AI answers change with who is asking.
An answer engine does not give everyone the same answer. RankSage runs your tracked questions as the buyers you actually sell to — a procurement lead in Mumbai, a developer in Berlin — and shows you where your visibility holds and where it quietly drops.
The problem
Every visibility tool measures the neutral ask. Your buyers never ask neutrally — they ask as themselves, with a role and a place and a context attached, and nobody is reading the answers those people get.
Persona Visibility, explained in about a minute
How it works
What it measures, what comes out, and why the number can be trusted.
- 01
You define the buyer, once
A persona is a role, a geography and a context — the person your positioning is supposed to reach. RankSage keeps a profile per persona so every later run asks as the same buyer.
- 02
The same questions, through their eyes
Your tracked prompts run again through the persona's lens, and everything is kept exactly as in a neutral run: the full answer text, the URLs cited, whether you were named.
- 03
Compared against the neutral baseline
Each persona's citation rate sits beside the neutral one, reported as a range because answers vary between runs. A gap that clears both ranges is real; one inside the noise says so.
- 04
Personas never contaminate the baseline
Persona answers are stored apart from neutral answers and never blend into your headline metrics. Your share-of-voice number means the same thing after you add ten personas as it did before.
- 05
A failed run gives the credit back
Persona runs are metered by credits, and a run that fails refunds its own credit automatically. You pay for answers, not for attempts.
What it does not do
- A persona is a modelled vantage point, not a recording of a real user's session. It shows how answers shift with context — it is not a claim about any individual.
- Persona credits are metered by plan, and Free has none — the baseline tracking comes first.
- Where a difference is inside the overlap of two ranges, RankSage says it cannot distinguish them rather than declaring a winner.
Works with
AI Share of Voice
See how often ten answer engines — from ChatGPT to Grok — name you, reported with a confidence range, not one flattering number.
Citation Integrity
Engines cite sources that are dead, or that never mention you. Every cited URL is checked — and only provable failures are called failures.
Question Mining
The questions your market actually asks, mined from real search surfaces and drawn as a mind map — with your own impressions as the only volume signal.
Questions
Do AI engines give different answers to different people?
Yes — context changes answers. The same question asked as a CFO evaluating vendors and as a developer comparing tools can produce different recommendations with different brands in them. Persona Visibility measures that difference against your neutral baseline instead of leaving it to anecdote.
How is a persona defined?
By role, geography and buying context — the shape of a real segment you sell to. You define it once and RankSage runs your tracked prompts through that lens on request, storing the full answers.
Why are persona results shown as ranges?
The same reason all RankSage citation rates are: answers vary between runs. Comparing two single numbers manufactures certainty; comparing two ranges tells you whether a persona gap is real or noise.
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