Overview
AI Visibility Optimisation moves the AI Visibility Score - a brand-safe, decision-stage citation metric weighted by sentiment, position and provenance. It combines citation engineering, entity authority and monitoring into a managed programme for how AI talks about you.
Business problem
AI mentions of the brand are rare, buried or less favourable than competitors', and no single number tracks it.
Decision supported
Decide where and how to intervene so the brand is surfaced, described accurately and recommended inside AI-generated answers.
Inputs & outputs
Inputs
- Brand presence, sentiment and position across AI answer engines
- Decision-stage query recommendation set
- AI Visibility Score and its provenance-weighted components
- Competitor share of voice within generative answers
Outputs
- AI visibility intervention plan prioritised by decision-stage impact
- AI Visibility Score breakdown with the levers that move it
- Share-of-answer competitive assessment
Decisions this helps answer
KPIs
- AI Visibility Score
- Visibility Confidence Score
- Share of model
SearchScore insight
Product feature mapping
How this capability maps to SearchScore product features, today and on the roadmap.
shipped
AI Visibility Score
beta
Competitor share-of-model
Future improvements
- Continuous multi-engine monitoring so visibility and sentiment shifts are caught as models update
- Answer-driver attribution that traces which specific sources an engine used to describe the brand
- Simulated answer testing that predicts recommendation likelihood before interventions ship
Starter prompt
Across ChatGPT, Perplexity and Google AI Overviews, summarise how each describes our brand versus two competitors and where we lose.Recommended next steps
Where this fits - and what's next
The SearchScore path from a problem you feel to visibility you can measure.