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cs.LG updates on arXiv.org

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Integrated Marketing Attribution: A Bayesian Framework fo...
[Submitted on 15 Jun 2026] · 2026-06-16 · via cs.LG updates on arXiv.org

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Abstract:Retail marketing measurement increasingly requires granular campaign-level insights without relying on user-level tracking. However, the two dominant approaches, Marketing Mix Modeling (MMM) and Multi-Touch Attribution (MTA), often produce fragmented insights. MMM is privacy-safe and robust for channel-level planning but is too coarse for campaign optimization, while MTA provides granular attribution but has become less reliable under increasing privacy restrictions. We propose Integrated Marketing Attribution (IMA), a unified framework that combines MMM with channel specific Bayesian attribution models to derive campaign-level effects from aggregated data. By leveraging MMM-informed priors, IMA delivers granular, privacy-safe attribution while preserving consistency with MMM.

Submission history

From: Meghana Ramanand Bhat [view email]
[v1] Mon, 15 Jun 2026 15:52:48 UTC (793 KB)

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