What is GEO?

The short version

SEO is about making your pages findable and rankable by search engines like Google. GEO is the same idea for AI: structuring your product data so answer engines like ChatGPT, Google's AI Overviews, and Perplexity can read it directly and cite it accurately in the answers they generate. Search engines hand back a list of links. AI answer engines generate an answer, and that answer is built from whatever product data the AI could actually read.

Why it matters to you

Shoppers increasingly ask an AI assistant "what's the cheapest 27-inch monitor" instead of typing it into Google. If your product data isn't structured in a way AI systems can read, you don't show up in that answer, or you show up wrong: a stale price, a mismatched spec, a link that isn't even yours, pulled from wherever the AI could actually find something. Good traditional SEO doesn't fix this on its own. It's a different, additional piece of work.

What "structured" actually means

Concretely, it comes down to a few things:

• Schema.org markup on every product page (Product, Offer, GTIN barcode) so an AI can read an exact price and spec instead of guessing from a page layout
• Explicitly allowing AI crawlers (GPTBot, ClaudeBot, PerplexityBot, Google-Extended) in robots.txt, most sites never think to check this
• Pages that render without needing JavaScript, so crawlers can actually read them
• An llms.txt file pointing AI systems at the pages that matter

How AI systems actually find your data

AI reads the web in three different ways. Background crawlers (Googlebot, OAI-SearchBot) build a cache on their own schedule, so there can be a gap between your page changing and an AI reflecting it. Live fetchers (like ChatGPT-User) read your page in the moment, triggered by an actual conversation, no staleness. Training crawlers (GPTBot) are separate again: they feed future models, not today's answers.

Either way, cached or live, an AI still has to interpret your page. Structure is what makes that reliable.

The one part you can't do on your own

Everything above, you could implement yourself, and you should. Marking up your own pages well will help you win queries where a shopper already wants to buy from you. But there's one answer your own product page structurally cannot give, however perfectly it's structured: "who's cheapest for this product."

A retailer's page can only ever state its own price. Answering the comparison question means seeing every retailer's catalogue at once, matched to the same product by barcode, and that is a large share of what people actually ask an assistant: cheapest 27-inch monitor, is this a good price, where should I buy this. That answer gets generated whether or not you're in it. Being absent from the underlying data doesn't keep you out of the comparison, it just means you're not one of the options when it happens.

That comparison layer is the part TrustRails publishes in machine-readable form, and it's the part no single retailer can produce about itself.

How TrustRails does this for you

We take the product feed you already publish and republish it with all of the above already in place, live, today. You can see it working at trustrails-compare.com, a real price-comparison site built entirely on this catalogue.