Core Insights - AI search is rapidly replacing traditional search methods, with ChatGPT alone achieving over 1 billion monthly active users and 25 billion daily interactions, approaching Google's 14 billion search volume [1] - Consumer behavior is fundamentally changing, as users now directly ask AI for product recommendations instead of conducting individual searches [1] - The importance of mastering Answer Engine Optimization (AEO) is highlighted, as brands need to ensure their products are included in AI-generated answers to remain relevant [1] Group 1: AEO Strategies - Companies should define target keywords based on query volume and product differentiation, categorizing them into three types: must-win core keywords, competitive but opportunistic keywords, and experimental new keywords [2][5] - Understanding the behavior differences among various answer engines is crucial, as performance on one platform may not translate to others [4][7] - Creating specialized and specific content is essential for being cited in AI responses, emphasizing the need for in-depth knowledge of product niches [10] Group 2: Content and Engagement - Generating "surround sound" around products through user-generated content and social media mentions can enhance visibility in AI searches [10][14] - Engaging on platforms like Reddit, where mentions can significantly impact AI citations, is recommended [17] - Using structured comparisons and listicles is favored by AI engines, with about one-third of citations coming from comparative content [18][20] Group 3: Monitoring and Adaptation - Companies should focus on brand influence rather than just click-through rates, as many AI searches result in "zero clicks" [22] - Regularly tracking citation changes is vital, as nearly half of the cited domains can change within a month, indicating a need for dynamic strategy adjustments [24] - The shift towards AI search represents a fundamental change in discovery mechanisms, creating significant growth opportunities for early adopters [25]