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AI Visibility

How to get cited by ChatGPT

When someone asks ChatGPT for a recommendation in your category, you want to be named. Here's the practical playbook for getting cited by ChatGPT, Perplexity, and the other AI systems people now ask first.

The short answer

To get cited by ChatGPT, you need four things: content written as clear answers to the questions people ask, consistent descriptions of your brand everywhere it appears online, citations from sources AI already trusts, and machine-readable structure (schema, FAQ markup, an llms.txt file). Together they make AI confident enough to name you.

Why ChatGPT cites some brands and not others

When ChatGPT recommends a brand, it's drawing on patterns it learned from across the web plus, increasingly, live sources it retrieves. It names brands it has seen described clearly, consistently, and authoritatively. Getting cited isn't luck — it's the result of giving the model every reason to be confident about who you are and what you're best at.

The playbook

Answer the real questions, in writing. Find the exact questions your customers ask AI, and publish the clearest answer on the internet — question as the heading, direct answer first. This is the content AI quotes.
Describe yourself the same way everywhere. Your site, your profiles, your directory listings should all say who you are in consistent language. Mixed signals make the model uncertain — and uncertain models stay silent.
Earn trusted citations. Get mentioned and linked by sources the model already trusts. Authority transfers — being referenced by a trusted source makes you one.
Add machine-readable structure. Schema markup, FAQ structure, and an llms.txt file tell AI systems plainly what you do, who you serve, and why you matter. You're handing the model a clean summary to cite.
Welcome the AI crawlers. Make sure your robots.txt allows GPTBot, ClaudeBot, PerplexityBot, and the rest. Many sites accidentally block the very crawlers they need.

What doesn't work

Keyword stuffing, thin content, and tricks don't move AI systems the way they once nudged search rankings. Models are trained to synthesize trustworthy information — they reward clarity and authority, not manipulation. The brands that win are the ones that genuinely are the best answer and make that easy to verify.

How to know if it's working

The test is simple: ask. Open ChatGPT, Claude, and Perplexity and ask the questions your customers would — "best [your category] in [your city]," "who should I hire for [your service]." See if you're named. That's your AI visibility baseline, and it's exactly what I measure in a free AI visibility scan.

See if ChatGPT recommends you today

I'll ask ChatGPT, Claude, Gemini, and Perplexity about your brand and category, and send you a report showing exactly where you appear, where you don't, and how to fix it.

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Frequently asked questions

Publish content that directly answers the questions your customers ask, describe your brand consistently everywhere it appears online, earn citations from sources AI already trusts, and add machine-readable structure like schema markup and an llms.txt file. Together these give ChatGPT the confidence to name your business when it's relevant.

No. ChatGPT recommendations are not paid placements — they're synthesized from what the model has learned and can retrieve about brands. You can't buy your way into an answer, but you can earn it through LLMO: structured content, consistent entity signals, trusted citations, and clear machine-readable data.

Usually because the model doesn't have a clear, consistent, authoritative picture of your brand. If your business is described differently across the web, lacks structured content answering customer questions, or isn't cited by trusted sources, the model stays uncertain — and uncertain models don't name you. Fixing those signals is the work of LLMO.

It varies. Machine-readable fixes like schema and llms.txt can be picked up relatively quickly by systems that retrieve live data, such as Perplexity and ChatGPT search. Deeper authority — the kind that gets you named from the model's training — builds over months as your consistent signals and citations accumulate across the web.

An llms.txt file is a simple text file on your website that gives AI systems a clean, structured summary of what your brand does, who it serves, and why it matters — often formatted as direct questions and answers. It's an emerging standard that makes it easier for AI to understand and accurately cite your brand.

Start here · The LLMO Playbook
How to Get Cited by AI
Read the playbook →