CausalMMM: Learning Causal Structure for Marketing Mix Modeling

The paper introduces CausalMMM, a variational inference framework that integrates Granger causality and graph neural networks to automatically discover heterogeneous causal structures in marketing mix modeling, enabling more accurate GMV prediction and actionable insights for diverse advertisers.

AdvertisingGMV predictionGraph Neural Network

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CausalMMM: Learning Causal Structure for Marketing Mix Modeling