AI never gives thesame answer twice.
Your visibility score should know that.
Relevant measures how AI answers really behave and shows you exactly what to fix.
The list changes on every ask. Fictional brands, real behavior.
The list changes on every ask. Fictional brands, real behavior.
leading AI engines
ChatGPT
Claude
Gemini
Perplexity
Copilot
AI OverviewsSame question. Different answer. Every time.
Ask an AI engine the same question in a fresh session and the top three reshuffles. Brands slide, appear, vanish. Try it.
Illustrative demo · fictional brands
One run is an anecdote.
Sixty runs is a measurement.
We read the same question across phrasings, personas, engines and repeats, because the spread between readings, not any single reading, is where the truth lives.
The result is a visibility score you can actually trust, a number a CMO can defend when someone asks “says who?”
You win the question. You lose the conversation.
Real buyers don't ask once. They follow up, add constraints, raise objections. Watch the same brand across one buyer's session. A one-turn tracker only ever sees turn one.
Three turns. Three different outcomes. One score would have told you none of it. So we track the conversation, not just the prompt.
So your real score is knowable.
The next question is what to do about it.
We don't stop at the score. We tell you what to fix, and prove it worked.
Every recommendation is tied to a named source and re-measured after you act. Which of these four fixes would you try first? Most playbooks start at the bottom.
AI visibility, measured like science. Fixed like engineering.
Built on science.
Not guesswork.
One answer is one observation. We combine real data with repeated measurements to work out what is actually true. Four promises make that concrete.
Read the methodologyEight readings. Every one you can trust.
A number you can trust is evidence. A number that tells you how sure to be is a decision a CMO can defend.
Questions teams ask before they measure properly.
Straight answers on GEO, why AI answers change, and what makes this measurement different.
What is GEO (Generative Engine Optimization)?
GEO (also called AEO, or Answer Engine Optimization) is the practice of measuring and improving how AI answer engines like ChatGPT, Gemini, Perplexity, Claude and Copilot describe and recommend your brand. SEO used to optimize your rank in a list of links. GEO optimizes your place inside a single generated answer.
Why do AI answers change every time I ask the same question?
The same prompt can give you a different answer every time you run it. The answer also shifts with how you phrase it, your location, your conversation history and which model version you hit. That is why asking a question once is not a measurement. It is an anecdote.
Why does my brand's score differ across GEO tools?
Most tools track a small prompt list you hand them and read each prompt once. Different lists and one-off readings give different numbers, and none of them tell you how sure to be. Relevant works out which questions matter most in your category and asks each one many times, so the score is stable, comparable, and a score you can trust.
How is Relevant different from other AI visibility tools?
Relevant is built as a statistical measurement system, not a dashboard. We work out which questions matter instead of asking you for a list, and we ask the same question dozens of ways, across phrasings, personas, engines and conversation turns. Every metric comes with a score you can trust, and every recommended fix is ranked by how much it actually moved the needle.
Which AI engines does Relevant track?
ChatGPT, Google Gemini and AI Overviews, Perplexity, Claude and Microsoft Copilot, including default and reasoning tiers where they answer differently.
How many prompts do you track, and who chooses them?
We do. Instead of asking for your prompt list, we work out which questions matter most in your category and recommend a set weighted toward what people actually ask. For example, 50 prompts might cover roughly 41% of the questions people ask in your category, and we tell you exactly which prompts to add to cover more.
What does a confidence interval on a visibility score mean?
It tells you how sure to be. A score of 62%, plus or minus 6, means your real visibility is probably somewhere between 56% and 68%. If a weekly change falls inside that range, it is just noise, not a real drop, and we say so instead of alarming you over nothing.
Does Relevant tell us how to improve, or just report?
Both. Every report comes with ranked, specific recommendations tied to the source, engine and prompts they affect. We re-measure after you act, so each fix comes with a real, measured result instead of generic advice.
How fast do recommendations show results?
It varies by fix and engine. Because we ask the same questions the same way every time, you see movement as soon as the engines pick up the change, usually within days to a few weeks. And you see it with a clear sense of how sure we are, so you know whether the move is real.
Do you track by country and language?
Yes. We track answers by city and language wherever you compete, because visibility in one market tells you nothing about visibility in another. That includes deep coverage of markets like India, with local phrasings such as Hinglish, alongside global English tracking.
The answer reshuffles every time. Your strategy shouldn't. See your real visibility, with a clear sense of how sure we are, in one walkthrough.