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.
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.
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.
- 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
- 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
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.
Collects public web content that may be used to train future Anthropic models
Your future content is excluded from training datasets. Claude may still reference your brand from what it already learned.
Fetches pages when a Claude user asks a question that needs your page
Anthropic cannot retrieve your pages in response to user questions, which reduces visibility in user-directed answers.
Crawls and indexes content to improve the quality and relevance of Claude’s search results
Anthropic states plainly that this may reduce your site’s visibility and accuracy in Claude’s search answers.
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.
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.
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.
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.
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.
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.
What we actually measure
How often Claude names you across your prompt set
150 to 300 prompts, run repeatedly, scored across the spread
Who Claude recommends instead of you
Extracted from the same runs
Which domains Claude pulled from when answering
Logged from cited answers, then targeted directly
Whether what Claude says about you is correct
Manual review against your canonical positioning
Whether Claude searched, or answered from memory
Presence or absence of citations in the response
Whether all three Claude bots can reach and read you
Server log analysis, not just robots.txt inspection
How stable your presence is
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.
How we optimize a business for Claude
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.
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.
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.
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.
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.
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.
Frequently asked questions
Can I submit my business to Claude?
Can I pay to appear in Claude’s answers?
Which crawler should I allow?
Does Claude use Google?
Why does Claude say something wrong about my business?
How long does Claude optimization take?
Is Claude worth optimizing for if it has fewer users than ChatGPT?
How do you prove the work is having an effect?
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.