ChatGPT Visibility Report

Updated 2 October 2026.

How it works

Enter a real buying prompt (like “best CRM for a small agency”) and your brand. This ChatGPT SEO tool puts the question to OpenAI’s ChatGPT model, reads back its ranked recommendations, and tells you whether you’re named, where you rank, and which competitors it surfaced instead. It is the closest thing to a rank check for AI answers — not a ranking in any index, but the order in which one model volunteers brands in your category.

Being named is the new front page. If you’re missing, the citation playbook shows how to earn the mention, and the AI Citability Checker scores whether your pages can be quoted.

What the report measures, exactly

The tool sends your prompt to OpenAI’s model through the API (the model used is printed on every result; the default is gpt-4o-mini) with an instruction to answer as ChatGPT would answer a buying question and to return its recommendations as a ranked list. It then checks that list for your brand. You get three things: named or not, rank N of M (your position among the M brands it recommended), and the full list of what it recommended instead. That list is the useful part when the answer is no: it is the set of brands the model has learned to associate with your category. People often search for a “ChatGPT rank tracker”; this is the single-check version of that idea — your rank today, not a series over time.

Two honest caveats. First, this is the model’s answer without web browsing. The ChatGPT app can switch on search, use your chat history and run a different model, and any of those can change the list. The report is the baseline view: what the model produces when it answers from training alone rather than from a live search. Second, language models are not perfectly consistent: the leading names are usually the most repeatable, the tail of the list least so. Identical prompts return the same result for about three hours; after that a fresh answer may differ at the margins.

The three results you can get

1. Named near the top

You are one of the first two or three recommendations. The model has absorbed enough consistent description of you to put you forward unprompted. Protect it: keep the pages that describe what you do and who you are for plain, current and quotable, and keep earning third-party mentions, because that is what the model is summarising.

2. Named, but low in the list

You exist to the model but are not its first thought. Look at who sits above you. In our experience the brands at the top tend to be the ones with the heaviest comparison and review coverage; what is certain is that nothing here is bought — there is no ad auction inside a model’s answer. The fix is comparative content that names you alongside them, in the places the model learns from, so the association strengthens.

3. Not named at all

The common case for younger or niche brands, and the result worth acting on. The list shows who the model thinks your category is. Start with how those brands are described on the web and where. Then run your own site through the AI visibility checker, which scores the eighteen structural signals that decide whether an engine can even read and quote you, and fix what it flags before you invest in mentions.

Which prompts to test

• The category prompt: “best [category] for [who you serve]”. This is the one that wins or loses customers. Being named here matters more than anything else.
• The comparison prompt: “[competitor] vs [competitor]”, without your name in it. If the model volunteers you as a third option, you are in the consideration set.
• The alternatives prompt: “alternatives to [market leader]”. The cheapest place for a smaller brand to get named.
• The problem prompt: “how do I [job your product does]”. Tells you whether the model connects your product to the problem at all.
• Skip the vanity prompt. Asking “what is [your brand]” nearly always returns something and proves nothing about whether buyers are sent to you.

Five to ten prompts give a readable picture. If you want the same prompts checked on Google’s side, the AI Overview citation checker reads the live Google AI Overview for a keyword and tells you whether your domain is cited.

How to earn the recommendation

There is no tag, feed or submission that puts a brand into a language model’s recommendations. What works is the same thing that has always built a reputation, done in a form the models can read.

• Be described consistently. One clear sentence about what you are and who you are for, repeated on your own site, your profiles and your listings. Models learn associations from repetition.
• Get into the comparisons. Review sites, “best of” roundups and comparison articles are the texts models lean on for buying questions. The citation playbook covers how to earn those placements.
• Make your own pages quotable. Lead with the answer, state concrete facts (prices, limits, integrations, dates) and structure them so a passage can be lifted. The citability checker scores a page for exactly this.
• Stay reachable. If your robots.txt blocks AI crawlers, the pages that describe you best are closed to them, which rules those pages out of live-search answers and makes them less likely to be picked up in future training data. The AI visibility checker tests this.

What this tool does not do

It checks one prompt against one brand at a time and keeps no history; every report is a snapshot. As a ChatGPT SEO tool it queries OpenAI’s model without web browsing, so it does not reproduce a ChatGPT-with-search session. It does not ask Perplexity, Claude or Gemini, and it does not read Google AI Overviews, which is what the citation checker is for. And it cannot tell you why the model chose a brand; it can only show you who was chosen.

Which AI visibility check do you need?

Four different questions all get called “AI visibility”, and they need different tools. This is the whole set, so you can go straight to the one that answers yours.

• Can AI engines read and cite this page? The AI visibility checker scores how machine-readable a single page is across eighteen signals. It does not ask any AI engine anything.
• Does ChatGPT actually name my brand? The ChatGPT visibility report puts one of your buyers’ questions to an OpenAI model and lists the brands it recommends instead of you. It runs without web browsing, so it shows the model’s baseline view rather than a ChatGPT-with-search session. (you are here)
• Is that answer changing week to week? The AI visibility tracker measures share of model — your brand against named competitors across a set of prompts, over time.
• How is any of this measured properly? Measuring AI visibility is the full method, including what a single spot-check cannot tell you.

Free, and what the paid tier adds

Every report here is free with no account and no card, a free plan rather than a trial, alongside 77 other free tools that do not expire. Pro at $49 a month adds the Prompt Observatory: a fixed set of buyer prompts for your category, re-asked every week, with a record of which brands were named. The Observatory currently queries Perplexity and Claude, not ChatGPT, so use this page for the ChatGPT snapshot and the Observatory for the weekly trend on the other two engines.

Frequently asked questions

Does ChatGPT recommend my brand?

Enter a buying prompt and your brand. The tool puts the question to OpenAI’s ChatGPT model and reports whether your brand appears in its recommendations, at what rank, and which competitors it names instead.

Is this the same answer I would get inside the ChatGPT app?

Close, but not identical. The tool calls OpenAI’s model through the API with the same question and no web browsing, so it reflects what the model recommends from what it has learned. The ChatGPT app can add live web search, your chat history and a different model, which can change the list. Treat the report as the model’s baseline view of your category.

Why does ChatGPT recommend competitors and not me?

Language models recommend brands they have seen described consistently and authoritatively across the web: review sites, comparison articles, communities and editorial coverage. If competitors are named and you are not, the gap is usually earned mentions and clearly structured, quotable pages, not anything you can fix with a tag.

What does rank mean in the report?

The model is asked for a ranked list of recommendations. Rank is your position in that list and total is how many brands it named. Rank 1 of 8 means you were the first of eight recommendations; rank 0 means you were not named at all.

Why did I get a different result when I ran the same prompt again?

Identical prompts return the same cached result for about three hours. After that the model answers fresh, and language models are not fully deterministic, so the order and the tail of the list can shift between runs. Treat one check as a sample and look for the pattern across a few prompts.

Does this track changes over time?

No. Each report is a single snapshot and nothing is saved. The Prompt Observatory in Pro re-asks a fixed set of buyer prompts every week and records who gets named, but it currently queries Perplexity and Claude, not ChatGPT.

Can I check a competitor instead of my own brand?

Yes. The brand field accepts any name, and the full list of recommendations is shown either way, so one report tells you everyone the model names for that prompt.

Which prompts should I test?

Use the questions a buyer would actually type: best X for Y, X vs Z, is X worth it, alternatives to X. Test five to ten across your category. Being named for the generic category prompt matters most; being named for your own brand name tells you little.