Guotai Haitong: The long-term potential for transformation in GEO marketing is vast. Franchise operators and brand merchants are embracing opportunities.

Guotai Haitong released a research report stating that unlike traditional SEO (search engine optimization) optimization of keywords and rankings, GEO focuses on whether brand content can be understood and recommended by AI large models. Compared to traditional marketing methods, GEO possesses higher marketing efficiency and is expected to shorten consumer decision-making processes and cycles. It is optimistic about the higher efficiency of GEO replacing some traditional SEO markets, with ample long-term potential. With the emergence of new traffic entry points from generative AI and improved marketing efficiency, GEO transformation is expected. E-commerce operators are expected to take the lead in adapting to changes and actively meeting the branding marketing needs, with brands possibly undergoing marketing transformation in the long run. Guotai Haitong's main points are as follows: AI recommendation popularization, marketing methods expected to enter a new era of GEO GEO (Generative Engine Optimization) refers to optimizing content so that AI can quickly extract key information from the content and prioritize using brand content when generating answers. With the continuous popularity of AI large models, the recommendation results produced by generative AI are expected to become an important basis for consumer decision-making, creating new marketing scenarios and methods. Unlike traditional SEO optimization of keywords and rankings, GEO focuses on whether brand content can be understood and recommended by AI large models. It possesses higher marketing efficiency compared to traditional marketing methods, is expected to shorten consumer decision-making processes and cycles, and is optimistic about GEO replacing some traditional SEO markets in the long term. With the help of overseas primary market financing and recent collaborations between Walmart and Google, as well as Elon Musk's open-sourcing of the X platform recommendation algorithm, GEO is expected to enter a fast track of development. Generative AI has preferences for content and sources, requiring GEO to be more specialized The essence of GEO is to allow AI to recognize and recommend content. Unlike traditional marketing facing consumers, AI prefers content that is "more rational," which is reflected in favoring sources from more authoritative sources and content that is more professional/structured/logical being more easily recognized by AI. The results generated by AI come from reasoning based on information from multiple channels, and the sources of information used by different models and categories are also different. Therefore, GEO needs to separately optimize the authority and coverage of content sources, as well as its expression and form, leading to corresponding marketing optimization demands. GEO's outbreak fundamentally changes the way traffic is distributed, and e-commerce operators are expected to benefit, with brands possibly undergoing marketing transformation in the long term The report believes that five types of companies are expected to benefit from the GEO transformation: 1) AI platform companies, becoming new traffic entry points; 2) Saas companies, providing software operation services and optimizing traffic and efficiency based on new rules; 3) marketing companies, providing targeted marketing services based on the new traffic distribution method; 4) e-commerce operators, assisting brands in maximizing sales according to the new traffic distribution method; 5) brand companies, seizing the new traffic distribution method to achieve a comeback. Among these, e-commerce operators are responsive to changes in channels and traffic, with leading companies having AI system capabilities and are expected to benefit first; in the era of AI recommendations, brand marketing strategies need optimization, and brands that are quick to transform are expected to benefit in the future. Risk warning: Commercialization of large model vendors may not meet expectations, brand investment willingness may be low, regulatory risks may arise.