How to Get Your Business Recommended by ChatGPT, Perplexity and Google AI

To be recommended by an AI assistant, your business has to be recognisable as a distinct entity, clearly associated with a category, and corroborated consistently across the sources those systems draw on. There is no submission form and no ranking to climb. The model synthesises from available information, so the work is making that information clear, consistent and plentiful.

Key takeaways

• AI assistants produce a shortlist, not a ranked page — you are either named or you are not.
• Consistency across sources matters more than it does for conventional search rankings.
• Blocking AI crawlers in robots.txt or at the network layer makes everything else pointless.
• Stating plainly who you are not for measurably helps models place you correctly.
• Progress is measured by sampling prompts over time, not by a rank tracker.

Why this is a different problem from ranking

Traditional search produces a list. If you are eighth, you exist — somebody scrolling will see you. There is a path from eighth to third to first, and the path is legible.

An AI assistant asked to recommend an agency, a contractor or a supplier returns three or four names in a paragraph. There is no eighth place. The question is binary: did the model name you?

What determines that is not position but confidence. The model needs to recognise your business as a specific entity, be confident about what category it belongs to, and find enough consistent corroboration to mention it without hedging. A business the model is uncertain about simply does not get named — the uncertainty resolves as omission.

First: check you are not blocking the crawlers

This sounds obvious and is routinely the problem. If your robots.txt blocks GPTBot, ClaudeBot, PerplexityBot or similar, or your CDN has AI bot protection switched on, your content cannot inform those systems at all.

Cloudflare in particular has shipped AI crawler blocking that defaults to on for some configurations, and plenty of site owners have it enabled without knowing. Check two places:

• yourdomain.com/robots.txt — look for Disallow under any AI user agent
• Your CDN or host's bot management settings — look for anything named "AI bots", "AI scrapers" or "AI training"

Every other tactic in this article is wasted effort while a crawler block is in place.

Entity clarity: being a thing the model recognises

Models work with entities — distinct, identifiable things they have information about. A business that appears under slightly different names, with varying descriptions and inconsistent details, is harder to treat as a single entity than one described identically everywhere.

What to make consistent, everywhere it appears:

• The business name, in exactly one form. Not "Smith Plumbing", "Smith Plumbing Ltd" and "Smith's Plumbing" across different profiles.
• A one-sentence description of what the business does, reused verbatim rather than rewritten per platform.
• Contact details — the same phone number and address format on the site, on directories, on social profiles.
• Category language — describe yourself in the words someone would use when asking about your category, not in internal branding language.

On the site itself, Organization schema should state this explicitly: legal name, URL, logo, contact points, the services offered, and sameAs links to every profile you control. That last field is how a model connects the entity across sources.

Category definition: explaining the space you occupy

Models answering "recommend a good X" need to be confident what X is and that you are one. Pages that assume the reader already knows the category provide nothing to match against.

A short, plainly written definition of your category — in the language a customer would use — gives the model something concrete. Not marketing language. A sentence that would survive being quoted out of context.

This is also where llms.txt earns its place: a plain-text file at the root of your domain summarising what the business is, what it does, who it serves and how to contact it, written for machine consumption rather than persuasion.

If you want to know how AI assistants currently describe your business, that is something we can check and show you on a free strategy call. Often the answer is "they don't, yet" — which is itself useful to know. Get in touch.

Decision criteria: the counter-intuitive part

Stating plainly who you are not a good fit for improves how reliably models recommend you.

The reasoning is straightforward once stated. A model deciding whether to name your business is implicitly deciding whether you match the user's situation. A site claiming to serve everyone gives it no boundaries to test against, so the safest behaviour is to omit you. A site that says clearly "we work with service businesses, not e-commerce" and "we do not build mobile apps" makes the match assessment easy — and the model becomes more willing to name you where you do fit.

In practice this means publishing:

• If-then statements — "if you need X alongside Y, this is a fit" in plain language
• Explicit exclusions — the work you do not take on
• Buyer segments — who typically hires you and what outcome they get
• Honest comparisons — how you differ from the realistic alternatives

Content structure that survives extraction

Everything that makes content extractable for featured snippets also makes it usable to a generative model. The overlap is almost total.

Pattern	Why it helps
Question-phrased headings	Matches how users actually phrase prompts
40–60 word standalone answers	Can be lifted without surrounding context
Specific figures with dates	Gives the model something concrete to cite
Comparison tables	Structured data the model can read directly
Named sources for claims	Raises confidence in the statement
Visible last-updated dates	Signals the information is current

The underlying principle: write so that any given paragraph makes sense alone. A passage beginning "as discussed above" is unusable out of context, and out of context is exactly where it will be read.

Corroboration across sources

A model's confidence rises when several independent sources agree. Your own website is one source and, on its own, a weak one — every business claims to be good at what it does.

What strengthens the picture:

• Directory listings with identical details across each one
• Profiles you control — social accounts, professional listings — all describing the business the same way
• Third-party mentions where they occur naturally
• A Google Business Profile that is complete, verified and matches everything else

None of this requires buying links. It requires that the information about your business is consistent wherever it already exists, which for most businesses means an afternoon of correcting details that drifted apart over several years.

How to measure whether it is working

There is no rank tracker for this, and anyone selling you a precise number is overstating what is measurable. The honest method is sampling.

Write down 20 to 30 prompts a potential customer might realistically use. Run them across ChatGPT, Perplexity, Gemini and Claude. Record for each: were you named, how were you described, and was the description accurate.

Repeat monthly. You are watching three things move — whether you get named at all, whether the description is correct, and whether you appear for a wider set of prompts over time. It is a sample, not a measurement, and should be described as such.

Frequently asked questions

Can I pay to appear in ChatGPT recommendations?

No. There is no advertising placement in the recommendation itself. What you can influence is the information those systems draw on — your site, your structured data, your profiles and how consistently they describe you.

How long does GEO work take to show results?

Longer than paid ads, comparable to SEO. Models are retrained and their retrieval indexes refreshed on their own schedules, so changes do not appear immediately. Expect months rather than weeks, with the crawler-access and consistency fixes having the fastest effect.

Does this replace SEO?

No. It sits on top of it. AI systems draw heavily on content they can crawl, parse and trust — the same foundation conventional SEO builds. A site that cannot be crawled or has no substantive content has nothing for either channel to work with.

Is this worth doing for a small local business?

It depends where your customers come from. If most arrive through local map searches and referrals, local SEO and your Google Business Profile deserve the budget first. If customers research providers before reaching out, that research increasingly happens in an AI assistant.

What if an AI describes my business incorrectly?

That usually traces to inconsistent or outdated information somewhere in the sources it draws on. Correcting the underlying sources — your site, your profiles, your directory listings — is the available lever. There is no direct correction mechanism, which is worth knowing before anyone promises you one.

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Want to know how AI assistants currently describe your business? We will run the prompts and show you the actual answers on a free strategy call — including when the answer is that you do not come up at all.

Book a free strategy call, or read more about our GEO service and how AEO differs from it.