Core Insights - The shift from traditional SEO to Generative Engine Optimization (GEO) reflects a fundamental change in how brands seek visibility in search engines, moving from keyword-based strategies to AI-driven recommendations [1][3][5] Group 1: Changes in Search Engine Dynamics - The monthly traffic for chatgpt.com is projected to reach approximately 5.7 billion by July 2025, with a 6% month-over-month increase, indicating a significant rise in AI search usage [1] - Traditional search engines are experiencing a drastic decline in traffic delivery, with news site click-through rates dropping by up to 79% when AI Overviews appear on Google results pages [2] - User behavior is shifting from a traditional search-click model to a direct question-answer interaction, necessitating a change in marketing strategies for businesses [3][5] Group 2: Differences Between SEO and GEO - GEO is fundamentally different from SEO due to the lack of transparent rules in AI search engines, making it a more unpredictable environment [5][6] - While SEO relies on backlinks and keyword optimization, GEO focuses on citations and the semantic understanding of content, emphasizing the importance of high-quality, original content [11][12] - Research has identified nine strategies that can enhance visibility in GEO, with some methods yielding up to a 40% increase in exposure [8][9] Group 3: Market Demand for GEO Services - The emergence of GEO services is driven by businesses' concerns about visibility in AI searches, leading to a proliferation of service providers ranging from traditional SEO firms to new startups focused on AI search [13][14] - Companies are adopting various strategies, including knowledge graph construction, authoritative content partnerships, and structured data deployment to enhance their AI search visibility [15][16][17][18] Group 4: Pricing and Effectiveness of GEO Services - The pricing for GEO services is inconsistent, with some companies charging monthly fees ranging from hundreds to thousands of dollars, often tied to performance metrics [22][23] - The effectiveness of GEO services is difficult to quantify due to the black-box nature of AI models, leading to a lack of standardized evaluation metrics [20][21] Group 5: Risks and Challenges in GEO - The market is also seeing the rise of low-quality GEO services that promise quick results but often deliver subpar outcomes, highlighting the need for businesses to be cautious [25][28] - Major AI search platforms are implementing stricter policies against low-quality content, indicating a move towards prioritizing credible and verifiable information [30][29] Group 6: Brand Strategies for GEO - Brands are advised to create machine-readable content and actively monitor their visibility in AI search results to mitigate anxiety about being overlooked [31][32] - Investing in unique, credible content rather than relying on shortcuts or low-cost services is essential for long-term success in the evolving landscape of AI search [33]