directly — this space moves fast, and any specific crawler policy is worth re-checking every few months rather than trusting a screenshot from last year.

How to prioritize this checklist

Fix in the order below: structured data and product-data gaps block AI from reading you at all, so they come before authority and freshness, which only matter once AI can see your content clearly.

Guessing which of these seven you're actually missing wastes time you don't have. A free AI Visibility Score scan checks your store against this exact list in under a minute and tells you which gaps to close first — no guesswork, and no email required just to see the score.