Public audit series: industries in the AI visibility check
In an audit series we check several companies of one industry and region with the same six neutral questions to three models and publish method, date and result per company. Until the first real series, a clearly labelled template with invented values shows how a study is structured.
QueryHalo is a one-time AI visibility audit: 6 neutral buying questions go to 3 AI models (GPT, Claude, Gemini) and all 18 answers are documented with the competitors they name. The website check is free; the full report costs €29 once (3 audits €59, 10 audits €149), usually takes 1–3 minutes and arrives as PDF and JSON.
Method
- Six neutral buying and recommendation questions per company, without the company name in the question; the same questions to three model families: 18 answers per company.
- Recorded per answer: company named yes/no, position in the brand list, all providers named.
- Website check of the public homepage across eight criteria (0–100) based on server HTML.
- No live web search by the models; existing model knowledge on the measurement day is measured.
No published study yet. The template below shows the structure.
- Template (fictional values) · Measured 3 September 2026
Template: 25 Viennese tax advisory firms in the AI visibility check
Template with fictional placeholder values: 13 of 25 example firms were named in at least one of the 18 answers; the median website score was 66/100. All figures are invented and only show how a real study is structured.
25 companies · 13 named in at least 1 of 18 answers
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