LLM SEO Tools
An LLM SEO tool runs prompts against ChatGPT, Gemini and Claude on a schedule and records whether your brand appeared and which sources were cited. It measures presence in answers, not rank position.
What our data shows: across 4,163 answers, brands appeared 4.8% of the time and the rate was near-identical across engines. Citation rates were not: 98.9% on Gemini against 73.6% on ChatGPT.
An LLM SEO tool runs a set of prompts against language models on a schedule and records two things: whether your brand appeared in the answer, and which sources the model cited. That is the whole category, whatever the marketing says. It measures presence in a generated answer rather than position in a ranked list, which is why a conventional rank tracker cannot be repurposed for it.
This page explains what the tools do and what to look for. If you want a ranked comparison of specific products, our best GEO tools roundup tests fourteen of them against real citation data. What follows is the layer underneath: what these measurements actually look like, using our own.
What the numbers actually look like
We run AI visibility scans as part of our product, so rather than quote a vendor's benchmark we can report ours. Between 8 July and 24 August 2026 we collected 4,163 answers across 1,088 distinct queries for 24 businesses, on ChatGPT, Gemini and Claude.
| Engine | Answers | Brand mentioned | Rate |
|---|---|---|---|
| ChatGPT | 1,157 | 58 | 5.0% |
| Gemini | 1,868 | 90 | 4.8% |
| Claude | 1,138 | 53 | 4.7% |
| All engines | 4,163 | 201 | 4.8% |
Two things stand out, and both cut against how the category is usually sold.
The engines are nearly identical. 5.0%, 4.8% and 4.7% is not a meaningful spread. Much of the tooling in this space is positioned around per-engine strategy, on the premise that ChatGPT and Gemini reward different things. On brand mentions, at least for the businesses we track, they do not. If a tool is selling you separate optimisation tracks per engine, ask what difference it is claiming and how it was measured.
The baseline is low. Under 5% is the normal state, not a failure. A brand appears in roughly one answer in twenty. That matters when a vendor promises to lift your AI visibility by some large multiple, because a move from 4% to 8% is two extra mentions in fifty answers and is well inside the noise of a small sample. Ask how many answers the claim is based on before treating it as a result.
Where the engines genuinely differ
The real divergence is not who gets mentioned. It is whether the model shows its sources at all.
| Engine | Answers | Cited a source URL | Rate |
|---|---|---|---|
| Gemini | 1,868 | 1,847 | 98.9% |
| Claude | 1,138 | 1,122 | 98.6% |
| ChatGPT | 1,157 | 852 | 73.6% |
Roughly a quarter of ChatGPT answers carried no attributable source. Gemini and Claude cited something almost every time.
This has a direct consequence for tool selection. A tool that infers your visibility by counting how often your domain appears in citation lists will systematically understate ChatGPT, because a quarter of the time there is no citation list to appear in. If ChatGPT matters to you, check whether the tool reads the answer text for brand mentions or only parses the citations. Those are different measurements and they will disagree.
The three categories of tool
Products in this space do one of three jobs. Most claim all three and are genuinely good at one.
| Category | What it does | What it cannot tell you |
|---|---|---|
| Visibility tracking | Runs your prompts on a schedule, records mentions and citations over time. | Why the number moved, or what to do about it. |
| Content optimisation | Scores or rewrites pages for the structures models tend to quote. | Whether models can reach your page, or whether anyone else references you. |
| Citation monitoring | Watches which third-party sources the models draw on in your topic. | Whether you can realistically get onto those sources. |
Visibility tracking is the category most people mean by an LLM SEO tool, and it is the most useful of the three, with the caveat that it is a thermometer. It tells you the temperature. It does not heat the room.
What to check before you buy
Which models, and which tier? This is the question almost nobody asks and it changes everything. Our own figures above come from the fast, inexpensive tiers of each provider, because running thousands of scheduled prompts on flagship models is expensive. That is a real limitation on our data and we would rather state it than let you assume otherwise. Ask any vendor the same question, because a tool quietly using a cheaper tier is not measuring what your customers see.
Does it read the answer or just the citations? Covered above. On ChatGPT these give materially different answers.
How many prompts, how often? Brand mentions sit under 5%, so small samples are mostly noise. A weekly scan of ten prompts produces numbers that will bounce around for reasons that have nothing to do with your marketing.
Are the prompts fixed? If the prompt set changes between runs, the trend line is meaningless. Comparability over time is the entire value of tracking.
Does it tell you what to do next? Most do not, and the honest ones admit it. Which leads to the part that matters.
What no tool in this category can do
Measurement is not movement. Models mention brands they encountered in the sources they were trained on or retrieved from, which means the lever is being written about on sites those models draw from. That is earned coverage on relevant third-party publications, and no amount of on-page optimisation substitutes for it.
This is why we treat AI visibility as an output of outreach rather than a discipline of its own. Our own take on the wider question is in GEO vs SEO, and if you want the practical version, how to get cited by ChatGPT covers what actually moves the number. To check where you currently stand without buying anything, how to check if ChatGPT mentions your brand walks through doing it by hand.
A tracking tool is worth having once you are doing that work, because otherwise you cannot tell whether it is landing. Buying one before you are doing the work gives you a precise measurement of nothing changing. If you are weighing paying someone to do the work instead, AI search optimization services covers what they deliver and what it costs.
Frequently asked questions
What is an LLM SEO tool?
A tool that runs prompts against language models on a schedule and records whether your brand appears and which sources were cited. It measures presence in generated answers rather than rank position.
How often do AI answers mention a specific brand?
Across our 4,163 answers, 4.8%. The rate was near-identical by engine: ChatGPT 5.0%, Gemini 4.8%, Claude 4.7%. Under one answer in twenty is the normal baseline.
Do all AI engines cite their sources?
No. Gemini cited a source in 98.9% of answers and Claude in 98.6%, but ChatGPT in only 73.6%. Tools that measure visibility purely from citation lists will understate ChatGPT.
Can an LLM SEO tool improve your AI visibility?
No. It measures. Mentions follow from being covered on the sources models draw on, which is an outreach problem rather than a tooling one.
What is the difference between LLM SEO and GEO?
They name the same activity. GEO is the more common term among SEOs, LLM SEO among tool vendors.
Method
Figures cover 4,163 successfully completed answers collected between 8 July and 24 August 2026, across 1,088 distinct tracked queries for 24 businesses, on ChatGPT, Gemini and Claude. A further 25 runs errored and are excluded. "Brand mentioned" means the tracked brand appeared in the answer text. "Cited a source URL" means the response carried at least one source link. Each engine was queried on its fast, low-cost model tier rather than its flagship, which keeps scheduled scanning affordable but is a genuine limitation: citation behaviour on flagship models may differ, and these numbers should not be read as describing them.