Claude SEO: how to get your brand recommended by Claude

There is no business listing to claim, no dashboard to log into and no ad slot to buy. Claude decides what to say about your business entirely from what the rest of the web already says. Here is how that actually works, and what we do about it.

01The platform

Why Claude is the hardest AI platform to influence, and the most valuable to win

With Google you get Search Console. With ChatGPT you get Bing Webmaster Tools sitting underneath it. With most local platforms you can claim a listing and fill in the fields yourself.

Claude gives you none of that.

There is no Claude Business Profile. No submission form. No advertising product. No verification process. Anthropic has built no surface through which a business can tell Claude who it is.

Which leaves exactly one lever: what the rest of the internet says about you, and how clearly it says it.

That sounds like a disadvantage. It is the opposite, for two reasons.

It cannot be bought. No competitor can outspend you into Claude’s answers. The playing field is unusually level.

It compounds into everything else. The work that makes Claude describe you accurately, consistent entity signals, third-party corroboration, clear public positioning, is the same work that improves every other AI platform. Claude is the strictest examiner. Pass it and the rest tend to follow.

Claude also matters more than its raw user numbers suggest. It is heavily used by developers, consultants, researchers, lawyers and analysts: people who are frequently the ones producing the shortlist, writing the recommendation or advising the buyer. Being absent from Claude means being absent from a disproportionately senior and decision-making audience.

02How it answers

How Claude actually answers a question about your business

Claude answers from two distinct layers, and the difference between them changes everything about what you can influence.

Layer 1 · Training knowledgeStatic
What it already knows
What it is
What the model learned during training
When it applies
Default behaviour for most questions
Search provider
None, it is internal
Does it cite?
Rarely, and without links
How fast can you change it?
Months to a year, next training cycle
What influences it
Broad, repeated, consistent presence across the open web before the cutoff
Layer 2 · Live retrievalLive
What it looks up
What it is
What Claude fetches from the live web during the conversation
When it applies
When the question needs current information, or the user asks
Search provider
Brave Search powers Claude’s web search tool
Does it cite?
Yes, with source citations
How fast can you change it?
Days to weeks
What influences it
Current pages that are crawlable, relevant and clearly written
Training gaps take a model release to close. Retrieval gaps are usually fixable fast.

The practical consequence:

If Claude answers a question about your industry from training knowledge alone and does not name you, that is not a page-level problem. No amount of on-page optimization fixes it quickly. It means your brand was not a sufficiently well-established entity across the web when the model was trained.

If Claude searches and still does not surface you, that is usually fixable, and often fast. Crawler access, page structure, or simply nothing existing that answers the question clearly.

Diagnosing which of the two you are dealing with is the first thing we do, and it is the step almost everyone skips.

The three Claude crawlers, and why most sites get this wrong

Anthropic runs three separate crawlers with three separate jobs. They can each be allowed or blocked independently in robots.txt, and blocking one does not block the others.

ClaudeBot
What it does

Collects public web content that may be used to train future Anthropic models

If you block it

Your future content is excluded from training datasets. Claude may still reference your brand from what it already learned.

Claude-User
What it does

Fetches pages when a Claude user asks a question that needs your page

If you block it

Anthropic cannot retrieve your pages in response to user questions, which reduces visibility in user-directed answers.

Claude-SearchBotKeep open
What it does

Crawls and indexes content to improve the quality and relevance of Claude’s search results

If you block it

Anthropic states plainly that this may reduce your site’s visibility and accuracy in Claude’s search answers.

All threehonour robots.txt, including the user-initiated one
No IP rangesverify by user agent string instead
Per subdomaina root block does not cover shop. or blog.
Each is allowed or blocked separately in robots.txt

Three details worth knowing, because they catch people out:

All three honour robots.txt, including the user-initiated one. That is a meaningful difference from OpenAI and Perplexity, both of which warn that robots.txt may not apply to their user-triggered fetchers. With Claude, a robots.txt block genuinely removes you.

Anthropic does not publish IP ranges, and says IP blocking is unreliable because its bots use public cloud provider addresses. Blocking those ranges can stop the bot reading your robots.txt at all. Verify by user agent string instead.

Rules must be set per subdomain. A block on the root domain does not cover shop.yourdomain.com or blog.yourdomain.com.

The mistake we find on roughly half the sites we audit

Most businesses that block Claude never intended to.

It happens one of three ways. Someone read an article about AI training and added a blanket Disallow for ClaudeBot, not realizing the search and user bots are separate. Or a developer enabled an aggressive bot-protection mode on Cloudflare or a similar CDN, which silently blocks AI crawlers regardless of what robots.txt says. Or a WordPress security plugin did it by default and nobody looked.

The result is identical in all three cases: Claude cannot read the site, so Claude cannot recommend the business. Nothing in any analytics dashboard reports this. It is invisible until somebody checks the server logs.

A deliberate choice is different. Publishers with a genuine reason to keep their archive out of training datasets can block ClaudeBot while leaving Claude-SearchBot and Claude-User open. That keeps you visible in answers while opting out of training. It is a perfectly reasonable position, and almost nobody realizes it is available. The full list is in our which AI crawlers to allow.

03How it chooses

How Claude chooses which businesses to name

Here is where most articles on this subject start inventing things.

Anthropic publishes no ranking factors, no scoring model and no weighting for how Claude selects which businesses to mention. There is no equivalent of the Search Quality Rater Guidelines. Any agency presenting you with “the seven Claude ranking factors” has made them up.

So we separate what we know into three honest categories.

Documented
Confidence high

The crawler behaviour above. That Claude’s web search runs on Brave. That Claude cites its retrieval sources. That answers draw on training plus live retrieval.

Strongly inferred from testing
Confidence moderate

Entity clarity, third-party corroboration and consistency of description appear to drive whether Claude names a business. Well-structured reference sources carry disproportionate weight. Claude is noticeably more cautious than other models about naming specific businesses, and more likely to hedge or give category advice instead.

Unknown
Confidence none

The actual weightings. Whether review scores are read directly. How recency is balanced against authority. Why Claude names a business in one run and not the next.

Anthropic publishes no ranking factors, scoring model or weightings

What our testing consistently shows

We run prompt sets against Claude for every client and every audit. A few patterns hold up reliably enough to act on:

Claude hedges more than any other model. Ask most assistants for the best supplier in a city and you get three names. Claude will often describe what to look for instead. Getting named at all is a higher bar, which is precisely why it is worth more when it happens.

Description consistency outperforms description quality. A business described in the same words across fifteen sources is named more often than a business described brilliantly but differently on each. Claude appears to be looking for corroboration, not eloquence.

Structured reference sources punch above their weight. Wikipedia, Wikidata and established directories carry more influence than their traffic would suggest. Entity presence on those sources is one of the highest-leverage moves available.

Specificity beats superlatives. “Award-winning digital agency” tells a model nothing it can repeat. “SEO agency in Vancouver specializing in AI search visibility for law firms and dental clinics” gives it something usable. Claude repeats what it can verify, not what you claim.

Answers vary between runs. The same prompt can return different businesses. That variance is itself diagnostic: wide swings usually mean the model is uncertain about your category, which is an opportunity.

What we will not tell you

We will not give you a score for how Claude ranks you against a published algorithm, because no such algorithm has been published.

We will tell you how often Claude names you across a defined prompt set, who it names instead, which sources it pulls from, and whether that number moves after we work on it. That is measurable, repeatable and honest.

It is also considerably more useful than a made-up score.

04What we measure

What we actually measure

01
Named rate

How often Claude names you across your prompt set

How we capture it

150 to 300 prompts, run repeatedly, scored across the spread

02
Competitor set

Who Claude recommends instead of you

How we capture it

Extracted from the same runs

03Matters most
Citation sources

Which domains Claude pulled from when answering

How we capture it

Logged from cited answers, then targeted directly

04
Description accuracy

Whether what Claude says about you is correct

How we capture it

Manual review against your canonical positioning

05
Retrieval vs training

Whether Claude searched, or answered from memory

How we capture it

Presence or absence of citations in the response

06
Crawler access

Whether all three Claude bots can reach and read you

How we capture it

Server log analysis, not just robots.txt inspection

07Matters most
Answer variance

How stable your presence is

How we capture it

Standard deviation across repeat runs

Two of these matter more than the rest.

Citation sources is the one that turns strategy into a task list. Once you know which twelve domains Claude pulls from when answering questions in your category, you stop guessing. Getting onto those pages becomes the work.

Answer variance is the one nobody else reports. A business named in 8 out of 20 runs is in a very different position from one named in 8 out of 20 consistently every week. The first is on the edge of recognition; the second is reliably mid-pack. The full method is in measuring visibility across repeat runs.

05How we optimize

How we optimize a business for Claude

01

Access audit

Before anything else, we confirm Claude can physically read your site.

  • Server log analysis for ClaudeBot, Claude-User and Claude-SearchBot hits, which is the only reliable evidence
  • robots.txt and llms.txt review across every subdomain
  • CDN, WAF and firewall rule inspection, since this is where most silent blocks live
  • Render testing, because content that only exists after JavaScript execution may not be read

This step takes days and regularly resolves the whole problem on its own.

02

Baseline measurement

We build a prompt set specific to your industry, services and market, then run it against Claude repeatedly to establish where you actually stand. Without this there is nothing to improve against and no way to prove the work later.

03

Entity consolidation

This is the core of Claude optimization and the part that most directly drives results.

  • A single canonical description of your business, written once, used verbatim everywhere
  • Consistent name, address and contact details across every property you control
  • sameAs consolidation in your structured data, pointing at every profile you own
  • Author and founder entities established with credentials and cross-linked bylines
  • Wikidata and structured reference presence where notability supports it

The goal is unglamorous and specific: make it easy for a model to determine what your business is, and hard to get it wrong.

04

Source targeting

We take the citation source list from Step 2 and work through it methodically. Listicles, directories, reference pages, industry publications and community platforms that Claude demonstrably reads. This is digital PR aimed at a specific, evidenced target list rather than at links in the abstract.

05

Content and structure

Pages written so that retrieval works in your favour.

  • Answer-first structure, with the direct answer in the first 40 to 60 words under each heading
  • Self-contained passages, because retrieval operates at passage level and a paragraph beginning “as mentioned above” is useless out of context
  • Server-side rendering, standard in our web design builds, so content exists in the HTML rather than after execution
  • Specific, verifiable claims with sources, since Claude repeats what it can corroborate

Then we re-run the prompt set and compare. Monthly.

06The wider strategy

Where Claude fits in the wider AIO and GEO strategy

Claude is one platform among six, and optimizing for it in isolation would be a mistake.

Research analyzing millions of AI citations found that around 91% of cited URLs appear in only one model. Strong performance on one platform tells you very little about the others.

Which is why we never sell single-platform optimization. Claude work sits inside our wider generative engine optimization program, alongside ChatGPT, Gemini, Perplexity, Copilot and Grok. Underneath it all sit the same foundations as our SEO agency work: technical health and content strategy.

The useful thing about Claude specifically: because it is the strictest and least gameable of the six, it works well as the benchmark. If Claude describes your business accurately and recommends you confidently, your entity foundations are genuinely sound.

Everything else gets easier from there.

07FAQ

Frequently asked questions

Can I submit my business to Claude?

No. Anthropic provides no business listing, submission form or dashboard. Claude builds its understanding of your business from publicly available information, which is why entity work across the wider web is the only route in. You can see whether Claude names you today in about a minute.

Can I pay to appear in Claude’s answers?

No. Claude carries no advertising product, and there is no paid placement of any kind. This is one of the reasons it is worth investing in: the results cannot be bought by a better-funded competitor.

Which crawler should I allow?

At minimum, allow Claude-SearchBot and Claude-User. Those two determine whether Claude can find and read you when answering questions. ClaudeBot is the training crawler, and blocking it is a legitimate choice if you have reason to keep your content out of training datasets. Just be aware it is a separate decision. Every bot is covered in our guide to GPTBot, ClaudeBot and the rest.

Does Claude use Google?

No. Claude’s web search runs on Brave Search rather than Google or Bing. That matters, because your Google rankings do not transfer directly and a site can rank well on Google while being poorly represented in Claude’s retrieval layer.

Why does Claude say something wrong about my business?

Almost always because something inaccurate or outdated exists publicly, or because nothing authoritative exists at all and the model has filled the gap. The fix is to correct the source, not to argue with the output. We trace which sources are producing the error and address them directly.

How long does Claude optimization take?

Access problems can resolve within days. Entity consolidation and source targeting typically show movement in eight to sixteen weeks. Training-layer presence is a longer game, measured across model releases rather than months.

Is Claude worth optimizing for if it has fewer users than ChatGPT?

Raw user numbers understate it. Claude skews heavily towards developers, consultants, analysts and professional services: the people who build shortlists and advise buyers. For B2B and professional services in particular, the audience quality is high.

How do you prove the work is having an effect?

We establish a baseline named rate across a fixed prompt set before starting, then re-run the same set monthly. You see the number, the competitors named alongside you, and the sources Claude cited. It is the same methodology we document in our prompt-set measurement guide.
Free AI visibility audit

Find out what Claude currently says about you

Most businesses have never checked. A fair number are blocking Claude entirely without knowing it, and almost none have any idea which competitors get named in their place.

We will run your prompt set, check your crawler access, and show you exactly where you stand.