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Visibility

Multi-assistant visibility scoring explained

10 min read · GEO Archer field guide

One crawl, five assistant personas — because ChatGPT, Claude, Gemini, Perplexity, and Copilot do not all “see” your brand the same way. Learn how to read the scores and what to fix first.

5

Assistants modeled

ChatGPT, Claude, Gemini, Perplexity, and Copilot — from one crawl.

75+

Strong visibility band

Scores in this range mean assistants likely surface you for on-topic prompts.

Gap

Understanding vs visibility

High visibility with low understanding is a hallucination risk — fix clarity first.

A single “AI score” hides how you lose deals

You might look fine to one assistant persona and invisible to another — especially models that weight live citations (Perplexity-style) versus structured facts (Copilot-style). Multi-assistant scoring exposes that split before a buyer chooses a vendor inside the chat window.

Example: visibility by assistant (same company, one scan)

Illustrative output shape from GEO Archer. Your real scan may show a different spread — that spread is the insight.

Why we model five assistants separately

Users do not pick one AI — they use whichever tool their company approved, their browser bundled, or their habit prefers. Each system emphasizes different signals: citation density, structured data, recency, brand mentions, or conversational brevity. GEO Archer simulates those personas against the same crawl so you see where your story breaks per channel.

  • One weak assistant score = one channel where competitors become the default answer.
  • Visibility without Understanding means you might be mentioned incorrectly.
  • Fix content once; rescan to see which personas moved.

What the numbers mean (and what they do not)

Scores are modeled likelihoods from your public site content — not live API calls to OpenAI, Anthropic, Google, or Microsoft. That keeps scans fast, repeatable, and compliant. Treat them as diagnostic MRIs: they show structural problems and relative strength, not a guaranteed ranking in tomorrow’s model version.

  • Low scores usually mean missing pages, not a penalty box.
  • Large spreads between assistants point to specific content types to add.
  • Track trends across rescans after you ship recommendations.

Prompts buyers actually type

Visibility runs consider realistic questions: “best [service] in [city],” “how much does [X] cost,” “[vendor A] vs [vendor B],” and problem-led queries. If your site cannot answer those in crawlable text, models fill gaps with guesses — often from competitors who published FAQs and comparison tables.

Playbook: raise visibility without spam

Ship authoritative FAQs with real scope and pricing bands (even ranges), add comparison pages that name alternatives fairly, strengthen About and service-area copy, and implement schema that matches visible text. GEO Archer’s simulation and visibility tabs show which assistant moves when you fix each gap.

  • Use the AI Visibility tab per site after each scan.
  • Pair with Recommendations for ordered execution.
  • Export PDF reports for stakeholders who do not live in the dashboard.

Being ‘in ChatGPT’ is not a strategy. Being correctly cited when it matters — that is visibility.

GEO Archer visibility methodology

Sources & further reading

Chart data on this page uses illustrative benchmarks unless labeled otherwise. Your GEO Archer scan reflects your live site.

Run visibility on your domain

See per-assistant scores and the prompts that expose your gaps — then fix them before the next RFP lands in someone’s chat thread.

Start a visibility scan