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Engine coverage

Six assistants, six opinions, one score

Each assistant reads different sources and answers in its own way. You can top one shortlist and miss another entirely on the same afternoon — which is why a single-surface check tells you almost nothing.

  • 6 surfaces tracked
  • 60 checks a week
  • Identical scoring
  • Forensics per answer

Short answer

Why not just track ChatGPT?

Do buyers really use that many assistants?

Yes — and different buyers default to different ones. Developers ask Claude and ChatGPT, researchers live in Perplexity, shoppers meet Google AI Overviews without ever choosing an assistant. A brand that wins one surface and misses three is not winning; it is present in one buying motion and absent in three others.

How do six surfaces stay comparable?

Ten grounded prompts times six surfaces produce sixty checks per ISO week. Every check is graded on the same five stances, sentiment, position and sources, then normalized to the same 0–100 scale. Google AI Overviews and AI Mode share Googlebot, so they are reported separately but never presented as independent providers.

Is collection real-time?

No. Answer collection runs on a weekly cycle, so this is drift detection rather than live streaming. A weekly reading is what tells you which week a position moved — a live feed would bury that signal in noise.

The six surfaces

They disagree. That is the point.

  • ChatGPTOpenAI · conversational shortlist answers
  • ClaudeAnthropic · long-form reasoned recommendations
  • GeminiGoogle · assistant answers
  • PerplexityCitation-first answer engine
  • Google AI OverviewsGoogle Search · synthesised overview
  • Google AI ModeGoogle Search · conversational mode (udm=28)
ChatGPT82 / 100Claude74 / 100Gemini80 / 100Perplexity71 / 100AI Overviews76 / 100AI Mode68 / 10078.4VISIBILITY

Illustrative example data — scores come from each brand's own weekly cycle

10
Buyer questions

Grounded in your pages

6
Surfaces

Scored identically

60
Checks / week

Evidence preserved

0–100
One score

Comparable weekly

Per-surface playbooks

Each engine answers differently

Retrieval mechanics, what moves the shortlist, and the fastest fix per surface.

How the shared scoring model works

Engine questions

Asked by technical teams

Quoted verbatim via FAQPage markup.

Do you query the AI engines automatically?

Run generation, response extraction, scoring, drift detection and remediation drafting are automated. Answer collection runs on a weekly cycle rather than continuously, so this is drift detection — not live monitoring, and not a real-time alerting system.

Why track six surfaces instead of one?

Each assistant reads different sources and answers in its own way. A brand can be the top pick in one and absent in another on the same afternoon. Ten prompts across six surfaces produce sixty checks per cycle, which is what makes week-over-week comparison meaningful.

Are Google AI Overviews and AI Mode different providers?

No. They are two distinct Google Search experiences that share Googlebot, so the platform reports them separately while making clear they are not independent model providers.

What actually moves an engine answer?

Retrieval access first, then entity clarity, machine-readable structure and third-party corroboration. The audit scores crawler access, llms.txt, Schema.org and semantic structure out of one hundred, and the remediation queue fires only when your own data calls for it.

Cover all six

One score across every assistant your buyers use

Ten prompts, sixty checks, forensics per answer — refreshed every Monday. Fourteen days free, no card required.

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