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E-Commerce Letters 2025
基于用户行为与消费心理的营销策略优化——以小红书情感咨询付费服务为例
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Abstract:
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.
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