Real-Time Streaming Attribution: Sub-Second Event Processing with Apache Kafka and Flink

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Authors: Michael Forsythe Robinson
Cited by: 0

Abstract

Marketing attribution has historically been a batch process — events accumulate, models run overnight, and decisions are made on yesterday's data. This paper presents a streaming attribution architecture built on Apache Kafka and Apache Flink that processes attribution events in under 100ms. The framework integrates stateful stream processing, windowed aggregation, and real-time Shapley calculation to enable millisecond-latency attribution decisions for live bidding and budget optimization. Provides infrastructure foundation for Robinson (2026a) through (2026f).

Fields of Study & Subjects

Advanced Database Systems and Queries Digital Marketing and Social Media Data Stream Mining Techniques

Publication details

Journal / source
Zenodo (CERN European Organization for Nuclear Research)
Publication date
4 March 2026
Language
EN