This article explains how to design and implement a scalable ad attribution platform, covering data collection, real‑time processing with Kafka, storage in HBase, deduplication strategies, attribution models, and configurable media integration to maximize ROI for marketers.
This article introduces Feizhu's advertising diagnosis platform and explains how recent causal inference techniques, especially the NO TEARS algorithm and Bayesian‑network‑based attribution, are applied to identify the root causes of performance fluctuations across the ad delivery funnel, improve diagnostic accuracy, and guide optimization decisions.
FAE, Alibaba’s high‑performance distributed MPP engine, stores billions of user‑behavior events in a time‑ordered AFile model and uses stateless masters, importers, mergers and workers with Redis and MySQL metadata to deliver sub‑second, 10‑100× faster ad‑attribution queries across ad‑hoc, offline and near‑real‑time scenarios such as frequency, path and funnel analysis.
