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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A new ARF Psych of GenAI experiment reveals that large language models apply a rigid, rule-driven logic when evaluating privacy scenarios—even when humans typically shift their reasoning based on framing, emotion and social context. Unlike consumers, who blend intuition, feeling and social perspective into their judgments, GPT-4o relied on a single internal rule across all testing conditions: data use is acceptable only with explicit consent. This consistency offers value for certain analytic tasks but exposes limits for advertising research that depends on emotional nuance and context-sensitive consumer insight.
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On September 29-30, the ARF and MSI co-produced the inaugural ANALYTICS & FORECASTING conference, exploring the evolving role of modeling in market research and forecasting, with a particular focus on the opportunities and limitations of synthetic data. Attendees engaged in critical discussions about the opportunities and limitations of modeling in market research applications and heard practical strategies and solutions from leading researchers and practitioners.
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Keith Smith, PhD (Managing Director, MSI) and Tracy Adams, PhD. (Senior Director, Research & Insights, ARF), report on their major takeaways from the recent MSI/ARF Analytics & Forecasting conference.
