虎嗅APP·2025-08-18 13:39Core Insights - The article discusses how AI is reshaping the e-commerce landscape, moving away from traditional search-compare-buy models to AI-driven purchasing experiences [5][6][9]. Group 1: Google's Crisis - Google's real crisis is not a decline in search volume but a shift in value creation, as AI changes the position of value creation in the search economy [7][9]. - AI agents like ChatGPT can directly answer consumer queries, reducing the need for users to click on Google ads, thus disrupting the traditional information intermediary role of Google [8][9]. - The decline in search volume for Safari, as noted by Apple's Eddy Cue, indicates a structural challenge for Google's business model, necessitating a new approach to adapt to AI-driven consumer behavior [8][9]. Group 2: AI Transformation of Purchasing Behaviors - Purchasing behaviors are categorized into five types, each undergoing varying degrees of transformation due to AI [10]. - Impulse buying may see increased frequency and precision as AI predicts and guides consumer impulses based on historical data [13]. - Routine essentials will be optimized by AI agents that track prices and make purchases at the right time, potentially altering consumer habits [14]. - Lifestyle purchases will benefit from AI's deep learning of personal style and preferences, offering tailored recommendations [15]. - Functional purchases will require AI consultants capable of providing personalized advice, akin to human sales experts [15]. - Major life purchases will still rely on human decision-making but can be enhanced by AI in information gathering and risk assessment [16]. Group 3: Amazon and Shopify's Competitive Advantages - Amazon and Shopify possess stronger defensive capabilities compared to Google, primarily due to their control over behavioral data and customer loyalty programs [18][20]. - Amazon's behavioral data reflects actual purchasing behavior, providing valuable insights for AI agents, while Google lacks this depth of data [19]. - Shopify empowers merchants, creating network effects that enhance its platform's indispensability in the AI era [21]. Group 4: Infrastructure Challenges for AI Commercialization - The article identifies four foundational challenges for AI in commerce, including the need for better data systems to capture user experiences accurately [23]. - The challenge of unified APIs is more political than technical, as current disparities hinder efficiency in AI agent operations [24]. - Identity and memory management pose complex challenges involving privacy and adaptability, requiring AI to understand consumer preferences deeply [24]. - Embedded capture of consumer preferences through real-time interactions presents innovative potential for AI agents [25]. Group 5: Future of E-commerce Platforms - The emergence of AI will lead to a reshaping of e-commerce platforms, with competition shifting from traditional metrics to data quality, AI capabilities, and ecosystem integration [29]. - New types of platforms, such as AI-native e-commerce platforms and vertical AI agents, are expected to arise, focusing on specific categories and providing tailored experiences [29]. - A new business model may emerge where consumers subscribe to AI shopping agents, allowing these agents to make purchasing decisions on their behalf [29]. Group 6: AI's Impact on Brand Marketing - AI will fundamentally alter brand marketing, as traditional mass marketing will decline in effectiveness due to consumers relying on AI agents for recommendations [30]. - Brands will need to ensure consistency and credibility in their messaging, as AI agents will analyze brand narratives for coherence [31]. - The potential for extreme personalization will allow brands to offer customized products based on detailed consumer preferences captured by AI [33].