Блог

Заметки о видимости в ИИ-поиске

Как ИИ-системы вроде ChatGPT и Perplexity находят, оценивают и цитируют сайты, и что нужно, чтобы попасть в их ответы.

15 статей

GEO, Measurement

One question, ten hidden ones

When a buyer asks an AI one question, the engine quietly turns it into about ten. Seer Interactive measured 10.7 hidden sub-queries per prompt across 501 prompts on Gemini 3. Most sites answer the headline question and none of the ten. Here is how to find your gaps.

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GEO

Different engines, different back doors

Claude searches the web through Brave. Gemini leans hard on YouTube. Perplexity is the most citation dense of the four. Where each engine gets its sources changes what you should do, and it is why we score every engine separately instead of blending an average.

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GEO, Measurement

We sell schema fixes. Our own site scored zero.

The first time we ran our own audit, the structured data category came back 0 out of 100. No JSON-LD at all. What schema actually is, why FAQ schema is our highest-weighted signal, what we fixed, and the caveat that keeps before-and-after scores honest.

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GEO, Measurement

AI can mention your business and still get it wrong

Invisible is one failure. Mentioned but not recommended is another. The third is being described inaccurately, and nobody checks it. Why we score representation accuracy separately, why a friendly wrong answer counts as negative, and the four causes of a wrong description.

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GEO, Local business

Ask a place-blind question, get a nobody answer

Our early local question sets asked place-blind questions like "what is the best hair salon?" and scored 0 real mentions in 20 answers. Branded questions scored 53 in 80. What that gap taught us about local business AI visibility, and the three fixes that follow.

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