在互联网时代，只要有场景，就自带流量。 现在品牌之难，就在于它即使有钱也没处花。即使花钱，传播量级也不够。 但是，也有柳暗花明之处。小试场景营销，发现即使是不那么知名的企业，并没有怎么花钱，通过场景 营销也能在很短时间内取得不错的业绩。 因为场景自带强大的传播基因，或者说场景自带流量。场景营销的认知效率之高，接近美国营销大师唐 ·舒尔茨提出的近乎理想化的整合营销传播 （IMC）。 商业的极简结构是企业战略咨询师施炜提出的认知、交易和关系三位一体。所有的商业活动，都可以纳 入上述三位一体的结构中。 口碑是认知，品牌是认知， IP（知识产权）是认知，UGC（用户生成内容）是认知，一切传播商业价 值的活动都是认知。这是本文讲的重点。 线下渠道是交易，电商是交易，即时零售是交易。一切让用户便利获得产品或服务的方式都是交易。 关系在商业中的价值，就是信任背书。历史形成的人际关系，有利于商业活动获得信任背书，降低交易 成本。同时，关系背书有助于降低认知成本。 如果说上述商业结构有一个起点的话，那就是认知。因为有认知，所以有交易；因为有交易，所以建立 了关系，包括线上关系、线下关系、社群关系。认知、交易和关系都可以建立在三 ...

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]