Core Insights - The article emphasizes that in the internet era, having a scene inherently brings traffic, making scene marketing a powerful tool for brands [1][30] - It discusses the importance of brand recognition and how scene marketing can achieve significant results even for lesser-known companies without substantial spending [3][14] - The article outlines a simplified business structure consisting of cognition, transaction, and relationship, highlighting the cyclical nature of these elements in commercial activities [4][14] Summary by Sections Scene Marketing - Scene marketing is described as having a strong inherent ability to generate traffic and is seen as a natural fit for integrated marketing communication (IMC) [5][24] - The article posits that scene marketing can effectively utilize various media and communication modes, including high-intensity and high-density recognition patterns [26][29] Recognition and Communication Models - Five classic cognitive communication models are identified: 1. Word-of-mouth and private domain models, characterized by high recognition intensity but slow dissemination [6][16] 2. Flow advertising model, which relies on high-density recognition through mass media [7][21] 3. Interactive recognition model, which emphasizes the interaction at sales points [9][15] 4. Public domain flow model, which leverages user-generated content (UGC) for mass recognition [19][20] 5. IMC model, which integrates all recognition modes into a cohesive strategy [11][19] The Role of Cognition - Cognition is identified as the starting point of the business structure, leading to transactions and relationships, which in turn feed back into cognition [4][14] - The article highlights that effective marketing begins with cognition, which is initiated through communication [5][30] Scene as a Communication Medium - Scenes are presented as versatile communication materials with natural dissemination capabilities, making them ideal for modern marketing strategies [5][29] - The article concludes that scenes possess a unique ability to evoke emotions, which is crucial for effective communication in the video era [29][31]

Core Insights - The concept of "companionship" in AI products is gaining traction, but its definition remains elusive, leading to potential misdirection in investment and development efforts [2][3][4] - The emergence of AI technology allows products to possess a sense of "subjectivity," enabling the formation of relationships between users and AI [4][11] - Understanding the different types of relationships—downward, upward, and lateral—can help clarify the various dimensions of companionship and user needs [5][6][8] Relationship Types - **Downward Relationship**: Characterized by the user feeling "needed," similar to the bond with children or pets, where the value exchange is straightforward and unidirectional [5] - **Upward Relationship**: Defined by the user feeling "given to," where the user seeks guidance or knowledge from the AI, posing challenges in maintaining trust [6][7] - **Lateral Relationship**: Involves the user feeling "caught," where interactions are dynamic and reciprocal, requiring a higher level of engagement and understanding [8][9] Product Capabilities - To evoke a sense of being "perceived," products must possess continuous observation and understanding capabilities [10] - To create a feeling of being "needed," products should actively communicate needs to users [10] - To foster a sense of being "given to," products must have the ability to deliver value proactively [10] - To ensure users feel "caught," products need to facilitate high-quality, closed-loop interactions [10] Effective Proactivity - The new era of AI products demands a shift from passive to effective proactive engagement, where products initiate interactions and create value [11][12] - Effective proactivity is not about overwhelming users but involves timely, contextually appropriate, and positively impactful interactions [12] Long-term Value - The ability to build relationships based on trust and long-term value delivery is a unique asset for AI products, enhancing user lifetime value (LTV) and creating a competitive moat [13] Industry Reflection - The high demands placed on products by the concept of companionship raise critical questions about the viability of this as a standalone market segment [14]