Overview
A programme for moving the AI Visibility Score across engines through citation, authority and monitoring.
Business problem
AI mentions are inconsistent and unmanaged, and no single framework connects the levers that move them.
Decision supported
Which levers to pull to improve how AI represents the brand.
Inputs & outputs
Inputs
- AI Visibility Score baseline
- Engine coverage
- Competitor share-of-model
- Sentiment data
Outputs
- Lever plan
- Score forecast
- Monitoring cadence
Step-by-step process
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1
Baseline
Measure the AI Visibility Score and share-of-model per engine.
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2
Diagnose
Separate citation, authority and sentiment weaknesses.
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3
Act
Apply citation engineering and entity authority where each matters most.
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4
Monitor
Track deltas and correct how models describe the brand.
Maturity model
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L1
Unmeasured
No view of AI representation.
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L2
Baselined
Score and share known.
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L3
Managed
Levers applied deliberately.
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L4
Governed
Representation actively defended.
KPIs
- AI Visibility Score
- Share of model
- Sentiment of mentions
Common mistakes
- Optimising one engine and ignoring the rest
- Chasing volume over favourability
- No monitoring after a win
SearchScore insight
Recommended next steps
Where this fits - and what's next
The SearchScore path from a problem you feel to visibility you can measure.