TL;DR
An AI visibility score is the share of analyzed AI answers that name a brand. That is how an AI visibility score is calculated, and every tool then picks what the two counts hold. In the 28 days to 30 October 2026, on 7 AI platforms, our project's most-named rival appeared in 3,701 of 8,953 answers, 41%. As a Share of Voice over nine brands, it read 21%. The denominator moved the score by half. Three platform sets moved it by 2 points.
On this page
In the 28 days to 30 October 2026, our project's most-named rival brand read 41.3% as visibility and 20.8% as Share of Voice. Both numbers count the same answers. A buyer who compares two tools sees gaps of this kind. This guide states the formula, names what each of its two counts holds, and divides one brand five ways. The margin of error is in our guide on how accurate the numbers are. The metrics beside the score are in our guide on AI visibility metrics.
How is an AI visibility score calculated?
An AI visibility score is the number of analyzed answers that name the brand, divided by the number of analyzed answers. An analyzed answer is what one AI platform returned to one prompt in one market on one day. The tool read it in full. The brand counts once per answer, however often the answer repeats its name.
Our own project tracks the category we sell in, AI visibility tools, and monitors five rivals. In the 28 days to 30 October 2026, on 7 AI platforms, it analyzed 8,953 answers. Profound, the most-named rival, appeared in 3,701 of them. Its score is 3,701 divided by 8,953, or 41.3%. Per 100 analyzed answers, 41 name Profound and 59 do not.
That is the whole formula. Everything that makes two tools disagree sits in the two counts: which answers reach the numerator, and which answers the denominator holds. FullReach AI calls this score visibility. The methodology states how it collects the answers behind it.
What goes into the numerator?
The numerator holds every analyzed answer whose text contains the brand's name, or a spelling the tool knows for it. Three choices change it:
- Spellings. A tool matches the exact name, or a list of spellings. In the same 28 days, Otterly AI appeared in 3,339 answers. In 3,333 of them, the name appeared as a second spelling that the project registered. A tool that knows only the registered name loses up to 3,333 of Otterly AI's 3,339 answers.
- Namesakes. A loose match counts another company. The analysis proposed "FullEnrich" as a spelling of our brand, and we rejected it, because FullEnrich is another company. A tool that accepts such a proposal adds another company's answers to the numerator.
- The label. Some scores count only the answers that recommend the brand. Our guide on AI visibility metrics defines recommendation status and the decision it supports.
What goes into the denominator?
The denominator is the set of answers, or of mentions, that the tool divides by. The table divides Profound's 3,701 answers from the same 28 days by five denominators.
| Denominator | What it holds | Count | Profound's score |
|---|---|---|---|
| Analyzed answers | Every answer a platform returned and the tool read | 8,953 | 41.3% |
| Attempts | The analyzed answers, plus the 4,697 attempts that returned no answer | 13,650 | 27.1% |
| Answers that name a monitored brand | The answers that name one of the five rivals or our brand | 4,792 | 77.2% |
| Mentions of monitored brands | One mention per brand per answer, over the six monitored brands | 12,652 | 29.3% |
| Mentions, with three detected brands added | The six, plus the three most-named brands the project does not monitor | 17,767 | 20.8% |
The first row is visibility. The fourth row is Share of Voice, which our guide on Share of Answer and Share of Voice computes by hand on 20 answers. The second row counts a platform's failure as an answer that named nobody. The third row ignores every answer in which no monitored brand appears.
The fifth row halves the visibility of the first row. In the same 28 days, the analysis detected three brands that the project does not monitor. Semrush appeared in 2,471 answers, Ahrefs in 1,614 and SE Ranking in 1,030. A tool that counts every detected brand in its Share of Voice divides by 17,767 mentions. Profound then falls from 29.3% to 20.8%. The guide on Share of Voice explains when the share is the right number at all.
How much does the platform set move a score?
On the three larger sets, the platform set moved the leader by 2 points and a small brand by 4 points. The table counts the same 28 days to 30 October 2026 over four platform sets. The last column names the entry plan that counts the same set, from the records we keep of each tool.
| Platforms counted | Analyzed answers | Profound | AthenaHQ | Entry plan with this set |
|---|---|---|---|---|
| ChatGPT, Google AI Mode and Gemini | 3,923 | 40.1% | 9.8% | Semrush AI Visibility |
| ChatGPT, Gemini, Perplexity, Copilot, Google AI Mode and Google AI Overviews | 7,647 | 39.2% | 10.4% | Ahrefs Brand Radar |
| All 7 | 8,953 | 41.3% | 13.8% | FullReach AI |
| Grok only | 1,306 | 53.9% | 33.9% | None |
Profound read 39.2% to 41.3% on the three larger sets. On Grok alone, Profound read 14.7 points above the lowest of them. AthenaHQ read 9.8% on three platforms and 13.8% on all of them. Grok named AthenaHQ in 33.9% of its 1,306 answers.
See which AI platforms name your brand today, before you compare two scores.
No account. Ten questions on three AI platforms.
Why do two tools disagree by half on one brand?
Two tools disagree by half when they divide by two different denominators, or count two different labels. In the 28 days to 30 October 2026, Profound read 41.3% as visibility. Only 1,427 of the same 8,953 answers recommend Profound, so a score of recommendations reads 15.9%.
Our records of Peec AI, Semrush AI Visibility and Ahrefs Brand Radar, read on 29 September 2026, list the metrics each tool reports. None of the three records states what its score divides by. Peec AI is an AI search analytics tool for marketing teams and agencies. It tracks visibility, position, sentiment and Share of Voice across AI platforms, and sells each self-serve plan with three models of the customer’s choice. Our guide on the Semrush toolkit states how Semrush computes its score.
This guide holds the prompts fixed. Our guide on why numbers differ measures what a change of prompts does.
How do you read a score from any tool?
Ask four questions before you compare a score with another tool's score, or with last month's score:
- What is the denominator, and how many answers does it hold? A score without its answer count hides both the formula and the margin of error.
- Which brands are on the list, and did the list change? A new rival lowers every share and changes no answer.
- Which platforms and which prompts count, and did a platform fail on some days?
- How does the tool match the name? Ask for its spellings and for the namesakes it rejected.
FullReach AI states the denominator on the tile. The visibility tile reads the answers that name the brand over all analyzed answers. The recommendation tile reads the recommended mentions over all classified mentions.
Two tiles of the Overview, on sample data. Each tile states its own denominator under the number: answers for visibility, mentions for recommendation.
See your own numerator and denominator today, on every AI platform. The first analysis runs right away.
7 days free, no credit card required
What to do next
- Write the denominator beside the score you have. When the tool does not state one, ask the vendor for the answer count.
- Compare the score only with the same tool's earlier score. A level from another tool compares two formulas, not two months.
- Pick the metric for your decision with our guide on AI visibility metrics, and fix the rival list before you report a share.
FullReach AI side by side with Peec AI, Otterly AI, Profound, Semrush AI Visibility, Ahrefs Brand Radar, Promptwatch, Searchable, Scrunch, Evertune, Rankscale and AthenaHQ.
Keep reading.
Updated
Which AI visibility metrics matter, and which tool reports them?
Which AI visibility metrics matter, what each one lets you decide, and the best platform for AI visibility metrics, measured on our own project.
Updated
How accurate are AI visibility numbers?
Why do AI visibility scores differ between tools? The margin of error of a day, a week and 28 days, measured on 8,953 answers, and what each window hides.
Updated
Semrush AI Visibility Toolkit: what the score leaves out
What the Semrush AI visibility score counts, which AI platforms it covers, and what one score hides: untyped brands, markets and perception, measured.
Updated
Share of Answer vs Share of Voice: two AI metrics by hand
Share of Answer divides by answers, Share of Voice by mentions. Both computed by hand from 20 real AI answers, with a sheet formula for each.
Updated
Why do AI visibility numbers change, and why do tools disagree?
Why do AI visibility scores move from day to day and differ between tools? We measured 1,008 answers from 7 AI platforms. The guide covers the counting unit, platforms, prompts, rivals and a fair comparison.
Updated
How to measure Share of Voice in AI answers
How to measure Share of Voice in AI answers, step by step, and why it moves when the monitored rivals change. Measured on real answers from 7 AI platforms.