The most frequently cited answer in the Chinese-language AI is not the biggest brand, but the best one. Tenten Brand Radar tracks the responses of ChatGPT, Perplexity, Gemini and Google AI Overviews to 500 complex business questions over a period of three months, sorting out the top 100 brands that are most frequently named, and the most anti-intuitive finding is that hundreds of billions of companies have been in business for many years, and that visibility has been passed to just a dozen people, SaaS. The difference is not in the budget, but in which case the contents can be read in and spit out as they are.
How did you figure this out?
First of all, the method, because it determines whether the list can be trusted. We don't capture the Internet, we don't look at who's doing the ads, but we actually ask what the AI engine has to do to directly influence the decision-making process and who it named in the answer. The same question is asked three times a week, reruns every week and runs for three months, with the aim of filtering out the occasional obscurities and leaving behind only the brand of "stable quotes." It doesn't count once a week, and it's only possible to be selected by the machine as a reliable source.
- Source of the problem: The most frequently asked question from real B2B searches, industry, and the "recommended which one" type of question, which covers software acquisition, marketing, financial technology, electricity and manufacturing.
- Tracking engine: ChatGPT (including search mode), Perplexity, Gemini, Google AI Overviews, four separate engines.
- Score method: The text of the answer is given a point at a time, and appears in the quoted source link for another weight, and the same answer repeats the non-repeated score.
- Time horizon: three months running again and again every week to stabilize values instead of single week heights.
The face of the first 100 names: three ladders.
Turning 100 brands into three layers, which are almost unrelated to the size of the company. What really opens the gap is whether it's sorted into machine reading.
- First Platoon (former 10): One colour is a solid brand of content building. The website has a well-structured comparative page, a price page and a full version of FAQ, Wikipedia, which is described by a third-party evaluation station. AI won't answer it wrong, so dare to quote it all the time.
- Second Platoon (11-40): Mostly by a single force. It may be an industry report that has been repeatedly quoted, or a defined terminological page that has been written so clearly that it overwhelms a larger opponent on a particular topic.
- Third Platoon (41-100): Visible, disappearing this week, next week. The problem usually arises from the partialization of content — the same theme is scattered in several articles in blogs, and no page can be taken out as an answer.
The most cited brand, only three in common.
The top 20 appear to belong to different industries, but tearing down their content structure would reveal an alarming overlap. They don't seem to be as famous as their opponents, but they do the same thing: let AI quote you at a lower cost than anyone else.
- Content can be extracted from the entire section. One paragraph says, "What is it, who is it, who is it?" So the machine doesn't have to cross a few pages to spell, and it's a complete answer.
- The truth is unanimous. The official web, Wikis, evaluation stations, and community are right about the same thing, and AI will not skip you because of conflicting sources.
- Tie structural mark. FAQ, priced, compared to Schema, the engine clearly determines which part is answering which question, and does not have to guess.
Why are some big brands missing?
The most worthwhile on the list is actually the absentee. A few companies in their own business, counting one or two, were barely named in the relevant questions and fell out of 100. They're not without content, they're all stuck where the machine can't read it: The key information is stored in the PDF format, the product code is embedded in the desired tab, and the comparative information is presented by an interactive component that will be loaded for a long time. People can see, reptiles can't catch, AI naturally when it doesn't exist. Another common situation is that officials and wikis, evaluation stations talk about each other, and the source is a contradiction, and the engine prefers to quote a small, consistent company.
AI's not looking for the most famous brand, it's looking for the answers that don't make it wrong. The better and less contradictory your content, the higher the chance of being quoted.— Tenten Brand Radar Observer Note
Turning from the list, you should do three things right now.
The real use of this list is not to see others in the ranks, but to see your own gaps. The path followed by the top brand can actually be replicated, and the sequence is clear: measure first, re-compensate, and finally match external facts.
- Set the baseline first. I don't know which subjects I'm missing and who's squeezing out, and all the moves behind me are just guessing. Throw your most important shopping list at the AI engine and see who it named.
- Complementing the "extractable" rights page. The idea of spreading around the blog is to make a clear comparison page, noun page or FAQ, so that the machine can get the full answer at once.
- Matching external facts. Update the description of the wikis, evaluation stations and partner pages so that they can speak the same language as the official web and clear the deduction of source conflicts.
