AI is transforming how organizations generate insights and forecast outcomes, but questions remain about reliability and the need for human oversight. On September 14-15 in NYC, industry and academic leaders gathered to discuss integrating AI into analytics workflows and maintaining transparency.
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On September 10, DATA POEM introduced interconnected, non-linear optimization using Large Causal Models, which enable real-time, granular decision-making across all marketing levers and market scenarios. This session was designed for leaders who suspect their current optimization framework is leaving significant value on the table—and want to understand what the architectural alternative looks like in practice.
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As privacy changes make it harder for marketers to track individual customer journeys, media and marketing mix modeling (m/MMM) is experiencing renewed interest. Open-source tools from Meta, Google and the PyMC ecosystem promise to make these methods more accessible, particularly for organizations without the resources for customized proprietary models. In this MSI working paper, Julian Runge and Koen Pauwels evaluate the leading open-source approaches, examining their capabilities, differences and tradeoffs. Their analysis shows that while automation can democratize sophisticated marketing measurement, using these tools responsibly requires careful attention to model assumptions, diagnostics, calibration and validation.
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AI-optimized, omnichannel campaigns are changing how media are planned, activated and measured. Drawing on in-depth interviews with advertisers and providers, the ARF Cross-Platform Measurement Council’s Attribution Working Group examined omnichannel campaign tools such as Google Performance Max and Meta Advantage+, exploring their potential to simplify execution, optimize across channels and improve performance. Their research also identified important tradeoffs, including transparency, testing capabilities and ongoing measurement and governance challenges.
Member Only AccessDrawing on in-depth interviews with advertisers and providers, the ARF Cross-Platform Measurement Council’s Attribution Working Group examined omnichannel campaign tools such as Google Performance Max and Meta Advantage+, exploring their potential to simplify execution, optimize across channels and improve performance.
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Retail Media Networks (RMNs) have become a cornerstone of modern advertising, but measurement practices across networks remain inconsistent and difficult to compare. This new ARF study examines 16 major RMNs to uncover how advertising assets, attribution systems, incrementality testing and closed-loop measurement are actually implemented in practice. The findings reveal that while reporting dashboards may appear unified, the underlying measurement systems often rely on disparate sources of retailer data, platform reporting, modeling and privacy-safe integrations. The report offers practical guidance for advertisers evaluating retail media investments and highlights the growing need for industry-wide measurement transparency and standards.
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