Running a lot of arbitrary questions does not show you your AI visibility.
AI search optimization starts by picking, with evidence, the questions your customers will actually ask.
The prompt set everything is measured against
is built from four strands of data that stand in for real demand.
We structure categories, product lineup, the competitive picture, and the objections that keep coming up, from your domain and brand material. It is the baseline that keeps the prompts from drifting away from the actual business.
We start from phrasings whose demand is already proven. Keyword volume sizes each topic; related searches widen what was missed.
People type keywords into a search box but ask AI in sentences. We collect that sentence-shaped demand separately, from autocomplete, related questions, and community Q&A.
Candidate questions go to the real AI engines. Only the ones whose answers diverge stay — a question that answers the same for everyone has nothing to measure.
From those four strands we build the prompt set everything is measured against, matched per language and market to the questions people there actually put to AI.
From that evidence we lock down the exact brand, domain, market, and customer facts the prompts will be built on.
Within that category, we split the decisions people actually make into intents. The unit is a decision, not a question.
Each intent is checked against search demand data, then widened with related searches and autocomplete to catch what was missed.
We put representative questions to the live engines. Questions where the answer differs by brand stay; questions that answer the same for everyone are dropped.
The same intent gets different situations, lengths, and registers until it reads the way a person would actually type it. That is not the same as stretching a keyword into a sentence.
The set is fixed and daily measurement begins. Prompts that change later are recorded as a version, so the basis of measurement never drifts.
Who is asking, in what situation, to decide what — all of it changes the length and register of the question. Anymorph's prompt set is designed to hold that whole spread.
The first question, still carrying search-box habits. Unpolished, almost no conditions attached.
A question with one real decision in it. One or two conditions that change the answer come attached.
A question with a specific situation in it. Scale, budget, the tools already in use — the constraints that decide the answer stay in the sentence.
A topic is the unit that groups prompts by search keyword, product, or situation.Worded differently or not, questions leading to the same decision sit in one topic.
Topic Prompt | Mention rate | Top Brands | Intent | |
|---|---|---|---|---|
12 | Choosing an AI search optimization (GEO) tool | 71%142/200 |  AAnymorph41% Visibility Labs33% GeoRank AI27% SearchScope19% Lumenpath12% | Commercial |
1recommend an AI search optimization tool | A Anymorph Visibility Labs GeoRank AI | |||
2we're a B2B SaaS company — is there an AI visibility tool worth using? | Visibility Labs AAnymorph GeoRank AI SearchScope Lumenpath | |||
3which GEO tools integrate with Search Console and GA4? | Visibility Labs GeoRank AI SearchScope | |||
4we're seed stage with under $700/mo to spend and need both Korean and English covered. which GEO tool fits? | Visibility Labs GeoRank AI AAnymorph | |||
10 | GEO platform pricing and contract terms | 39%78/200 | Visibility Labs33% GeoRank AI27% AAnymorph41% SearchScope19% Lumenpath12% | Transactional |
8 | Quality of auto-generated pages | 33%66/200 | Visibility Labs33% GeoRank AI27% SearchScope19% AAnymorph41% Lumenpath12% | Informational |
9 | How GEO differs from SEO | 58%116/200 | Visibility Labs33% AAnymorph41% GeoRank AI27% SearchScope19% Lumenpath12% | Informational |
6 | Mention rate against competitors | 55%110/200 | Visibility Labs33% AAnymorph41% GeoRank AI27% SearchScope19% Lumenpath12% | Commercial |
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