Large-model AI generation engines such as Google (Gemini), Microsoft (MAI), ChatGPT, Claude, LLaMA, Grok, Falcon, DeepSeek, and others have fully permeated the search and content generation experiences across various regions and countries worldwide. Therefore, individuals and companies—especially those with foreign trade websites—must integrate these engines as essential traffic channels. This also includes numerous domestic platforms like Doubao, Wenxin, Yuanbao, Pangu, Tongyi, Hunyuan, and Kimi.
What are the content function characteristics of generation engines?
In fact, generation engines feature diverse and multifunctional capabilities, including search, consultation, reference lookup, and question-answering. They mark web addresses as references through citations; however, this has also led to intense competition in content display, along with flexible and varied content results. As a result, companies, enterprises, or websites must align with the content characteristics of generation engines—namely crawling, identification, analysis, and adoption—ultimately achieving GEO (Geographic Optimization) display effects.
What essential considerations must be followed for GEO?
AI-generated content must never be used.
Websites must optimize their code structure.
Gray-hat methods must not be employed.
Proper SEO (Search Engine Optimization)/SGE (Search Generative Experience) knowledge is a must.
Content data must be compatible with Google AI and meet its adoption requirements.
Additionally, it is crucial to take into account and align with the technical characteristics of each generation engine. Particularly in GEO optimization, targeted adaptation of the content information structure is necessary. Furthermore, it is essential to dynamically verify GEO data performance, then make timely adjustments and supplements to achieve tracking and optimization effects. Since GEO exhibits random and dynamic performance, it is imperative to secure an absolute high-probability of effective results.