Dialogue with Wancheng Cloud Commerce: Publishing Articles ≠ GEO Optimization, Large Models Don't Just Push What They're Fed | Overseas Pioneers

Introduction:

Looking at the global market and exploring the second growth curve has become a definite direction. However, how to go global still tests the wisdom and courage of every Chinese enterprise. There are numerous paths for going global, such as brand expansion overseas, supply chain expansion overseas, and cross - border e - commerce. Yet, there is never a one - size - fits - all answer. Markets like North America, Southeast Asia, the Middle East, and Latin America are vast but also come with their own challenges. Behind every long - distance expedition is the exploration of Chinese enterprises. More Chinese figures are emerging on every distant coastline.

The "Global Pioneers" column aims to seek out global benchmarks in different fields, analyze real - world cases from a professional perspective, distill methodologies through consensus, and discover new possibilities in differences.

"Help me put together a set of clothes suitable for a seaside vacation."

"Help me recommend a Western restaurant suitable for a date."

"With a budget of 3,000 yuan, which floor - sweeping robot is the most cost - effective?"

Such Q&A sessions with AI are happening to hundreds of millions of users around the world. In the past, people would input these questions into search engines like Baidu and Google, which led to SEO (Search Engine Optimization) marketing. As the traffic entry point shifts from search engines to AI tools, GEO (Generative Engine Optimization) has emerged.

Different from the traditional SEO, which aims for "search result ranking", the core goal of GEO is to make brand information be preferentially cited and recommended in AI - generated answers. In an era when AI comprehensively penetrates user information acquisition and consumption decision - making scenarios, for global enterprises, doing well in GEO means seizing a new traffic entry point.

What is the fundamental difference between the logic of GEO and SEO? Why do some people say that GEO is a false proposition? How should global enterprises plan their GEO strategies? How can small and medium - sized enterprises start with low costs... With these questions that global enterprises are concerned about, we had a special conversation with Tan Li, the general manager of the brand global expansion department of Wancheng Cloud Commerce, to analyze how to make enterprises be seen, trusted, and recommended to users by AI in the era of AI search.

1. GEO is called the evolution of SEO in the AI era. Compared with SEO, whose core lies in search result ranking, what is the key to GEO optimization? What is the core difference between it and traditional SEO?

Tan Li: The core difference is that traditional SEO is more about "rule - based competition", while GEO is more like "trust - based competition". In the past, when doing SEO, our goal was to rank the page on the first page of Google so that users would click on it. But now, many users directly ask questions in AI and don't even click on the links. So the problem you need to solve is how to make AI "cite you" or even "recommend you" in its answers.

So the key to GEO is, first, whether you are a "trusted source" (whether anyone in the whole network recognizes you); second, whether your content can be understood, disassembled, and reused by AI; and finally, whether your content has a complete evidence chain, such as data, cases, or third - party endorsements.

2. After GEO, some people have also proposed the concept of AEO. What is the difference between the two?

Tan Li: Many people use these two concepts interchangeably, but I personally distinguish them in this way: AEO is more about "Q&A result optimization", and its core is to make your content directly become the standard answer to a certain question, such as FAQs and selected summaries. GEO is broader. It faces generative AI, not just answering one question, but participating in the "output after multi - source information integration". So AEO is more about "structural skills", while GEO is more about "overall brand and content ecosystem".

3. The concept of GEO has sparked extensive discussions in the past two years. Why should enterprises pay attention to GEO at this time? In the context of the continuous increase in AI search penetration, what strategic position should GEO occupy in an enterprise's marketing system?

Tan Li: Let me share some very real changes: Nowadays, users are getting more and more used to asking AI directly instead of screening search results by themselves. Moreover, in the front - end decision - making process of many industries, AI has begun to replace the "information collection stage". Also, some customers may form a judgment about you in AI before even opening your official website. So enterprises can't ignore GEO. The reality is right here. I think GEO occupies a very crucial position in an enterprise's marketing system. It won't replace SEO but is a "second traffic entry point" parallel to SEO, and may even become one of the main entry points in the future.

4. How to understand that some enterprises think GEO is a false proposition after some attempts, or that they can continuously feed corpora to large models by themselves?

Tan Li: I think this is a bit of a misunderstanding of the working mechanism of AI. A large model doesn't "recommend whatever you feed it". It has several screening logics: First, whether the information is consistent (for example, whether it can be verified from different sources); second, whether the source is credible (whether it is a long - existing content asset); third, whether it is mentioned on multiple platforms (rather than from a single source). So feeding corpora by yourself is essentially just a single - point information input, and it's difficult to form a "trust network".

However, I also understand why some people say GEO is a false proposition because there are indeed many "false practices", such as only doing in - site content, only piling up AI articles, and not doing external verification. These basically hardly work.

5. When an enterprise plans its overseas GEO marketing, what key steps does it need to go through? What differences will there be in the paths for enterprises in different industries and of different scales?

Tan Li: From a practical perspective, there are four key steps: First, disassemble how your customers screen suppliers and what this path is like. Second, reconstruct your content structure, including the official website, blog, FAQs, cases, etc., all in a way that can be "understood by AI". Third, build an external trust system. For example, review platforms, media exposure, social media discussions, and industry citations are all very important. Fourth, conduct multi - channel distribution to continuously make your content visible and cited on different platforms.

Different enterprises may have obvious differences in two aspects: industry complexity and brand foundation. For example, the medical and industrial industries require more professional endorsements than other industries. Enterprises with a brand can more easily expand their influence, while those without a brand need to "make up for trust" first.

6. During the implementation process, how should enterprises make changes or even reshaping in terms of content strategy and technical infrastructure to meet both AI understanding and user resonance?

Tan Li: In terms of content strategy, it is necessary to have a clear structure, the information should have evidence and data sources, and the expression should be close to real - person communication. In the technical aspect, the basics are more likely to be ignored: for example, Schema structured data (Product, FAQ, Article, etc.), robots, index, hreflang and other basic configurations, and also the page readability. In summary, it is to create "understandable content".

7. When planning a GEO global expansion plan, what is the most easily overlooked but crucial link for enterprises? For small and medium - sized enterprises lacking a professional team, what feasible solutions or cooperation models are there?

Tan Li: After serving so many cross - border enterprises, we found that the most easily overlooked point is actually "letting AI access you". It sounds basic, but many enterprises will fall into misunderstandings in practice: for example, robots block AI crawlers, the page noindex setting is incorrect, or there is a mess in multi - language... These will directly lead to the situation that no matter how much content you create, AI can't see it.

The second easily overlooked point is off - site trust building. Many people still think that "publishing articles = doing optimization", but GEO values more: reviews, evaluations, social media discussions, and media citations.

For small and medium - sized enterprises, I suggest two paths: ① Lightweight: Focus on a niche area to create in - depth content + a small amount of high - quality external endorsements; ② Cooperative: Find a service provider with resources to do integration (content + channels + data), and don't blindly make mistakes by yourself, as the cost will be very high.

8. When an enterprise selects a GEO service partner, what core capabilities of the partner should it focus on (such as whether it has a vertical industry knowledge base, cross - platform channel resources, an effect monitoring and analysis system, etc.) to avoid the trap of "ineffective investment"?

Tan Li: This question is very crucial because there are indeed quite a few "concept - based service providers" now. I suggest focusing on four capabilities:

First, industry understanding ability. Whether they understand your industry, not just being able to write content.

Second, content production quality. Whether there are real cases and whether they have localization capabilities, rather than just pure AI batch generation.

Third, channel and distribution ability. Whether they have overseas platform resources, such as media, communities, and evaluation channels.

Fourth, data monitoring system. For example, after a period of time, see if it has been cited by AI, which content is effective, and what the ROI is.

If the partner can only talk about "how many articles to publish", it can basically be directly excluded.

9. The popularity of Seedance 2.0 at the beginning of 2026 made the industry see the possibility of AI video generation leaping from "trial - and - error like drawing cards" to "industrial production". What does the "cost collapse" of only 8 yuan for a 10 - second promotional video mean for the content production logic of cross - border e - commerce?

Tan Li: This change is quite subversive. In the past, making videos was costly and time - consuming, so the competition was about "whether you have content". But now that the cost is close to zero, it means that content is no longer a barrier, and the "effectiveness of content" has become the barrier.

10. When the video production cost approaches zero and everyone can generate high - quality content in batches, how will the focus of enterprise competition change? From the perspective of GEO planning, how should enterprises build marketing thinking in the AI era?

Tan Li: When the supply is infinite, what is scarce changes. I think future competition will focus on three points: First, cognitive occupation, whether you are in the users' minds; second, trust structure, whether it has been verified by multiple parties; third, data ability, whether you can quickly iterate content.

From the perspective of GEO, I think enterprises should establish a new way of thinking: They should regard brand content as an asset for long - term accumulation, and at the same time build up trust such as word - of - mouth and reviews little by little. More importantly, before publishing content, ask yourself: Will AI use it? Will users trust it? Avoid creating "self - indulgent" content.

11. The popularity of Seedance 2.0 has also triggered discussions about deepfake and copyright. When cross - border e - commerce sellers use such tools to generate marketing materials, how should they avoid potential risks of portrait rights and copyright?

Tan Li: This issue really can't be ignored. I suggest trying to avoid using recognizable figures (especially public figures) as generation materials. The material sources should preferably use commercially licensed libraries. For brands, logos, music, etc., the scope of authorization should be confirmed. Special caution should be taken with content related to medical and efficacy, as the compliance risks are higher. After all, AI can help you reduce costs, but it can't help you be "exempt from liability".

* The views expressed are from the interviewed institutions or individuals and are for reference only.

This article is from the WeChat official account "Comprehensive Service Port for Zhejiang Enterprises Going Global", author: Zhejiang Enterprises Going Global.