How to Get Your Brand Cited by ChatGPT, Claude and Perplexity

Ask ChatGPT to recommend an agency, a tool, or a supplier in your category. Whoever it names is winning a form of distribution that did not exist three years ago, and most of their competitors have not noticed yet.

Here is what actually determines whether your brand is in that answer.

First, get a baseline

Almost nobody does this, and it makes the rest of the work unmeasurable.

Write down 15 to 25 prompts a real buyer would type — not brand searches, but the questions someone asks before they know who you are. “Best performance marketing agency for D2C brands.” “Who can help with Shopify conversion optimization.” “Agencies that do both Google and Meta ads.”

Run them across ChatGPT, Claude, Perplexity, Gemini, and Google AI Overviews. Record three things: whether you appear at all, how you are described when you do, and who gets named instead.

That last column is the useful one. It tells you which competitors the models currently consider the safe answer, and inspecting their footprint usually explains why.

Make your entity unambiguous

Answer engines have to resolve “your brand” into a single thing they can make statements about. When the signals conflict, the model does the safe thing and omits you.

Conflicts are usually mundane:

• The company name is written three different ways across your site, LinkedIn, and directory listings.
• Your homepage says one thing about what you do; your LinkedIn tagline says something noticeably different.
• Your service list on the site does not match the services described anywhere else.
• The founder’s name appears on the site but connects to nothing verifiable.

Fixing this is unglamorous and disproportionately effective. Pick canonical facts — legal name, category, service list, location, founder — and make every surface agree. Then encode them in Organization and Person schema so machines are not inferring from prose.

Write answers that survive being quoted

The mechanical part of AEO: models extract passages, not pages.

A passage gets extracted when it is self-contained. If your answer only makes sense after reading the two paragraphs above it, it is much less likely to be lifted cleanly into a response.

What works:

• A question-shaped heading, phrased the way a person would actually ask it.
• Directly beneath it, a 40 to 60 word answer that stands alone with no setup.
• Then the detail, examples, and nuance for human readers who want more.

This is not a trick. It is the same discipline as writing a good executive summary — the difference is that failing to do it now costs you visibility rather than just patience.

Concrete numbers help too. Content that includes specific figures and identifiable sources gets selected noticeably more often than content making unsupported claims, which stands to reason: a model quoting a specific statistic is on firmer ground than one repeating an adjective.

Let the crawlers in

You would be surprised how often this is the whole problem.

Check your robots.txt for GPTBot, ClaudeBot, Google-Extended, PerplexityBot, and CCBot. Some hosting platforms and CDNs block AI crawlers by default, and some re-enable that blocking after configuration changes without telling you. If you are blocked, nothing else in this article matters.

Then publish an llms.txt — a plain-text summary of who you are and what your key pages cover. It is not a magic ranking file, but it gives AI systems a clean, unambiguous description of your site rather than making them reconstruct one from your navigation.

Earn corroboration

The hardest part, and the one no amount of on-site optimization substitutes for.

Models weight claims that multiple independent sources agree on. If the only place on the internet asserting that you are a serious performance marketing agency is your own homepage, that is a weak signal. If the same characterization appears in directories, podcast appearances, guest articles, client mentions, and industry roundups, it becomes something a model will state confidently.

This is the part that takes months rather than weeks, and it is the reason AEO is not purely a technical exercise. Structure makes you extractable. Corroboration makes you citable.

Measure share of answer

Re-run your baseline prompts monthly. Track how often you appear, whether the description is accurate, and whether you are displacing the competitors who used to own those answers.

Watch for the specific failure mode where a model mentions you but describes you wrongly — as a single-channel vendor, in the wrong country, or with services you do not offer. That is usually an entity problem, and it is fixable.

The uncomfortable summary

None of this works if the underlying claim is not true. Answer engines are quite good at reflecting consensus, and manufacturing consensus is expensive and fragile.

The reliable path is the slow one: be genuinely good at a well-defined thing, describe it consistently everywhere, structure it so machines can quote it, and let independent sources confirm it. That has always been the durable version of visibility. AI search just made the structural half of it explicit.