Data driven multi-touch attribution modeling with Markov chains
In this research paper, we used Google and Facebook conversion lift studies to calibrate our Multi-Touch Attribution results from Google Ads Data Hub (ADH). We assessed the feasibility of these conversion lift calibrations and the impact of using conversion lift results in the calibration adjustment.
The Attribution Modeling for ETL project offers a comprehensive suite of tools and methodologies for implementing various marketing attribution models, including first-touch, last-touch, linear, time decay, and U-shaped models. These models are essential for understanding the impact of different marketing channels on customer conversions.
[Project] Transformer 기반 광고 기여도 모델 제안
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