AI technological transformation has profoundly impacted daily life, and with the rise of AI search demand, GEO is emerging as a new paradigm for corporate marketing. This shift is driving competition logic away from the traditional SEO's bidding-based recommendations towards an AI citation competition in the era of large language models. The firm believes that new-era traffic portals will migrate to AI applications offering superior user experiences. Under this trend, Alibaba possesses both top-tier domestic large model capabilities and the most extensive mass consumption ecosystem. This positions the company not only to provide premium scenarios for B-end merchants to implement GEO marketing strategies but also to build an intelligent consumption closed loop around generative AI, ultimately leveraging enhanced user experience to boost traffic and achieve a positive feedback cycle. Alibaba-W (09988) is recommended.

Shenwan Hongyuan's key viewpoints are as follows: The rise of AI search is triggering a transformation in information access points, with GEO creating a new marketing paradigm for enterprises. Recently, the user scale and penetration rate of traditional search engines have declined, while the user base for AI search is experiencing rapid growth, poised to gradually become a new mainstream channel for information acquisition. Against this backdrop, the user search path is shifting from "search-click webpage" to "question-directly obtain answer," and the logic of traffic competition is upgrading from the "click game" of the SEO era to the "citation competition" of the large model era. In this context, Generative Engine Optimization (GEO) provides a new path for corporate marketing. It aims to enhance a brand's "citation rate" and "recommendation probability" within AI-generated answers by optimizing content structure, semantic expression, and authoritative endorsements. This enables enterprises to transition from competing for search clicks via bidding to a new optimization strategy centered on understanding and influencing AI decision-making processes.

GEO establishes a new marketing logic distinct from traditional SEO, moving corporate marketing efforts from "influencing users" forward to "influencing the model." Within the GEO framework, enterprises systematically optimize marketing content by studying large language models' preferences regarding content structure, expression methods, and authority. The goal is to increase the content's recognition rate, citation rate, and recommendation probability within AI-generated answers. In the new search and recommendation system centered on large models, the primary entity that enterprises need to understand becomes the model itself. As GEO typically covers the entire marketing implementation process and employs continuous dynamic tracking and algorithmic optimization for iterative strategy, compared to traditional SEO's reliance on short-term traffic acquisition through bidding rankings, this mechanism allows enterprises to achieve more stable, high-quality exposure. Consequently, it is expected to realize higher effective conversion rates and ROI within AI-generated content recommendations. According to IDC and the China Academy of Information and Communications Technology, the global GEO industry market size is projected to exceed $12 billion by 2025, with a three-year compound annual growth rate (CAGR) of 145%, and is expected to maintain rapid growth through 2027.

GEO and intelligent commerce are reshaping information and transaction traffic portals; Alibaba, with its top-tier models and rich mass consumption ecosystem, is well-positioned to succeed in the future large model era. With the launch of UCP, Google, in collaboration with retail giants like Shopify, Walmart, and Target, is establishing unified interaction standards. This enables AI-driven conversational processing across the entire journey of product discovery, recommendation, ordering, payment, and after-sales service, laying the foundation for future intelligent agent commerce. Aligning with this trend, Alibaba is actively deploying AI traffic portals domestically. By deeply integrating its self-developed large model, Tongyi Qianwen, with its e-commerce and mass consumption ecosystem, Alibaba provides users with an integrated AI Q&A and task execution experience. This effectively uses AI to connect multi-platform traffic within its ecosystem and also provides the scenario for B-end merchants to implement GEO marketing strategies.

Risks include weaker-than-expected terminal consumption, intensifying industry competition, and slower-than-anticipated development of cloud business.