AI健康软测评在电商精准营销中的应用研究：路径、效益与合规策略

Research on the Application of AI Health Soft Assessment in E-Commerce Precision Marketing: Pathways, Benefits, and Compliance Strategies

摘要: 面对竞争加剧与隐私合规趋严的双重挑战，电商精准营销亟需兼顾商业效果与社会责任。本文界定的“AI健康软测评”，是一种基于用户自报告、可解释行为信号及设备侧生理近似信号的非诊断性健康倾向评估，旨在实现电商场景匹配与内容个性化。研究构建了“路径–效益–合规”三维应用框架：在路径层，提出“数据指标体系–因果细分提升建模–触达反馈闭环”实施路线，并明确了搜索、详情页等关键嵌入触点；在效益层，建立了包含转化率提升、复购优化及退货率抑制的综合评估指标与A/B测试方法；在合规层，设计了“最小必要 + 分级授权 + 用途限定 + 透明可解释 + 偏见监测”五项治理机制，并探讨了模型卡、边缘计算等技术落地路径。本文为功能性食品、可穿戴设备等健康相关品类在后隐私时代的体验式精准营销提供了理论依据与可操作的方法论。

Abstract: Faced with the dual challenges of intensifying competition and stricter privacy regulations, e-commerce precision marketing urgently needs to balance business performance with social responsibility. This paper defines “AI Health Soft Assessment” as a non-diagnostic estimation of health tendencies based on self-reports, interpretable behavioral signals, and device-side physiological proxies, aiming to achieve scenario matching and content personalization in e-commerce. The study constructs a three-dimensional application framework of “Pathways—Benefits—Compliance”. In terms of pathways, it proposes an implementation roadmap of “Data & Metrics—Causal Segmentation & Uplift Modeling—Activation & Feedback Loop”, clarifying key touchpoints such as search and detail pages. Regarding benefits, it establishes a comprehensive evaluation system including conversion uplift, repeat purchase optimization, and return rate reduction, supported by A/B testing methods. For compliance, it designs five governance mechanisms: “Data Minimization, Tiered Consent, Purpose Limitation, Transparency & Explainability, and Bias Monitoring,” and explores technical landing paths such as model cards and edge computing. This paper provides theoretical foundations and actionable methodologies for experiential precision marketing of health-related categories, such as functional foods and wearable devices, in the post-privacy era.