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How to Get Recommended by Claude

Claude would rather say nothing than say something it can’t back up.

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Claude is built to be cautious about claims it can’t verify, which means vague marketing copy gets you nowhere and clear, checkable facts get you everywhere.

Claude is the careful one

Every AI tool has a personality, whether its makers intended that or not, and Claude’s comes across as more cautious than most about stating things it can’t back up. Ask it to recommend a specific business and, more often than the others, it’ll hedge, qualify its answer, suggest you verify details yourself, or decline to name just one option if the evidence in front of it feels thin or overly promotional. That’s by design, Anthropic has built Claude to lean towards being useful without overstating its confidence. For a business owner, that caution cuts both ways. It means Claude is harder to win over with polished marketing language alone, phrases like ‘award-winning’ or ‘industry leading’ tend to read as unverifiable claims rather than evidence, and Claude is more likely to quietly discount them. But it also means that once you’ve given Claude something genuinely checkable, it’s often more willing to state it plainly, because the caution is about unverifiable claims, not about being negative toward businesses generally.

What actually convinces a cautious model

Specific, boring, checkable facts do more work with Claude than anywhere else on this list. Opening hours. A real price range. How long you’ve been trading. The actual qualifications your team holds. The postcode areas you cover. None of that is exciting copy, but it’s exactly the kind of detail a cautious model can treat as fact rather than opinion. Consistency matters just as much, if your ‘12 years trading’ claim on your website doesn’t match what a directory listing says, or your service area on one page contradicts another, that’s the kind of contradiction that pushes a careful model further toward hedging rather than committing to a recommendation. The businesses that come across best to Claude tend to be the ones that write about themselves the way they’d fill in an official form, plainly, accurately, without embellishment, then repeat those same facts identically everywhere else they appear online.

Where Claude shows up beyond the chat window

It’s worth remembering Claude isn’t only the chat interface at claude.ai. Anthropic’s models sit behind a growing number of workplace tools, research assistants and customer-facing products that businesses build using their API, which means someone using a piece of software to shortlist suppliers, research a service, or draft a recommendation might be running on Claude underneath without ever seeing the Anthropic name at all. That matters for procurement-style searches in particular, someone at another company quietly researching who to hire, rather than a consumer chatting casually. Being ‘Claude-legible’, clear, factual, consistent, isn’t just about pleasing one chatbot, it’s increasingly about being legible to a layer of software sitting underneath tools you’ll never see the inside of.

How to write for a model that double-checks everything

Go through your own website and flag every unsubstantiated superlative, ‘leading’, ‘best’, ‘number one’, and either replace it with the real fact behind the claim or cut it. If you genuinely are the longest-established firm in your trade locally, say since when, and make sure that date matches your Companies House record and your ‘about us’ page word for word. If a claim has a source, a certification body, an award you actually won, an accreditation, link to it or name it properly rather than just asserting it. Then check your details match across every listing you appear in, directories, socials, review sites, because a cautious model treats matching independent sources as far stronger evidence than one confident sentence on your own homepage.

Common questions

The things people ask us first

Why would Claude refuse to recommend anyone rather than just pick someone?
Because Anthropic has deliberately tuned it to avoid stating things confidently when the underlying evidence is thin, rather than picking an answer just to seem helpful. If Claude only has one vague, self-written page to go on for a whole category of business, it may well tell the user it can’t confidently recommend one and suggest they check reviews themselves. That’s frustrating if you’re the business missing out, but it’s consistent, and it means the fix is straightforward, give Claude clearer, more independently verifiable evidence to work with, rather than trying to argue with how the model behaves.
Does Claude use live web search like Perplexity does?
Claude can use web search in some contexts and products, but it isn’t built around live citation the way Perplexity is, and its underlying caution about unverifiable claims applies whether or not it’s actively searching. That means the fixes that help Perplexity, fresh dated content, direct citable claims, help here too, but the deeper lever for Claude is consistency and factual specificity across everywhere your business is described, not just having one very current page. Treat freshness as a bonus with Claude, not the main event.
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