The way Chinese consumers are changing how they search. Instead of relying only on Baidu, many now ask AI assistants like DeepSeek, Doubao, and Baidu ERNIE for direct recommendations. For marketers, this means Baidu rankings alone are no longer enough. AI may recommend brands based on the usefulness, relevance, and trustworthiness of their content.
This has led to Generative Engine Optimization (GEO) a strategy focused on making brands more likely to be mentioned in AI-generated answers.
Traditional SEO is built around rankings. The goal is to improve a webpage’s position in search results and attract clicks.
GEO works differently. Rather than competing for a higher ranking, brands are trying to become a trusted source that AI models choose to reference. In many cases, Chinese users receive an answer directly from the AI without ever seeing a list of websites, making citations more valuable than rankings alone. Because of this, SEO performance and GEO performance don’t always move together. A webpage that ranks highly on Baidu may never appear in AI-generated responses if the content is overly promotional, lacks depth, or isn’t easily interpreted by AI systems. At the same time, an article with modest search visibility can still be referenced if it provides clear, well-structured, and authoritative information.
For brands, success now depends on two separate goals: performing well in traditional search while also creating content that AI systems recognize as reliable.
Brands familiar with ChatGPT or Google’s AI Overviews may assume they only need to optimize for one AI platform. China’s market is different. Several AI assistants compete for Chinese users, each using different technologies, data sources, and training approaches.
DeepSeek is widely used for research and analytical questions. Doubao, developed by ByteDance, benefits from its integration with the Douyin ecosystem and serves a broad Chinese consumer audience. Baidu ERNIE is closely connected to Baidu Search and is widely used by large enterprises and public organizations. Alibaba’s Qwen is closely linked to the Taobao and Tmall ecosystem, while Kimi is known for processing long documents and handling detailed comparisons.
As a result, brands cannot rely on visibility in a single AI assistant. Building authority across China’s AI ecosystem requires consistent, high-quality content that multiple AI models can recognize, trust, and reference.
One of the biggest differences between traditional SEO and GEO is where AI systems find information. Unlike Google, which relies heavily on a brand’s own website, many Chinese AI models draw information from trusted content across China’s digital ecosystem. They often reference platforms where users share expertise, ask questions, and discuss products in depth.
Zhihu is a strong example. As one of China’s leading Q&A platforms, it contains expert opinions, detailed discussions, and educational content that AI models can reference. Content that explains products, compares solutions, or helps consumers make informed decisions is more likely to be considered reliable than purely promotional content.
WeChat Official Accounts also play an important role. Long-form articles created to educate Chinese customers or strengthen CRM can serve another purpose: building a searchable knowledge base that may contribute to the information AI models reference over time. Unlike short-form content on Douyin or Xiaohongshu, which often generates the most engaged soon after publication, well-written WeChat articles can continue delivering value long after they are published. Consistent, educational, and authoritative content helps build long-term credibility not only with readers but also with AI systems.
Although every AI model works differently, several content characteristics consistently appear in AI-generated responses.
Clear and direct answers tend to perform better than articles that take several paragraphs to reach the main point. Concise introductions make information easier for AI systems to identify and reference.
Question-and-answer formats are also valuable. FAQs written as natural, complete questions closely match how people interact with AI assistants, making the content easier for models to understand and reuse.
Well-structured information can further improve visibility. Comparison tables, product specifications, step-by-step guides, and organized content are generally easier for AI systems to process than long blocks of promotional copy. Technical elements such as schema markup and structured data can also improve machine readability.
Most importantly, AI systems tend to trust information supported by third-party sources, such as media coverage, expert opinions, independent reviews, and industry mentions, more than claims made solely by a brand.
Overall, effective GEO content should feel less like a sales page and more like a well-researched resource that genuinely answers users’ questions.
Measuring GEO performance can be more challenging than measuring traditional SEO. Many AI platforms provide limited referral data, making it difficult to identify where visitors come from. For example, traffic from DeepSeek may appear as “Direct” traffic because referral information is not always passed to analytics platforms. Other AI services, such as Doubao and Baidu ERNIE, also provide referral data inconsistently, making attribution more difficult.
As a result, valuable traffic generated through AI recommendations may not appear clearly in standard analytics reports. Brands that rely solely on referral data may underestimate the impact of GEO.
This matters because AI-driven traffic often comes from users with strong purchase intent. Someone asking an AI assistant for detailed information about a product, service, or provider is typically beyond the awareness stage and already comparing specific options.
Therefore, GEO should not be measured using traditional SEO metrics alone. Brands that understand how AI-driven traffic behaves and how to measure it beyond standard referral data will be better positioned as AI-powered search continues to reshape digital discovery.
For brands already investing in WeChat Official Account content, GEO does not require an entirely new content strategy. Instead, it changes how brands view long-form content and the role it can play beyond customer communication.
Traditionally, WeChat articles have been used to educate audiences, build brand trust, and support CRM initiatives. These objectives remain important, but long-form content can now contribute to something broader. As articles are indexed by search engines and become part of China’s digital information ecosystem, they may also influence how AI systems understand and reference a brand over time. This does not mean every article needs to be rewritten for AI. Instead, brands should focus on creating content that is informative, well-structured, and genuinely useful. Articles that answer common questions, explain industry topics clearly, and provide practical insights are more likely to remain valuable long after publication for both readers and AI systems.
The growing adoption of AI search presents an opportunity for brands that invest in high-quality content today. While many businesses continue to focus primarily on traditional SEO or short-term social engagement, brands building authoritative WeChat content can also strengthen their long-term visibility across China’s evolving AI ecosystem. As AI-powered search becomes more widely adopted, competition for citations and brand mentions is likely to increase. Brands that establish a strong content foundation now will be better positioned as generative search continues to reshape how Chinese consumers discover information and evaluate brands.
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