Methodology

How we measure AI visibility

Most tools hand you a single number and ask you to trust it. We treat AI visibility as a measurement problem, and we show our work. Here is how the numbers in your report are produced, and where our edge stays proprietary.

AI assistants answer your customers' "who is best for this?" questions with a short list of recommended businesses. Measuring whether you are on that list sounds simple, but AI answers are noisy, they vary by engine, and they change over time. A number that ignores all of that is a guess with a decimal point. These are the principles that make our numbers trustworthy instead.

01

We ask the questions your customers actually ask

We generate the real prompts a buyer would type to find a business like yours, not one flattering query we picked. If the questions are wrong, every number after them is wrong, so this is where we start.

Live in every report
02

We measure many times, and show the uncertainty

Ask an AI the same question twice and you can get two different answers. We run every question multiple times per engine and report your mention rate with a 95% confidence interval, so you get an honest margin of error instead of a falsely precise score.

Live in every report
03

We prove a gap is real before we report it

If a competitor looks like it is beating you, we run a statistical significance test, corrected for the many comparisons in a report, before we say so. We do not call a coin biased after a single flip, and we do not report a lead that is inside the margin of error.

Live in every report
04

We check every major AI, and how much they agree

ChatGPT, Claude, and Gemini do not always agree. We measure across engines and report their level of agreement, so you can see where you are consistently recommended and where one engine is carrying, or missing, you.

Live in every report
05

Every number links back to the evidence

This is the one that matters most. Nothing in your report is a black-box score. Every finding traces back to the actual AI answer that produced it, so you, or a skeptical colleague, can read the exact response and verify it yourself.

Live in every report

What we refuse to do

  • Hand you a vanity score with no way to check it.
  • Report a competitor gap that is really just sampling noise.
  • Judge your visibility from a single AI answer.
  • Recommend keyword-stuffing tricks that AI engines ignore or penalize.
The frontier

Where our edge stays proprietary

A raw mention count can mislead: an easy question flatters you, a competitive one punishes you, and a model update can move everyone at once. Our research extends the measurement further, so a rating is comparable across businesses and stable through model changes rather than fooled by them.

We are transparent about our principles and every finding is verifiable, but the specific models behind this work are our own. It is the part we keep to ourselves.

In active development

See it applied to your business

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