We ask the five major AI engines real buyer questions, more than once, and record who and what they name. Every number on the site is a count from those answers, with its date and its sample size.
LAST UPDATED: SEPTEMBER 8, 2026
| What | The question it answers | Unit |
|---|---|---|
| A question page | What do the engines answer, and whom do they name, for this exact question? | Names ranked by mention rate: answers mentioning them out of answers sampled |
| A brand or tool page | Across every question it appears in, where does this brand stand? | Share of answers per question, over time |
| A voice | Which people do the engines reach for, unprompted, in a segment? | Mention rate as a fraction of sampled answers, across questions and engines |
| CiteRank | How often is one person actually cited by AI in their segments? | 0 to 100, from the four weighted signals below |
Ask an AI engine the same question twice and you get two lists. Research on brand answers finds that repeating the same prompt explains about a third of the variation, and that asking more engines and more wordings improves precision more than asking the same engine again and again. So we ask five engines, twice each, and we tell you how many answers mentioned each name. A mention rate of 7 of 10 answers is a finding. A mention rate of 1 of 10 is a lead.
The variance-components study (arXiv:2607.13304) · the Pebblous iteration reanalysis
Ask an AI engine the same question twice and the answers differ. Before we show any movement, we measured how much. We re-asked the same prompts on five engines, either twice on the same day or a week apart, and counted how far the results moved when nothing had really changed. These are measurements on our prompts, not on CiteRank itself.
Mention Rate is the fraction of a prompt's answers that name an entity. With 15 answers per prompt (five engines, three samples each), for names that came up both times, it moved by more than about 27 to 33 percentage points in only 1 re-ask in 20 (163 prompts asked twice on the same day, 159 asked a week apart). We therefore show a change only when it is larger than about 36 points at 15 answers, and we show it as counts, such as "named in 7 of 15 answers, was 3 of 15".
A name that 40% or more of a prompt's answers agreed on was still at 40% or more on a re-ask in 75% of cases (163 prompts, same day, three samples per engine).
Rank place was not stable enough to show. On a re-ask with nothing changed, 67% of entities named by three or more engines moved two or more places, and 39% moved five or more (153 prompts). We do not show rank-place movement.
A week apart looked like the same day. The noise comes from asking again, not from time passing.
What we have not measured yet: the noise of the CiteRank score itself, and how the engines differ from one another. We will publish both when we have measured them, and we will not rank the engines before then.
A score or rate whose two ends fall on either side of one of these dates is flagged, not trended.
2026-07-04: Citation Rate moves to source attribution.
2026-07-26: each probe asks for exactly 10 names, so rates before this date are not comparable.
2026-08-16: one engine (Grok) is removed from the set because the vendor cannot collect it.
2026-09-16: the pinned prompt series is re-cut; comparisons across versions are breaks.
Outside changes we watch, as reported by others: on 2026-05-07 ChatGPT changed how it shows links (reported by Profound and Qwairy); on 2026-01-27 Gemini 3 became the default behind Google AI Overviews (reported by SE Ranking).
Example row - unit illustration, not a measurement.
Confirmed names rank first. Names from a single answer are shown too, labelled, because where the engines disagree is exactly what you came to see.
A fixed set of questions is asked every Monday with the same setup. A change between Mondays is a change in what the engines say, not in how we asked. Single-week wiggles are weather; multi-week trends are climate.
A person becomes a voice when the engines name them unprompted in two or more answers from different engines, or across two questions. Our questions never contain anyone's name. The Israel index is built from questions asked about Israel in Hebrew and in English; the two languages surface different people, and both belong.
CiteRank is the outcome score for a person: how often AI cites them, weighted by where. It is measured on the same answers as everything above.
| # | Signal | Weight | What it measures |
|---|---|---|---|
| 01 | Citation Rate | 45 | Named citations of the voice's controlled domains across the engines we ask. The direct outcome signal. |
| 02 | Domain Reach | 25 | Breadth of the distinct domains AI actually cited when answering about this voice, weighted by tier - primary sources count far more than aggregators. |
| 03 | Share of Voice | 20 | Of all the names AI gives when asked about a segment, the share that goes to this voice. Measured only on questions that name no one. |
| 04 | Topical Authority | 10 | Backlink and press-mention signal, off-AI. The upstream signal that produces citations. |
Domain Reach is tier-weighted. Where a citation lives changes how much it counts - a Wikipedia or LinkedIn citation carries far more than one on an audio-only podcast feed.
| Tier | Weight | Platforms |
|---|---|---|
| TIER 1 | 1.0× | LinkedIn, YouTube (with indexed transcript), Reddit, Wikipedia |
| TIER 2 | 0.75× | Medium, Quora, Substack, editorial publications, podcast (with transcript page) |
| TIER 3 | 0.5× | Personal website, Forbes/HBR contributor profiles, GitHub |
| TIER 4 | 0.1× | Instagram, TikTok, X/Twitter, audio-only podcast, generic low-DR sites |
Citability is a leading A–E grade on a single piece of content. It is reported beside CiteRank and is deliberately never summed into it.
| Component | Weight | What it measures |
|---|---|---|
| Information Gain | 40% | How much genuinely new signal the piece adds beyond what engines already have. |
| Original Framing | 25% | A distinct framing or claim engines can attribute to you, not a restatement of consensus. |
| Credibility | 20% | Verifiable sourcing, controlled domains, and a track record engines can trust. |
| Structure / Extractability | 15% | Clean structure engines can lift cleanly - headings, direct claims, quotable lines. |
Postability is the craft companion to Citability, judged against the author's Voice DNA on a 0–100 scale. Advisory only; it never blocks publishing.
| Component | Weight | What it measures |
|---|---|---|
| Hook | 35% | Does the opener stop the scroll? |
| Voice | 40% | Does it sound like you, measured against your Voice DNA? |
| Format | 25% | Platform-fit and scannability - does the close land? |
The sampling design and the weights are grounded in external, verifiable research - not house opinion.
The foundational framework for optimizing content toward generative-engine citation.
Repeating the same prompt explains roughly a third of the variation in brand answers.
More engines and more wordings improve precision more than repeating one engine.
Which platforms LLMs cite most, by engine, at scale.
Prompt-level analysis of which sources surface across generative engines.
Measured lift in AI citations following structural and distribution changes.
Your CiteRank already exists. Find your score, see what moves it, and watch the trajectory.
CHECK MY CITERANK