GEO策略 Does geo have any technical substance? Yes, but not much—the principle is very simple.

GEO is not a deeply logical technology. On the contrary, as long as I tell you the principle, it becomes something anyone can easily operate.

So-called GEO means that when users ask questions on AI platforms such as Doubao, Qwen, Hunyuan, DeepSeek, and others, the answers returned prioritize recommending the content we have planned.

And these domestic large models now all answer in combination with source media. This technology is not hidden behind the large models; it is visible to everyone.

For example, Doubao, the AI platform with the largest traffic in China, when we send a question, will first screen sources to use for reference and corroboration. We can see this directly on the front-end page, as shown in the image.


In Figure 1, the part I underlined is the source. Many ordinary users simply have not noticed it. If we are a little more careful, clicking it will show Figure 2.

The AI first performs semantic-level word segmentation based on the question and locks the scope of the question—that is, “it believes this question should be analyzed from several dimensions”—and then uses the segmented words to find relevant content in its source database.
This is the answer logic of all mainstream domestic LLM AI model products. In terms of finding scope and screening, it is actually the same principle as search engines.

So actually, it is very easy to operate. We can see that many sources are not particularly authoritative media; even authoritative media can be accessed through reasonable channels. This is the LLM generative AI logic that fits our national conditions. The reason is simple: our biggest information source is civil media and payable official media.
As long as you want the AI to know you and let users mention you when searching, grasp the right sources and you are more than halfway to success.

Why do I say you are only more than halfway to success? Because GEO is not entirely without technical content.
Because in judging the authenticity, originality, authority, and structured data of content, we have had this ability since the Baidu era, so AI does not refer to things 100% blindly; it still has a certain ability to discriminate—that is, first select, then distinguish, then reason. This is the generation principle of more than 90% of personalized content.
So if you want AI to recommend you, you still need to put some effort into the content. After all, if you write nonsense, others can tell. But these details at most count as editing ability. Nowadays, copywriters are more common than dogs on the street, so this is really not difficult. If you are only doing regional-level enterprise competition, you don’t need to be very professional at all. Get the sources right and the copy on the right track, and you will rise.
At the current stage, doing this much is enough.

As for the future, there will certainly be higher requirements for content, and ultimately it is still content that competes. So don’t be fooled by GEO companies. GEO is not mysterious; it is just the content distribution platforms of the past, and even inferior to the content written by your own self-media editor. A truly impressive GEO should be a strategy expert + copywriting expert. It should be able to combine your industry market and your own development situation to formulate a playbook consistent with the current state of development. This is like a set of brand tactics: first educate the market, then build trust, cultivate interest in products, build reputation, and ultimately return to market thinking.

The moderator’s summary is one sentence: GEO is low-level technology + high-level thinking, and only then can it be played well. At this stage, most GEO companies are low-level technology + pure SEO thinking. They have no playbook at all and no awareness of brand and performance.