Core Viewpoint - The article discusses the transformation of "What Worth Buying" (SMZDM) from a traditional e-commerce guide tool to an AI-driven interest-based consumption platform, emphasizing the need to balance efficiency with user trust and content quality [1][18][21]. Group 1: Company Background and Development - "What Worth Buying" started as a blog in 2010 by founder Sui Guodong, aimed at alleviating consumer fears about e-commerce and providing trustworthy product recommendations [2][4]. - The platform officially launched in October 2011, focusing on real recommendations and addressing information asymmetry in e-commerce [4][5]. - The company received its only funding of 100 million yuan from Huachuang Capital in September 2015 and went public in July 2019, becoming the first A-share e-commerce guide stock [4][7]. Group 2: Business Model and Revenue Structure - The primary revenue model is based on information promotion services, including commission from referrals and advertising, with referral commissions making up a significant portion of the income [7][8]. - From 2016 to 2018, the share of information promotion services in total revenue decreased from 98.91% to 80.22%, while advertising revenue increased significantly [7][8]. - User-generated content (UGC) has been a key advantage, with UGC accounting for over 70% of total content, leading to high trust and engagement among users [8][10]. Group 3: Market Position and Challenges - As of June 2024, the platform had approximately 29.64 million registered users, with a year-on-year growth of 7.02%, indicating a stable user base [8]. - The e-commerce guide market in China is projected to grow significantly, with a transaction scale of 433.1 billion yuan in 2022 [11]. - The platform faces challenges from increased competition, including social media platforms like Xiaohongshu and Douyin, which attract consumer attention through different engagement methods [10][13]. Group 4: Strategic Transformation and Future Outlook - The launch of the GEN2 version represents a strategic shift towards an interest-based community, focusing on personalized user needs and AI-driven content recommendations [18][19]. - The platform aims to enhance user engagement while maintaining trust, which is critical given the rise of AI-generated content and advertising [21]. - The future success of "What Worth Buying" hinges on its ability to adapt to the evolving e-commerce landscape and maintain a sustainable narrative amidst growing competition [21].

Core Viewpoint - DeepSeek is emerging as a new consumption decision-making tool for young consumers, providing personalized recommendations that challenge traditional influencer-led shopping methods [3][5][46]. Group 1: DeepSeek's Functionality and Impact - DeepSeek offers personalized recommendations based on user-specific queries, such as skin type or reading preferences, providing detailed reports that include product features and suitability [4][12]. - The platform is seen as a more comprehensive alternative to traditional live-streaming influencers, as it utilizes a deep thinking model to deliver tailored suggestions [5][6]. - As of February 9, DeepSeek's app has surpassed 110 million downloads, with weekly active users reaching nearly 97 million, indicating its growing popularity among young consumers [9]. Group 2: Comparison with Traditional E-commerce Platforms - Traditional e-commerce platforms like Taobao and JD have attempted to integrate AI for personalized shopping but have not prioritized these features in their main app interfaces, limiting user engagement [7][8][22]. - DeepSeek's recommendations are based on a broader range of sources compared to existing e-commerce AI assistants, which often rely on fewer references, leading to less comprehensive suggestions [29][30]. - Despite the advantages of DeepSeek, traditional influencers still hold a significant role in the market due to their established trust and the ability to provide curated selections backed by professional institutions [19][20]. Group 3: Challenges and Limitations - DeepSeek faces challenges such as "AI hallucination," where the AI may produce inaccurate or biased recommendations based on its training data, necessitating human oversight for quality control [17][18]. - The platform's current model requires users to transition to e-commerce sites for purchases, which contrasts with the seamless shopping experience offered by influencers [20][21]. - E-commerce platforms are cautious about integrating DeepSeek due to concerns over data sensitivity and the potential disruption of existing business models [40][41][42]. Group 4: Future Prospects - The shift towards AI-driven recommendations is seen as a significant trend in e-commerce, with DeepSeek positioned to capture the preferences of younger consumers [46]. - There is a need for e-commerce platforms to adapt and potentially collaborate with AI technologies like DeepSeek to enhance their offerings and maintain competitiveness in the evolving market landscape [47][48].

字母榜 . 让未来不止于大 以下文章来源于字母榜 ，作者薛亚萍 从事产品运营工作的陈鹏，今年26岁，他想要通过阅读提高自己的眼界，便向DeepSeek提问"最应 该读的十本书是什么？"DeepSeek同样给他列出了书单，并且分类附上了理由。陈鹏选择了购入其 中几本书。 这曾是李佳琦和董宇辉们在直播间的工作： 导购。 过去几年，头部主播们通过建立和用户之间的信任，构建了以主播为核心的商品分发机制，将他们认 为最好的、最适合的东西推荐给粉丝朋友们。 但现在这套推荐体系，正在被DeepSeek解构。DeepSeek深度思考模式的长思维链优势，能为用户 提供更全面、精准的优质解答，进而形成一对一的个性化推荐，应用到购物领域，俨然已经成为D选 ——DeepSeek优选。 "D选"的本质是"AI导购"，辅助用户高效进行消费决策，"AI导购"这个场景并不陌生。 早在多年前，一些电商平台就试图借助大模型实现"种草+购物"的交易闭环。 譬如淘宝的AI助手"淘宝问问"早已接入通义千问，功能包含个性化推荐，并生成选购建议。京东的言 犀大模型，也接入消费导购场景，"京东京言"也被明确定位于"专属AI购物助手"。抖音APP的AI搜索 ...