Optimization of Marketing Strategies Based on User Behavior and Consumption Psychology—A Case Study of Emotional Counseling Paid Services on rednote

社交电商通过“内容 + 社交”模式重构知识服务消费场景。基于小红书平台Z世代用户(日均使用时长72分钟)的情感咨询消费研究显示，用户决策呈现显著分化特征：搜索型用户依赖长尾关键词(如「分手复合技巧」)触发需求，经历平均7.2篇笔记筛选、68%高时长主页验证及4.8天决策周期；算法推荐用户则受场景化视频驱动(观看完整率92%)，12小时内可完成转化。研究据此构建“内容运营–信任机制–算法协同”模型，通过峰终定律强化内容记忆点、建立用户证言可视化机制及优化LBS标签匹配，实现头部博主咨询转化率提升19.8%。该模型揭示了社交电商中情感焦虑向知识消费转化的内在逻辑，为平台商业生态优化提供双重路径：短期提升服务转化效率，长期建立情感需求与内容供给的动态平衡。Social e-commerce platforms are reshaping knowledge service consumption through their “content + social” model. Focusing on rednote’s Gen Z users (with a daily average usage time of 72 minutes), this study investigates emotional counseling paid services and reveals distinct decision-making patterns: search-driven users rely on long-tail keywords (e.g., “breakup reconciliation tips”) to trigger demand, undergoing a decision cycle averaging 7.2 post screenings, 68% prolonged homepage verification, and 4.8 days; algorithm-driven users, however, are influenced by scenario-based videos (92% full-view rate) and complete conversions within 12 hours. Building on these findings, the study proposes a “Content Operation - Trust Mechanism - Algorithm Synergy” model, which enhances content memorability via the peak-end rule, establishes a visualized user testimonial mechanism, and optimizes LBS tag matching (e.g., prioritizing legal counseling services for users in Tier-1 cities). This framework elevates conversion rates for top bloggers by 19.8%. The model elucidates the intrinsic logic of transforming emotional anxiety into knowledge consumption in social e-commerce, offering dual pathways for platform optimization: short-term efficiency improvement in service conversion and long-term dynamic equilibrium between emotional demand and content supply.