Real Cases: How We Get Products Cited by AI

GEOScope doesn't just talk methodology — we ran the detect-fix-monitor loop on our own product line. Three real cases with verifiable data.

GEO Tool · Own Case

GEOScope: Eating Our Own Dog Food

We monitor geo.oneaicv.com across 9 AI engines daily. The data is honest — including the unflattering '0% cited' number, which is exactly the problem GEO solves.

9
engines
64
probes/scan
6h
interval
Boutique hotel · Illustrative (Beta)

Demand invisibility: never entering the AI shortlist

The usual problem is not "ranking low" — it is that when a traveller asks AI for "boutique hotels for couples in this city", the property is simply absent from the answer. A beautiful website does not change that. ARI separates the two cases with M1 Demand Coverage and M2 Recommendation Presence: is AI not shortlisting you, or shortlisting you but not naming you?

M1+M2
shortlist first
8 metrics
business, not technical
Intent×Engine
opportunity ranking

Illustrative scenario (Model Estimate · Beta) showing how the metrics read — not a specific client dataset.

Resort / attraction · Illustrative (Beta)

Mentioned by AI — but always after the 5th slot

Decent presence with a consistently weak position is the second way to leak demand: M3 Top Position Strength and M4 AI Share of Voice stay low while one or two rivals in the AI CompSet show a high "pressure" rate — they are placed ahead of you almost every time. The fix is usually not a website redesign, but the specific sources AI actually cites for those intents.

M3 / M4
position & share
Pressure
who really beats you
Source attribution
what you can move

Illustrative scenario (Model Estimate · Beta) showing how the metrics read — not a specific client dataset.

Browse Cases by AI Platform
ChatGPT CitationGet your site cited by ChatGPT Perplexity AuditGet cited by Perplexity Gemini VisibilityBoost Gemini visibility Claude MonitoringTrack Claude citations

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