How visibility is calculated

• Based on the brand's industry, services and market, the system writes up to 15 questions buyers ask AI: 3 recommendation questions and 2 each for comparison, concern, long-tail, local, price and switching.
• After duplicates and unusable questions are removed, the actual number is shown in the report, usually 13 to 15. In the new-analysis wizard you can also edit the questions or paste your own: with 10 or more of your own, the first 15 are used as they are; with fewer than 10, the system fills in questions by the quotas for the 7 types, up to 15. Each type has a cap when filling in, so your own questions beyond a type's cap, or whose type can't be identified, may not be used. System-written questions that fail our checks are replaced.
• Questions are asked in the market's language, for example Traditional Chinese for Taiwan and Japanese for Japan.
• Questions written by the system never include the brand name, so the brand's own name can't inflate its visibility. Custom questions you paste are used as written; ones that include the brand name will push the score up.

• Taiwan, the US, Japan, Korea and Global: 5 AI platforms, namely ChatGPT, Gemini, Perplexity, Google AI Overviews and Claude.
• China: DeepSeek, Kimi and Qwen. These are called through OpenRouter, so we measure the models themselves without web search, which can under-count brands.
• Google AI Overviews has three outcomes: an overview was returned, Google shows no overview for that question, or a technical failure. Only returned overviews count toward scores; if more than 20% fail, the report flags the data as incomplete.
• If a platform query fails, the system asks ChatGPT instead; those substitute answers don't count toward the original platform's score. Claude is not substituted: if a Claude query fails, that question simply has no Claude answer.
• If Claude can't be queried for a run (for example, while the service is paused), that report is scored on the other 4 platforms and says Claude wasn't included; because the platform set differs, its scores can't be compared directly with reports that include Claude.

Mention rate = answers that mention the brand ÷ valid answers

• Each question on each platform is one answer; several mentions in one answer count once.
• The interval uses two methods: a Wilson interval, and a two-level resampling that redraws questions and then each answer (fixed random seed, 1,000 rounds). The final interval covers both, taking the lower of the two lower bounds and the higher of the two upper bounds. Fewer questions mean a wider interval.
• Mention rates fall into three levels: 50% and above, 20% to 50%, and below 20%. When the interval spans more than one level, the report marks it “needs confirmation”: a re-run could land in a different level.

AI visibility score = Σ(platform points × weight) ÷ Σ(platform valid answers × 5.5 × weight) × 100

• Points per answer: mentioned +1, recommended +2; ranked 1st +2, 2nd +1.5, 3rd +1, 4th +0.5, 5th +0.3; +0.5 if the passage about you is at least 30 characters. Maximum 5.5 per answer.
• Negative mentions (for example, AI telling people to avoid you) only earn the mention and passage points, not recommendation or rank points.
• Answers that were asked again are multiplied by how often the brand reappeared (see the next section).
• Platform weights: Google AI Overviews 1.5; ChatGPT, Gemini and Perplexity 1.0 each; Claude 0.6. In Japan and Korea ChatGPT is 1.2 and Perplexity 0.8, and Claude stays at 0.6; in China DeepSeek 1.0, Kimi 1.2, Qwen 0.8.

• Answers that mention you are asked again on ChatGPT, Gemini, Perplexity and Claude; up to 15 competitor-only answers are also re-checked; no more than 30 re-asks per report.
• A brand that appeared the first time but not on the re-ask gets half credit for that answer; brands that only show up on the re-ask are not added.
• Google AI Overviews is not re-asked, and this step is skipped when the analysis runs short on time.
• In our own test on 27 September 2026, the same brand and the same 14 questions asked twice gave mention rates of 31.5% and 41.7%. Compare runs with the same question set and check whether the intervals overlap, rather than reading the score difference alone.

Grades: A from 80, B from 60, C from 40, D from 20, otherwise F.

So a high GEO score doesn't mean AI will recommend you. To see whether AI mentions or recommends you, look at the mention rate and the AI visibility score.

About llms.txt: it's a site guide for AI tools, not a ranking factor, and Google says you don't need special files like this to appear in its AI search features (Google Search Central, checked 2 October 2026). We treat it as one small technical check.

• AI answers change; a report is a snapshot of that moment and may not repeat exactly.
• With up to 15 questions and 1–2 asks per answer, samples are small: good for direction and clear gaps, not for 1–2 point changes.
• Brand names are matched automatically, with same-name merging. If AI calls you something else (for example only your company name), add it as an alias in the analysis settings.
• The 40 most-mentioned competitors are verified with live web search and removed if they can't be confirmed, but mistakes are still possible; if the search service is unavailable, this step is skipped and the report says so.
• The China market measures the models themselves, without web search.
• Re-tracking from the brand page may use different questions than last time; to compare runs, paste the same custom questions into a new analysis.