AI can accelerate campaign measurement, but how do you know the results are reliable? On July 15, the ARF Cross-Platform Measurement Council led an exploration of validating AI-powered measurement models and systems. Industry practitioners shared validation approaches, frameworks, and tools that work based on real case studies. Plus, attendees had the opportunity to ask questions in a Q&A.
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Marketers have access to more data than ever before, yet many still struggle to answer the most important question: Did the marketing effort truly make a difference? And if so, how? Lots of metrics exist. So, is collecting more metrics the best approach to evaluating true impact? In this guest article for The Advertising Club of New York, ARF Senior Director of Research & Insights Tracy Adams argues that the future of measurement isn't about collecting more metrics—it's about integrating multiple approaches to build a more complete, decision-ready understanding of marketing impact.
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As retail media expands across onsite, offsite and in-store environments, buyers are looking beyond basic attribution to determine whether advertising is actually driving incremental sales. In a guest article for The Advertising Club of New York, Tracy Adams, PhD, ARF Senior Director of Research & Insights, examines findings from the second phase of the ARF Retail Media Network Standardization Project, revealing what advertisers and agencies say they need to make retail media measurement more comparable, transparent and trustworthy.
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Artificial intelligence is becoming deeply embedded in advertising and marketing, but adoption alone is no longer the story. In this guest article for The Advertising Club of New York, ARF Senior Director of Research & Insights Tracy Adams examines findings from the ARF's latest AI research, which reveals that while organizations are increasingly confident in AI-generated outputs, many are still developing the testing, governance and measurement practices needed to ensure those outputs deliver meaningful business value.
Randomized controlled trials remain the gold standard for measuring advertising effectiveness, but they are often too costly and complex to deploy across every campaign. This MSI Working Paper introduces Predicted Incrementality by Experimentation (PIE), a new framework that uses data from a limited set of experiments to predict causal advertising effects for campaigns that are not directly tested. The research demonstrates that PIE can dramatically outperform traditional attribution metrics, offering marketers a practical way to scale causal measurement without scaling experimentation itself.
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As generative search and agentic AI transform how consumers discover, evaluate and purchase products, traditional identity resolution and attribution systems are struggling to keep pace. This new paper by the Identity Resolution Working Group of the ARF Cross-Platform Measurement Council, introduces the concept of “Delegated Identity”—a framework designed to reconnect human intent with AI-driven actions in an increasingly AI-mediated marketplace. The report explores the emerging identity gap, evaluates industry readiness and outlines the challenges and opportunities facing marketers, identity providers and AI platforms.
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As generative AI becomes increasingly integrated into research workflows, what does "human in the loop" actually mean? This latest installment in the ARF and MSI's Psychology of Gen AI series explores how researchers and large language models can work together to develop rigorous research designs—and why human judgment remains indispensable throughout the process. By comparing multiple AI-generated experimental designs and refining them through expert evaluation, the study demonstrates that AI is most valuable as a collaborator that expands possibilities, not as a replacement for methodological expertise.
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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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