当老板要求分析竞品的Deep Research功能时，如何系统性地完成一份有价值的报告？本文通过真实案例拆解竞品分析的完整流程，让你掌握 一套让战略洞察落地为可执行建议的方法论。 前面三篇讲了为什么做、评什么、怎么选竞品。这篇我用一个真实案例，把整个流程串起来走一遍。 案例背景就是开头提到的那个场景：老板说"现在其他产品都出了Deep Research功能，去帮我分析一下他们做的效果"。 拿到这个需求，我会怎么做？ 第一步：先别急着动手，把需求拆清楚 很多人拿到需求就开始打开竞品截图，这是不对的。我会先问自己几个问题： 1.1 这份报告是给谁看的？ 老板让做的，那主要受众就是老板和管理层。他们关心的是战略层面的东西：竞品在押注什么方向？我们应该怎么跟进？有没有风险？ 这意味着我的报告要结论前置，先说判断再给证据，不要铺垫太多背景。 1.2 Deep Research到底是什么？ 在分析竞品之前，我得先搞清楚这个功能本身是什么。 Deep Research是OpenAI在2025年2月首次推出的功能，核心特点是：AI能自主进行网络搜索、整合多个来源的信息、深度分析数据，最后生成一份完整的 研究报告。 和普通的A ...

Core Insights - The article emphasizes the importance of correctly identifying competitors before conducting detailed analysis, as selecting the wrong competitors can render the entire report useless [1][2]. Group 1: Definition and Classification of Competitors - Competitors are defined as products that can divert user attention, time, or budget, not just those that offer similar products [2]. - Three categories of competitors are identified: direct competitors, indirect competitors, and potential competitors [2]. Group 2: Direct Competitors - Direct competitors are characterized by operating in the same market, targeting the same user base, and offering similar core functionalities, leading users to choose between them [3][4]. - An example provided is the competition between Doubao and Kimi, both AI dialogue assistants targeting C-end users [4][5]. Group 3: Indirect Competitors - Indirect competitors address similar problems but differ in product form, core functionality, or usage scenarios, potentially diverting users in specific contexts [6][7]. - Midjourney is cited as an indirect competitor to AI dialogue products, as it serves the broader need for AI-assisted creation but through different means [8][9]. Group 4: Potential Competitors - Potential competitors currently differ significantly in product form and functionality but may compete for the same user resources in the future [10]. - Douyin is mentioned as a potential competitor due to its large user base and capability to introduce AI features, which could disrupt the market [11][12]. Group 5: Analysis Directions - When selecting competitors, companies should consider the analysis direction, which can include business strategy, specific functionalities, and user overlap [13]. - Business direction focuses on the competitor's commercial logic and revenue models, while functional direction examines specific features and technical paths [14][15]. - User direction analyzes user overlap and migration costs, which can inform operational strategies [16][17]. Group 6: Sources for Finding Competitors - Companies can identify competitors through various channels, including app stores, industry reports, social media, and direct user feedback [18][19][20][21][22]. - App stores provide a direct source for similar products, while industry reports offer insights into market dynamics and player rankings [19][20]. Group 7: Practical Example - A practical example is provided for selecting competitors for the Deep Research feature, categorizing them into direct, indirect, and potential competitors based on their functionalities and market positioning [23][24]. Group 8: Summary Principle - The core principle for selecting competitors is to first understand who is competing for the same users, which informs the focus of the analysis [25].

Core Insights - Manus emerged as a promising AI agent with a viral demonstration video, attracting 2 million users for reservations within a week and a valuation of $500 million after a $75 million investment from Benchmark [1][3] - However, the initial excitement faded quickly as users found the product's performance lacking, revealing that it relied heavily on third-party large model APIs and struggled with complex tasks [3][4][9] - The broader AI agent industry faces challenges, with predictions indicating that 40% of AI agent projects may be eliminated by 2027 due to high costs and unclear business models [9][10] Group 1: Rise and Fall of Manus - Manus was initially celebrated for its capabilities, such as resume screening and travel planning, leading to significant media attention and investment [3][4] - As users began to test the product, they encountered performance issues, including slow response times and inaccuracies in task execution [4][6][9] - The high subscription cost, ranging from $19 to $199 per month, did not align with the product's actual performance, leading to user dissatisfaction [6][9] Group 2: Industry Challenges - The AI agent market is characterized by a proliferation of products that merely layer a user interface over existing large models, resulting in a lack of differentiation and high vulnerability to cost increases [10][11] - Many AI agents are criticized for being "Frankenstein" products, combining various functionalities without effectively addressing user needs, leading to poor performance in real-world applications [12][14] - The high operational costs of general-purpose agents, combined with low user retention and conversion rates, create a precarious financial situation for many startups in the sector [14] Group 3: Successful Strategies in the AI Agent Space - Companies that focus on niche markets and provide tailored solutions are more likely to succeed, as they address specific pain points for clients [18][20] - Genspark, a company that pivoted to AI agents, achieved significant revenue by focusing on office automation and data analysis, demonstrating the importance of finding a specialized market [20][21] - Successful AI agents emphasize return on investment (ROI) for clients, offering transparent pricing models and clear value propositions [22][24] Group 4: Building Sustainable Ecosystems - Companies that integrate user feedback and community innovation into their products can create a competitive advantage and ensure continuous improvement [25][27] - The development of ecosystems around AI agents, where third-party developers contribute to the platform, enhances functionality and attracts more clients [27][28] - The future of AI agents lies in their ability to combine technology with real-world applications, focusing on creating tangible value rather than merely chasing trends [28]