Why Vertical AI Products Monetize More Easily Abroad Than in China

Jiang Wu · 2024-12-11

*Originally published in Chinese on December 11, 2024.*

Vertical AI products, each built for one professional task, seem to find paying users more easily overseas than in China. The reasons are a set of historical factors, and they overlap with the differences between the Chinese and overseas markets.

Vertical needs and split-up products

The first factor is a different way of thinking. People understand vertical products well. Many users work in professional scenarios or use a different product for each function, and they have a strong sense of this and a history of paying. When a good product really improves efficiency and produces better results, they pay without hesitation. That is one reason.

Global from day one

Second, English remains the common language of products worldwide, so once a product launches it naturally faces the global market. Products built in the United States, India or Europe, using English as the main language, face a global market by default. Many founders of vertical products on this route do not think they are different, since AI plus a service gives a natural global advantage. Much of their marketing and system is contributed by users around the world. The number of users is larger than it would be for a single-language base, and quite likely a good share of the global revenue comes from Chinese users. For example, among the first hundred users of many new products in Silicon Valley, 20 to 30 may be Chinese users of a certain kind. That may not last, but in general the logic still gives some advantage, and the phenomenon still exists.

Open APIs

Third, thanks to the open and mature product APIs abroad, whether enterprise or consumer, users who are willing to use and tinker can fit a product into their existing workflow. Once the workflow becomes more efficient, the user's spending rises. Many Chinese products and scenarios are closed, and if a single scenario's capability is not opened up, users' total spending is limited. If it is opened, and the capabilities are compatible or spill over upstream and downstream, that helps a lot in raising the paying rate.

Different user markets and infrastructure

There is also a different logic, in that the user market itself is different, and the difference comes from past infrastructure. Overseas users, whether individuals or business customers, have a good base and a good soil for paying for software. When AI arrives and helps automate the features of each paid module, the products they offer within the payment system look like they deliver results. On the other hand, although many new products have appeared in the market, their share of revenue is still limited, or it still looks like only a beginning.

Chinese apps in the global market

Some Chinese applications do make money. Take GPT wrapper apps: among the top 10 paid products worldwide, perhaps three come from Chinese teams. We do not know they are Chinese teams, and they do not stress that they serve only one region. So what we perceive here is limited. Also, if we split the enterprise and consumer user logic, Chinese users' spending has not been seen at scale. That is a difference in overall feel. A pure consumer product does not announce at birth whether it is Chinese or global. Where the service involves heavy content review, such a team ships a global product first. That is one of the differences we sense today.

Home · All articles · Topics · 简体中文