If you use international tools like Profound, Peec, Oterly to monitor your visibility in AI answers, the numbers in the middle market are almost undervalued. The reason is not that your brand is not strong enough, but the schematics of these tools, the logic of the metalogics and the modeling, are all premised on English and the United States. Taiwan users actually ask, how AI quotes, and they can't see half.
What the hell is AI seeing?
This type of tool has three core indicators: reference rate (how many times your brand appears in a response to a set of hints), reference ratio (how many of the sources quoted by AI come from your domain) and speech preferences (referring to positive, neutral or negative). This is done by preparing a set of hints that are regularly thrown to models like ChatGPT, Gemini, Perplexity, Claude, to capture text and quote links. The quality of the whole process depends on two things: the hints don't look like real users, and the pick-up ends don't understand Chinese. These two points are all problematic in the middle of the scene.
Three scenarios for sharing mainstream international tools
Spread out some hot tools and assume a high level of consistency. They do not deliberately ignore the multiplicity of products, but rather produce from the first day of the United States market.
- The hint is written in English, or the English tip machine is translated into Chinese.
- Terminator and physical recognition follows the NLP pipe in English, using space-sized, string-to-brand words First Name
- Surveillance area defaults for America, interfaces defaults, en, model accounts mostly run around US nodes.
Blind Point One: A hint is not a question for the Taiwanese.
The English phrase "best CRM for startups" is translated as "newly created CRM", but Taiwan B2B purchases will actually be called "What's the new CRM for Taiwan Saas better" and "HubSpot Taiwan Agent recommends." The list of names that AI recalls is completely different with the word "recommended" and the local comparative. The tool translates a hint, which is the same as a question that a Taiwan user doesn't ask at all. Your visibility is either zero or nothing, and neither of them has any reference value.
Blind point two: the Chinese cut-off makes the brand reference catch.
Chinese sentence does not have spaces. In English, tokenizer encounters a phrase like "sweetly improved with a busy content engine" that easily binds the brand name to the previous word or cuts it in the wrong place, leading to underestimation of the number of references. Simplicity is even more difficult: the same brand sometimes appears in the AI response in simplified writing, and this reference simply disappears if the tool is compared to a complex string. The shorter the brand name, the closer the term is used, the more serious the scratches.
Blind Point Three: Models and locale configurations will rewrite the results.
The same hint is that accounts are located in the United States and Taiwan, Gemini and Portexity return source lists; language settings are not the same as the websites quoted in zh-TW, ChatGPT. Most of the international tools are in U.S. nodes, English locale, and the "AI answers" that the U.S. users see are not the version that your Taiwan potential clients see. You think you're monitoring your own market, actually, monitoring someone else's market.
Blind Point Four: Emotional interpretation is insensitive to Chinese
The Chinese tone, sarcasm, euphemism, and the English emotional model are out of line. The tools are likely to be positive. When you judge the course of the brand's reputation with emotional indicators, the interpretation itself is distorted, and the conclusions that emerge from it are also distorted. This kind of error does not make the report ugly, but it often makes it better and harder to detect.
The most dangerous thing about seeing numbers is not ugly, but rather reasonable -- it makes you think the market is covered, and AI doesn't even mention you in Taiwan users' questions.— Tenten GEO consultant team
What to do, how to do it.
The selection tool asked three questions: whether the hints can be customised to a multiplicity of real questions, cut-offs and references, whether there are references to Chinese, whether the Taiwan region and zh-TW language can be locked down. If one of them fails to do so, it will have to be checked manually, so that the default value of the tool does not come to a conclusion. Brand Radar of Tenten was designed for the mid-story scene, where the hint bank was attached to the actual search for B2B in Taiwan, where the cut-off and source-to-source ratio supported the complexity at the same time, measuring your real market.
I'd like to know how much visibility the tools in hand have left you with. We'll run through it with your own brand and a couple of real hints and show you the difference between international tools and not seeing them.
