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Sensor Tower's Full Funnel Digital Intelligence Playbook

2026年6月4日·3 分钟阅读

摘要

Sensor Tower发布《全漏斗数字情报手册》,主张在数字营销中整合网站、移动应用及广告投放数据,以超越单一指标的局限,实现用户旅程的全局洞察。手册基于对家居与生活方式、化妆品及银行三大类别的竞品分析,展示如何利用Digital Advertising、Mobile App、Web和Audience Insights四大模块,构建从触达到转化的完整归因框架。

在家居与生活方式零售商案例中,Wayfair在2025年保持最大网站流量,而Kohl’s以16%的同比增速领跑Web流量增长,Macy‘s紧随其后达10%,加剧了头部竞争。值得注意的是,虽然Macy’s和Kohl‘s均拥有大量仅使用APP的用户(分别占42%和38%),但高端品牌如Crate and Barrel和Williams-Sonoma则几乎完全依赖Web流量。在MAU和下载量方面,Wayfair遥遥领先,而Kohl’s与Macy‘s在APP端表现接近,显示出相似的移动端投入。

然而,Audience Insights揭示了关键差异:尽管APP用户规模相似,Macy’s用户以Fashionista和Sneakerhead等时尚导向群体为主,将Macy‘s视为潮流目的地;Kohl’s则更吸引Wholesale Shopper、Shopaholic和Home Cook等注重价值与家庭实用的用户。这种用户画像的根本差异,意味着两者的用户获取(UA)策略必须分道扬镳,而非简单复制对手的打法。

手册最终提出数字广告是补齐漏斗的最后一环,但并未在预览中披露全部数据,而是鼓励读者下载完整报告以获取化妆品和银行类别的详细分析。通过整合多源数据,广告主可避免单维度决策的盲区,实现基于LTV和ROAS的精准投放,提升整体广告变现效率。Sensor Tower的框架为MMP、SKAN等归因工具提供了更丰富的上下文,助力品牌在复杂的数字生态中实现增量提效。

分析师点评

这篇文章的价值在于,它将网站流量、App表现、受众画像与广告投放串联成全漏斗分析,打破了数据孤岛。对于UA经理而言,Macy’s与Kohl’s案例揭示了:即使App用户规模相近,受众画像的差异(时尚驱动 vs. 实用主义)会直接决定广告创意的调性与渠道选择。当前零售业普遍面临iOS隐私政策后的归因困境,这种多维度交叉验证的方法,或能帮助广告主更精准地分配预算。

值得关注的是,文章中提及的‘Web流量增长’与‘App独家用户’的对比信号,暗示了不同品牌在渠道侧重上的战略分野——这为竞品分析提供了新视角。

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