Metric · formula, worked example, traps · checked November 8, 2026
AI share of voice is your brand's mentions divided by every brand's mentions in AI answers to a fixed set of questions. It tells you how much of the conversation you hold, not whether answers tell buyers to pick you. Measure that too, as a recommendation rate with its range.
share of voice = your brand's mentions ÷ all brands' mentionsCounted across answers to a fixed question set, one mention per brand per answer. Otterly.AI and Profound publish this form.
recommendation rate = answers that recommend you ÷ all answersReport it with its 95% range, about ±1.96·√(p(1−p)/n).
Want to measure the number that decides who buyers pick? supereo ours is our pick: it leads with the recommendation rate, the share of answers to your buyers' questions that recommend you, with its range, and reports mentions and citations beside it. Run the free audit.
The idea is the same everywhere; the details aren't. From each tool's own docs:
| Tool | Share of voice, in its words | What the base is |
|---|---|---|
| Otterly.AI | "number of my brand mentions / total number of all brand mentions" | Each prompt, engine and day counted once per brand |
| Profound | "divides the number of responses that mention your brand by the total number of brand mentions across all responses" | All brand mentions in its tracked responses |
| ZipTie.ai | "an entity's appearances divided by the total appearances of all tracked entities" | "a share inside your own monitored prompt set", which it says isn't "a market-wide impression share" |
| SE Visible | "your share of mentions compared with the competitors you track" | The competitors you track |
| Ahrefs Brand Radar | How often brands are mentioned or cited, as "modeled visibility signals" | Its prompt index; Estimated Impressions weight mentions by Google search volume |
| Nightwatch | "Compare your brand's presence against competitors in AI conversations" | Not defined further on the pages we read |
Sources: Otterly KPI definitions, Profound glossary, ZipTie methodology, SE Visible, Ahrefs methodology, Nightwatch, read November 8, 2026.
Notice the base. Every version divides by mentions of the brands someone chose to track, across questions someone chose to ask. Change either and the share moves. Search Engine Land called this "a hidden denominator" in June 2026 (Dan Taylor).
Take 200 answers to your buyers' questions. In supereo's November 7 run, an answer that named tools named a median of 6, so say every answer names six brands: 1,200 mentions in all. You're named in 120 answers and recommended in 30. A competitor, X, is named in 100 and recommended in 70.
| Metric | You | Competitor X | Who it says is winning |
|---|---|---|---|
| Share of voice (mentions ÷ 1,200) | 10.0% | 8.3% | You |
| Mention rate (answers naming you ÷ 200) | 60% (53 to 67) | 50% (43 to 57) | You |
| Recommendation rate (answers recommending you ÷ 200) | 15% (10 to 20) | 35% (28 to 42) | X, clearly: the ranges don't overlap |
An illustration with our arithmetic: 95% ranges in brackets, ±1.96·√(p(1−p)/200). The six-names-per-answer figure is the median from supereo's research panel, November 7, 2026.
Share of voice and the mention rate both put you ahead. The recommendation rate says buyers who ask are told to pick X more than twice as often. That's the gap the visibility metrics can't see, and it's the one that costs deals.
The fix isn't to drop share of voice. It's to freeze the questions and the competitor set, report each engine separately with ranges, and set it beside the recommendation rate. Search Engine Land's October 2026 advice was the same: report "visibility rates with ranges, split by platform, over rolling multi-week windows" (Greg Jarboe).
| Metric | What it tells you | Its trap |
|---|---|---|
| Recommendation rate | How often answers tell the buyer to pick you | Needs a judge that reads each answer; ask how it decides |
| Mention rate (visibility) | How often you're named at all | Counts the sixth name the same as the pick |
| Share of voice | Your slice of all mentions | Moves with the competitor set and the questions |
| Citation rate | How often your pages are linked as sources | You can be cited without being named |
| Average position | Where you fall in answers that name you | Ignores the answers that don't |
| Sentiment | How you're described | Only measured when you're mentioned |
| Search Console AI impressions | How often Google showed your links in AI features | No searches and no rivals in its documented views |
Whichever you track, three rules hold: fix the question set, count many answers per engine, and print the range.
Public posts, word for word. They're individual posts, not reviews or ratings.
“Semrush does that too and it always feels like a vanity metric.”u/evolkween on r/DigitalMarketing · Jul 15, 2026 · Read the post · The post is about a single percentage visibility score
What helpsA share of mentions can't tell a passing name from a pick. supereo leads with how often answers recommend you, with its range, and reports mentions beside it.
“If your metric changes between week one and week three, you cannot disaggregate model update noise, prompt sensitivity, retrieval corpus changes, and actual brand visibility shifts.”u/PearlsSwine on r/GEO_optimization · Jun 15, 2026 · Read the post
What helpsThat's the case for control questions. supereo measures questions a change can't touch over the same weeks, so a model update or retrieval shift moves them too and drops out of the verdict.
“A move from 28 to 33 percent on the mention count is inside the noise.”u/Slow-Commercial4316 on r/SEO_LLM · Sep 25, 2026 · Read the post
What helpsThe arithmetic agrees: on a few hundred answers, a 5-point move sits inside the range. supereo prints the range so you don't have to work it out.
Your brand's share of all brand mentions in AI answers to a fixed set of questions: your mentions divided by everyone's. It shows how much of the conversation you hold.
Freeze a set of buyer questions and the competitors you compare against, ask each question many times on each engine, count one mention per brand per answer, and divide yours by the total. Report it per engine with its range, and beside your recommendation rate.
As rates over many answers: how often you're named, recommended and cited, each with a 95% range. At a 30% rate, 200 answers give a range of 24% to 36%.
There's no universal number, because the base differs by tool and by question set. Compare yourself with your own past and with the competitors in the same set, and check the recommendation rate before you celebrate.
No. AI visibility counts how often a brand shows up anywhere in an AI answer, often as one name in a list of six. Being recommended means the answer tells the buyer to pick you. supereo reports both, and leads with its recommendation rate: the share of answers to your buyers' questions that recommend you, with its range.
supereo leads with it: its judge records whether each answer recommends you, keeps the answer's own words as the quote, and gives the rate its range. Most other tools here lead with mentions, share of voice or a visibility score.
More: AI Overview trackers compared · AI brand monitoring · Best AI visibility trackers
Share of voice definitions come from each tool's docs, read November 8, 2026. The worked example is an illustration built on the median names per answer from supereo's November 7 research panel. Search Engine Land is owned by Semrush, which sells an AI visibility tool. Quoted posts are copied word for word. Full method.