研究发现位置数据在广告精准投放中价值随用户使用时间变化，早期关键，后期可替代。
The Privacy-Utility Trade-Off of Location Tracking in Ad Personalization
- 结合经济理论与机器学习，量化位置数据与行为数据的互补与替代关系。
- 冷启动阶段位置数据提升投放效果近20%，后期行为数据可替代位置数据。
- 揭示广告个性化中的隐私-效用权衡，指导企业何时启用位置追踪。
企业收集大量用户行为与地理数据。行为数据反映数字足迹，地理数据体现物理足迹。二者结合存在显著隐私风险，需明确其对商业目标的价值及互补或替代关系。本文融合经济理论、机器学习与因果推断，基于某大型亚洲国家领先应用内广告平台的数据，发现地理数据在用户行为历史较短的冷启动阶段最具价值，此时与行为数据互补，使定位性能提升近20%；随着用户行为数据积累，地理数据作用转向可被替代，仅靠行为数据即可捕捉用户异质性。研究揭示了广告个性化中的核心隐私-效用权衡，为管理决策提供依据。
原文摘要 · Abstract (English)
Firms collect vast amounts of behavioral and geographical data on individuals. While behavioral data captures an individual's digital footprint, geographical data reflects their physical footprint. Given the significant privacy risks associated with combining these data sources, it is crucial to understand their respective value and whether they act as complements or substitutes in achieving firms' business objectives. In this paper, we combine economic theory, machine learning, and causal inference to quantify the value of geographical data, the extent to which behavioral data can substitute for it, and the mechanisms through which it benefits firms. Using data from a leading in-app advertising platform in a large Asian country, we document that geographical data is most valuable in the early cold-start stage, when behavioral histories are limited. In this stage, geographical data complements behavioral data, improving targeting performance by almost 20%. As users accumulate richer behavioral histories, however, the role of geographical data shifts: it becomes largely substitutable, as behavioral data alone captures the relevant heterogeneity. These results highlight a central privacy-utility trade-off in ad personalization and inform managerial decisions about when location tracking creates value.
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