A Large Scale Heterogeneous Treatment Effect Estimation Framework and Its Applications of Users' Journey at Snap
PositiveArtificial Intelligence
- A new framework for estimating Heterogeneous Treatment Effects (HTE) has been developed by Snap, utilizing experimental data from millions of Snapchat users. This framework combines results from various experiments to identify previously unmeasurable user characteristics and provides stable treatment effect estimates at scale, focusing on user influenceability and sensitivity to ads.
- This advancement is significant as it enhances Snap's ability to target ads more effectively, leading to a reported improvement in key business metrics that exceeds typical significance thresholds, potentially boosting advertising revenue and user engagement.
— via World Pulse Now AI Editorial System
