Companies run many marketing experiments, but most A/B tests are analyzed independently—limiting what firms can learn about how customers respond to interventions over time. This research introduces a hierarchical Bayesian framework that integrates data from many experiments simultaneously to estimate customer-level responsiveness to marketing. Using large-scale field experiments, the model decomposes treatment effects into customer, campaign and timing components and uses these insights to improve targeting decisions. The results show that most variation in marketing effectiveness comes from persistent differences in customer responsiveness, enabling firms to better identify who to target and when.
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On February 19, 2026, the ARF Attribution Working Group hosted a deep‑dive session focused on the rapidly evolving landscape of Shoppable Ads, exploring how new formats are emerging, how they function across platforms, and how measurement practices are adapting. The discussion delved into shoppable ads across retail media networks, social platforms, display inventory, and connected TV environments, highlighting how these formats are redefining the relationship between media exposure and commerce outcomes.
The conversation built on the Working Group’s broader initiative to evaluate five emerging advertising channels, an effort informed by industry interviews and an agency/advertiser survey. The session was moderated by Chip Godfrey (Director, Data Strategy, J.D. Power, and a member of the ARF Attribution Working Group). The panelists were Yannick Koger (Sr. Manager, NA Retail Measurement Solutions, Pinterest), Jared Oliver (Manager, Advanced Analytics & Modeling, Ocean Spray and a member of the Attribution Working Group), and Phil X. Jackson (Director, Global Digital Marketing Effectiveness & Innovation, Haleon).
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Media planning frameworks often assume that channels operate independently or compete within the same funnel stage. This research challenges that assumption by demonstrating that the largest performance gains come from cross-funnel synergies, particularly between upper-funnel television, middle-funnel digital media and lower-funnel promotions. Using a large-scale CPG dataset and a novel estimation–optimization approach, the study shows that explicitly modeling these interactions can materially improve media allocation decisions while also significantly increasing incremental revenue.
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Advertisers rely on identity crosswalks as a critical tool for linking identifiers across data sets and platforms without exposing personal information. This white paper from the Identity Resolution Working Group of the Cross-Platform Measurement Council provides a brief practical introduction to crosswalks and how to implement them effectively. It outlines common operational models, covers use cases for brands, agencies and publishers, and addresses accuracy, privacy and match rate considerations. The guide offers advertising researchers and data practitioners clear, actionable steps for navigating the complex identity landscape.
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