How AI tools choose which sites to recommend

Recommendation is retrieval, not memory

When someone asks an AI assistant "what's a good invoicing tool for freelancers?", the model doesn't consult a private ranking of every product in the category. For anything current, assistants like Perplexity and search-connected ChatGPT run a live retrieval step: they issue searches, fetch a handful of pages, and compose an answer from what those pages actually say.

That has a blunt implication: to be recommended, you first have to be retrieved. If your site doesn't surface for the underlying searches — because the pages are thin, client-rendered, or blocked — the model never sees you, and no amount of product quality changes the answer.

What survives the retrieval step

• Pages that state plainly what the product is, who it is for, and what it costs — the exact facts an answer needs to include.
• Direct-answer copy: a sentence the model can quote is worth more than a paragraph it has to interpret.
• Specific intent pages — comparisons, use cases, pricing — that match the question as asked, not just your brand name.
• Server-rendered HTML. Retrieval fetches are fast and rarely execute your JavaScript.
• Corroboration: third-party mentions, reviews, and consistent details across pages make a claim safe to repeat.

Why models hedge — and how trust breaks the tie

Assistants are penalised for confidently recommending something that turns out to be wrong, so they hedge when the evidence is thin. A site with no about page, no visible team, no pricing, and template copy reads as unverifiable — and unverifiable products get dropped from answers or buried in a "there are many options" list.

Trust signals are how you become the safe answer: an identifiable entity (Organization schema, a real about page), claims that match across your site, visible pricing, and pages that answer the follow-up questions a cautious buyer would ask next.

See how you do on the questions that matter

You can test this directly: ask an assistant the questions your buyers ask and see who gets named. A free Robot Visible scan does the systematic version — it grades whether your site gives retrieval something to find and answers something worth citing, then ranks the gaps by impact.