Our approach
How we find the answer
A method you can inspect. We connect the questions buyers ask, the answers AI gives, the evidence behind them and the work that changes them, and we say plainly what stays uncertain.
The method
Five moves, repeated until the answers change.
Start with the questions buyers actually ask.
A visibility programme that begins with keywords begins in the wrong place. We define the buying questions that shape a shortlist, in the language a buyer would use, and agree which ones matter commercially.
Observe what the answers say.
We record what AI assistants answer to those questions, with the sources they cite and the brands they recommend. Every observation keeps its provider, period and cohort, because an answer without that context cannot be trusted.
Separate mention, citation and recommendation.
A brand can be mentioned without being cited, and cited without being recommended. We keep the three apart and report each with its own denominator, never as a single score.
Turn the gaps into work.
The evidence points at specific gaps: a claim with no supporting source, an integration described nowhere, a category question where you never appear. We turn each gap into prioritised work with an owner and an expected effect.
Measure what changes, and say what does not.
Every intervention is recorded with its date and intended outcome. We compare before and after on the same questions and cohort, and we report flat or negative results as openly as the ones that move.
Three outcomes, never blended
Mentioned is not cited. Cited is not recommended.
Mentioned
Your name appears in the answer.
Cited
Your own evidence is used as a source.
Recommended
You are suggested for the buyer's stated need.
Clear about uncertainty.
We do not control what a model recommends, and answers differ between providers and over time. Where the evidence is thin, we say so, and we explain what a single observation can and cannot support.
Stand out.
Get chosen.
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