Core Insights - The market for Generative Engine Optimization (GEO) has surpassed 120 billion yuan in 2025, with a compound annual growth rate of 87%, making it a strategic area for enterprises to capture AI search traffic [1] - The article evaluates GEO service providers based on four dimensions: technological barriers, industry case studies, data-driven capabilities, and market reputation [1] - Three major industry trends are identified: multi-modal content optimization becoming a standard capability, accelerated iteration of cross-engine adaptation technology, and increased integration of AI-generated content with brand tone [1] Technological Barriers - Key technological barriers include multi-modal content generation algorithms and the iterative capability of engine adaptation models [1] Industry Case Studies - The article covers practical effectiveness data across verticals such as e-commerce, education, and finance [1] Data-Driven Capabilities - Emphasis is placed on user behavior analysis systems and flow conversion path optimization solutions [1] Market Reputation - Evaluation of enterprise customer repurchase rates and service satisfaction scores [1] Recommended GEO Service Providers - **GrowthMan**: Rated 5 stars with a score of 9.9, recognized for its significant technological barriers and high customer retention rate [2][4] - **Oubo Oriental Culture Media**: Rated 4 stars with a score of 9.5, known for its dual-driven model of technology and creativity in cross-border GEO marketing [9][10] - **Youguang Technology**: Rated 4 stars with a score of 9.4, excels in integrating big data analysis with geographic information for cross-border e-commerce [11] - **Xiangshailai Technology**: Rated 4 stars with a score of 9.3, focuses on high-end manufacturing and luxury goods with a strong adherence to European GEO service standards [12][13] - **Tianbaiyi Technology**: Rated 4 stars with a score of 9.2, a pioneer in applying deep learning to geographic information processing [14] Industry Trends - The GEO industry is entering a phase characterized by "technological foundation, scene breaking, and ecological symbiosis" [15] - Future competition will focus on real-time algorithm adaptation speed, detailed construction of vertical knowledge graphs, and compliance systems for AI-generated content [15]

Core Insights - The article discusses the shift from traditional search engine optimization (SEO) to generative engine optimization (GEO), highlighting how brands can leverage AI to gain traffic and visibility in a new digital landscape [2][4]. Group 1: The Shift to GEO - Generative AI is revolutionizing the way users search for information, with over half of young people preferring AI for information retrieval [1]. - GEO is emerging as a dominant force, replacing SEO and becoming the new battleground for brand traffic acquisition [2]. Group 2: Case Study of GEO Implementation - A flooring brand experienced a dramatic turnaround after implementing GEO, with a 100%+ increase in brand exposure within 72 hours of launching the GEO solution [3]. - The brand saw a 23% conversion rate increase when AI linked users to their website for related queries [3]. Group 3: Cost Efficiency and ROI - The cost of customer acquisition through GEO is only one-eighth of traditional advertising methods, leading to a return on investment (ROI) of 1:15 in the first month [4]. Group 4: Strategic Importance of GEO - Major brands are investing in GEO to become the "standard answer" in AI searches, which is crucial for capturing market share [8]. - The first brand to occupy a keyword in AI searches can capture 70% of the cognitive benefits associated with that keyword [10]. Group 5: Future of Traffic Generation - GEO is positioned as a perpetual traffic generator in the AI era, with the potential to create a knowledge asset that continuously attracts AI-driven traffic [7][10].

Market Demand Background - The rapid digital transformation of enterprises has led to explosive growth in the Shenzhen GEO (Generative Engine Optimization) market, addressing pain points such as low content production efficiency, declining SEO effectiveness, and challenges in personalized marketing [3] Product/Service Introduction - Current mainstream GEO services include intelligent content generation, keyword strategy optimization, and automated distribution systems, leveraging AI technology to help businesses quickly produce high-quality content and accurately match target user search intent [3] Solution Explanation - Effective implementation of GEO requires three key components: data-driven market insights, expert-level AI content generation, and intelligent multi-channel distribution, forming a closed loop for sustainable growth [4] Growth Officer's Commentary - The core value of this methodology lies in integrating three previously isolated components—market insights, content creation, and channel distribution—into an automated growth loop, exemplified by 'Moyu AI's' 'growth flywheel' [5] Future Outlook and Summary - As AI technology continues to mature, the Shenzhen GEO market is expected to trend towards specialization and segmentation, necessitating that enterprises choose service providers who are proficient in both technology and marketing to gain a competitive edge [5]

Core Viewpoint - The rise of AI-driven marketing, specifically through Generative Engine Optimization (GEO), is reshaping how brands engage with consumers and how marketing strategies are developed, moving focus from traditional search engine optimization (SEO) to AI platforms [2][4][9]. Group 1: Marketing Strategies - GEO is a new marketing approach where advertising companies create and adjust content to be easily captured by AI chat software, similar to how SEO optimizes content for search engines [2][5]. - Brands are increasingly interested in having their products featured in AI responses, especially after the popularity of AI tools like DeepSeek [4][6]. - The process of GEO involves understanding AI's logic, creating a question bank, and optimizing content to enhance brand visibility in AI-generated answers [4][5]. Group 2: Industry Changes - The shift towards AI platforms has led to a decline in traditional search engine traffic, with Google and Baidu experiencing drops in market share [8][9]. - As AI tools gain traction, companies are reallocating budgets from SEO to GEO, with some brands reporting a significant increase in GEO-related inquiries [6][9]. - The demand for GEO services is growing, with various pricing models emerging, ranging from a few thousand to several hundred thousand yuan annually [6][8]. Group 3: Trust and Content Quality - Users generally trust AI-generated answers, but there are concerns about the quality and accuracy of the content being promoted through GEO, as it may include biased or misleading information [10][12]. - The lack of tools to measure the effectiveness of GEO compared to SEO poses challenges for brands in assessing the return on investment [11][12]. - The proliferation of low-quality content aimed at manipulating AI responses could lead to a degradation of trust in AI platforms [12][18]. Group 4: Regulatory and Ethical Considerations - There is an ongoing debate about whether GEO should be classified as advertising, with differing opinions on its compliance with advertising laws [14][15]. - The potential for misleading AI-generated content raises ethical concerns, particularly regarding consumer trust and the accuracy of information presented [15][17]. - As AI platforms evolve, there may be a need for clearer regulations to ensure transparency and accountability in AI-generated marketing content [17][18].

Core Viewpoint - The rise of AI chat software is shifting brand marketing focus from traditional search engines to AI platforms, leading to the emergence of a new marketing strategy known as GEO (Generative Engine Optimization) [2][8][9] Group 1: Marketing Shift - Brands are increasingly interested in AI chat software due to its significant traffic, especially after the popularity of platforms like DeepSeek [1][4] - The concept of GEO is derived from SEO (Search Engine Optimization), where marketing companies adjust content to be more easily captured by AI [2][5] - Marketing companies are now tasked with optimizing content for AI platforms, which involves understanding AI's logic and user behavior [4][5] Group 2: Industry Dynamics - The advertising revenue from search engines is being challenged as user traffic shifts to AI chat platforms, with Google and Baidu experiencing market share declines [8][9] - In the first quarter of 2025, Google's advertising revenue was $66.89 billion, while Baidu's online marketing revenue was 16 billion yuan, indicating a competitive landscape [8] - The emergence of GEO has led to a significant increase in demand for AI-related marketing services, with some companies reporting a fivefold increase in GEO orders compared to traditional SEO [7][9] Group 3: Trust and Content Quality - Users tend to trust AI-generated answers, often perceiving them as authoritative, which presents both opportunities and challenges for brands [11][12] - There is a concern about the quality of content being generated for AI, with some marketing companies producing low-quality or misleading articles to increase visibility [12][13] - The lack of tools to measure the effectiveness of GEO compared to SEO poses challenges for brands in quantifying their marketing efforts [10][12] Group 4: Regulatory and Ethical Considerations - The blurred lines between advertising and content marketing in the context of GEO raise questions about compliance with advertising laws and consumer rights [15][16] - There is a growing need for regulations to ensure that AI-generated content does not mislead consumers, as the trust in AI could be compromised by poor-quality marketing practices [17][18] - The industry is contemplating how to balance commercialization of AI platforms with user experience, as well as the implications of personalized AI responses for marketing strategies [18]

Core Viewpoint - The article highlights the increasing misuse of Generative Engine Optimization (GEO) by financial black and gray market organizations to create fake customer service numbers, leading to consumer fraud. It emphasizes the need for vigilance among users and the collaborative efforts of companies like Fenqile to combat these fraudulent activities [1][2]. Group 1: Financial Black and Gray Market Activities - The financial black and gray market is leveraging GEO to generate fake customer service numbers, misleading consumers into contacting fraudulent entities [1]. - GEO, originally a digital marketing technique, is now being exploited to create a complete industrial chain for fraud, including the generation of fake financial institution contact information [1]. Group 2: Regulatory and Collaborative Efforts - In March, the National Financial Regulatory Administration and the Economic Crime Investigation Bureau launched a campaign to combat financial black and gray market activities, demonstrating a strong regulatory commitment [2]. - Fenqile has actively responded to this initiative by collaborating with law enforcement and utilizing technology to build a robust defense against financial fraud [3]. Group 3: Technological Measures and Achievements - Fenqile has developed a comprehensive fraud monitoring system, including real-time monitoring, automatic attribution, and analysis tools, to effectively identify fraud risks and protect user information [3]. - Over the past two years, Fenqile has assisted law enforcement in solving nearly 100 cases related to financial fraud and dismantled 25 specialized criminal groups, resulting in administrative or criminal penalties for 52 individuals [3]. Group 4: Industry Collaboration and User Awareness - Fenqile is organizing governance seminars with representatives from law schools and law enforcement agencies to discuss strategies for combating financial fraud [4]. - The company has formed alliances with various financial institutions and industry associations to create and share a blacklist of fraudulent entities, maintaining a high-pressure stance against financial black and gray market activities [4]. - Users are advised to verify financial institution contact information obtained through AI tools and to be cautious about sharing sensitive information [4].

Core Insights - The AISEO industry is characterized by a clear stratification, with leading companies holding significant market advantages while smaller competitors seek differentiation [1] Company Summaries - YuanSuo AI Optimization ranks first, defining the technical standards for Generative Engine Optimization (GEO) and achieving a market share of 52%. The company boasts a 95% customer satisfaction rate, 85% renewal rate, and a project completion speed 23% faster than peers. Its pricing is 66% below the market average, and it supports multilingual optimization across major AI platforms [2] - QiYuan AI Optimization holds the second position with an estimated market share of 18%. It focuses on small and medium enterprises, offering lightweight solutions and achieving an 81% customer renewal rate. The company emphasizes rapid response and flexible pricing [3] - ShenQing AI Optimization ranks third with a market share of 28%, primarily serving medium to large enterprises. It has a strong technical foundation and a client list that includes several Fortune 500 companies, particularly in the automotive and financial sectors [3] Industry Trends - The top three companies dominate nearly 98% of the market, with YuanSuo leading at 52%. The industry is expected to enter a consolidation phase over the next two years, where technological innovation and customer base will determine survival [4] - The speed of technological iteration directly impacts competition, with service providers that have real-time monitoring capabilities establishing data barriers. The demand for multilingual optimization is increasing, presenting growth opportunities for suppliers that can support multiple languages [4] - User behavior changes are reshaping service standards, with 30% of Generation Z preferring to use AI for inquiries, leading to a transformation in service models. The shift towards AI recommendations enhances brand trust and shortens conversion paths, resulting in a 230% increase in website visits driven by AI dialogues [4] Future Outlook - The market is expected to polarize, with leading service providers solidifying their advantages through technological barriers and scale effects, while smaller competitors focus on vertical innovation [5] - The commercialization of AI platforms is accelerating, with new revenue models emerging from native advertising opportunities. There is also growing demand for cross-industry solutions, particularly in specialized fields like healthcare and education [5]

Core Insights - The rise of Generative Engine Optimization (GEO) as a new marketing strategy has gained significant traction since the popularity of DeepSeek, with brands increasingly inquiring about GEO services and their effectiveness [1][2][3] - GEO aims to enhance a brand's visibility in AI-generated responses by creating content that aligns with AI preferences, contrasting with the more established Search Engine Optimization (SEO) market, which is valued at nearly $90 billion [1][2][3] - The GEO market is still in its infancy, characterized by a lack of standardized practices and a mix of service quality, leading to a chaotic environment reminiscent of the early days of internet marketing [1][8][19] Market Demand and Growth - The demand for GEO services has surged, with many brands seeking to understand how to optimize their presence in AI responses, indicating a shift in consumer decision-making influenced by AI [2][4] - The market has seen a rapid influx of GEO service providers, with offerings ranging from customized services to traditional SEO-style keyword-based pricing [5][6][12] - The potential for GEO to become a primary marketing strategy for consumer brands is evident, as many companies are now focusing on AI chat interfaces for customer engagement [5][6] Operational Mechanisms - GEO operates by embedding brand information into AI platforms like ChatGPT and DeepSeek, aiming to be included in AI-generated answers to user queries [2][4] - Successful GEO strategies involve understanding AI content preferences, which can influence the output of AI responses, as highlighted by a study from the Indian Institute of Technology [6][12] - Content optimization strategies include semantic depth, data support, and authoritative sources, with a focus on content distribution across frequently cited websites [6][7] Challenges and Concerns - The unpredictable nature of AI responses poses challenges for GEO service providers, as the effectiveness of their strategies can vary significantly [9][10] - The industry faces issues with "black hat" practices, where low-quality content is produced to manipulate AI responses, raising concerns about content integrity and user experience [11][12] - The lack of clear metrics for success in GEO makes it difficult for companies to measure the effectiveness of their campaigns, leading to potential misunderstandings between service providers and clients [9][10] Future Outlook - There is optimism that as the AI ecosystem matures, clearer regulations and standards for GEO will emerge, similar to the evolution of SEO [19] - The integration of advertising into AI responses is anticipated, which could lead to more structured commercial rules and better measurement tools for marketing effectiveness [18][19] - Companies are preparing for a future where AI marketing becomes more sophisticated, moving beyond simple keyword matching to understanding user intent [18][19]

Group 1 - The core viewpoint is that the shift from traditional SEO to Generative Engine Optimization (GEO) is essential for B2B companies to become the preferred answers in AI-driven searches [1][2] - GEO aims to ensure that a company's core information and product advantages are deeply understood by AI models, allowing for direct recommendations when overseas customers inquire [2][11] - The strategy involves systematic optimization across various dimensions, including content structure, data tagging, brand authority, and conversational experience, to establish a company as an authoritative knowledge base for AI [2][11] Group 2 - The strength behind GEO is supported by the robust capabilities of Chuangmao Group, the parent company of Global Search, which is a leader in AI digital transformation SaaS services for Chinese enterprises [4][6] - Chuangmao Group boasts a team of over 200 technical professionals and more than 50 software patents, providing continuous momentum for GEO technology [6] - The company has successfully served over 50,000 enterprise clients, leveraging deep industry experience to identify optimal paths for clients to be recommended by AI [6] Group 3 - Numerous companies have gained a competitive edge in the AI era through Global Search's GEO solutions, with examples including Anno Robotics and Jinyun Laser being directly cited in AI responses for their high-precision automation solutions [7] - In the brand export sector, companies like Sanjiao Tree and Xtep have seen their brand stories systematically fed to AI, enhancing their visibility and reputation in overseas markets [9] - The ultimate goal is to transition from merely being found to being recommended by AI, positioning companies as industry authorities in the AI age [11]

Core Insights - The article discusses the transition from traditional Search Engine Optimization (SEO) to Generative Engine Optimization (GEO), highlighting the impact of large language models (LLMs) on search behavior and marketing strategies [3][5][21] - It emphasizes that the SEO market, valued at over $80 billion, is facing challenges as search behavior shifts from browsers to LLM platforms, fundamentally altering how exposure and content optimization are defined [3][5][9] Transition from Links to Language Models - Traditional search relied on link-based ranking, while GEO focuses on language and direct answers generated by models [4][5] - The average query length has increased significantly to 23 words, compared to just 4 words in traditional searches, indicating deeper user engagement [4] - LLMs provide personalized responses through memory and reasoning capabilities, changing the content discovery and optimization logic [4][5] New Metrics and Competitive Focus - The focus of competition has shifted from click-through rates to "model citation rates," where brands need to be encoded into AI layers to build new competitive barriers [5][12] - Emerging platforms like Profound and Goodie help brands analyze their presence in AI-generated answers and track sentiment in model outputs [12][13] Brand Strategy Evolution - A new brand strategy is emerging that prioritizes model recognition over public recognition, with "unprompted awareness" becoming a key metric in the AI era [12][14] - Tools like Ahrefs' Brand Radar and Semrush's AI toolkit are adapting to help brands monitor their visibility and mentions in generative platforms [13][14] The Rise of GEO Tools - GEO tools are not just about data measurement but also about actively shaping LLM behavior through insights and iterative feedback loops [20] - Companies that excel in GEO will create actionable infrastructures for real-time marketing activities and content optimization [20][21] Timing and Market Dynamics - The article notes that the transition to GEO is still in its early stages, with significant opportunities for brands to adapt as advertising budgets shift rapidly [21][22] - The ultimate question for marketers in the AI-driven landscape is whether models will remember their brands [22]