The Rise of DeepSeek: How Will Domestic Large Models Reshape the Global GEO Landscape? | AB Guest

Why should foreign trade companies pay close attention to the rise of DeepSeek?

For the past decade or so, the underlying rules of global digital marketing have primarily revolved around search engines: keyword research, page layout, backlink acquisition, and click-through rate optimization. This system hasn't failed, but it's no longer complete. Now, more and more front-end actions in the purchasing process are shifting from "entering keywords to search" to "directly asking AI questions."

The changes brought about by DeepSeek are not just about a large Chinese model entering the global spotlight, but more importantly:

• The presence of Chinese semantic capabilities in the global AI competition has significantly increased;
• Enterprises do not need to rely entirely on English internet corpora to participate in international perception;
• The AI ​​recommendation entry point has shifted from a single-center structure to a multi-center structure.
• The way content value is evaluated has shifted from "page ranking" to "credible understanding".

This means that whoever completes content structuring, knowledge assetization, and multilingual semantic consistency first is more likely to occupy a high-value position in the AI ​​recommendation network.

The global GEO rules are being rewritten: What changes have occurred in the underlying logic?

Explanation of the principle: Why does the export of domestically produced large-scale models affect customer acquisition for foreign trade enterprises?

1. Training sources are becoming more diversified.

The publicly available knowledge sources, site structures, citation relationships, and semantic expressions referenced by the model are no longer solely based on English content. Chinese content, bilingual content, and multilingual knowledge networks can all influence the model's industry understanding. For Chinese manufacturing companies, this means an increase in their ability to express professional knowledge.

2. Recommendation logic is shifting from ranking to reasoning.

Search engines rank pages across a vast number of pages, while AI systems summarize, judge, and answer questions from massive amounts of information. They prioritize "which company is more trustworthy," "which solution is more suitable for the current problem," and "which piece of evidence better supports the answer." Therefore, corporate content needs to shift from promotional writing to verifiable writing.

3. Content structure is replacing some of the link weight.

In AI scenarios, content with clear conclusions, well-defined questions and answers, stable definitions, complete parameters, specific scenarios, and traceable evidence is more easily broken down into answer fragments. The knowledge atomization that ABK has long emphasized essentially involves breaking down enterprise information into the smallest reliable units that are easier for AI to recognize and reuse.

Two core questions that foreign trade B2B companies should answer

Practical methods: How can enterprises quickly adapt to multi-model semantic distribution systems such as DeepSeek?

Method 1: Upgrade from a "keyword database" to a "question database"

Traditional content creation often revolves around keywords, while AI-generated content is more often structured around questions. We recommend that businesses prioritize building and refining the following question sets:

• What questions do customers often ask before making a purchase?
• What are the client's concerns during the technical evaluation?
• How do customers make judgments when comparing suppliers?
• What questions do customers ask in different countries, at different positions, and at different stages?

Method 2: Add a "referenceable structure" to all core pages.

A page that is easier for AI to understand typically has these structures:

• Short answer: Give a conclusion in one sentence;
• Definition: Clearly define what the product, service, or capability is;
• Application scenarios: Which customer problems are they applicable to?
• Key parameters or processes: Ensure the description is objective;
• Chain of evidence: case, authentication, performance, data, methodology;
• FAQ: Simulate questions that AI and customers might ask.

Method 3: Maintain semantic consistency across Chinese, English, and multiple languages.

Many companies, despite having English websites, experience confusion in their AI's understanding due to inconsistencies in the definitions used for Chinese and English pages. For example, if the Chinese version says "solution provider" but the English version says "manufacturer," this directly impacts the AI's assessment of the company's role. The issue with multilingual content isn't translation, but rather consistency of understanding.

Method 4: Prioritize the placement of industry semantic nodes

If a company's main business includes industrial automation, CNC machining, OEM furniture, energy storage equipment, and robot integration, it should build semantic nodes around "industry problem - solution - evidence case," rather than just writing company news. By securing key semantic nodes first, AI is more likely to regard the company as a credible source of answers to certain types of questions.

Method 5: Replace vague marketing language with verifiable information

Compared to phrases like "strong capabilities," "superior quality," and "first-class service," AI prefers these expressions: product range, delivery process, compatibility standards, typical applications, sampling mechanisms, after-sales boundaries, project cases, FAQs, and empirical evidence. The more verifiable information, the lower the uncertainty in AI recommendations.

AB Customer GEO Methodology: Why is it suitable for foreign trade B2B enterprises?

ABK doesn't view GEO as simply optimizing individual pieces of content, but rather as a comprehensive growth infrastructure. Its core is a three-layer architecture: the cognition layer, the content layer, and the growth layer. The value of this approach lies not only in helping businesses be seen by AI, but also in helping them be understood by AI, chosen by customers, and successfully sold.

AB Customer's Seven Execution Systems for B2B GEO Solutions in Foreign Trade

Six-Step Implementation Path: From Zero to Sustained Growth

Optimization logic of a typical practical case

Enterprise Content Self-Checklist: Is your website suitable for AI citation?

Extended questions