privacy

Analytics & Forecasting 2025

  • ARF
  • ARF

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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Privacy Rules, Trust Gained: How Regulations Change Consumer Data Sharing

  • ARF
  • ARF

Research in this Marketing Science Institute (MSI) working paper shows that privacy regulations can increase consumer willingness to share data. Using behavioral data from a popular U.S. shopping app and complementary evidence from the Consumer Expenditure Survey, the research finds that regulations in California and Virginia boosted both the volume and diversity of data sharing—especially among consumers who were initially more reluctant.

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Navigating Identity Loss: Measurement and Targeting in a Privacy-First Era

  • ARF
  • ARF Analytics Council

How is the loss of digital identifiers reshaping advertising research? This guide, by the ARF Analytics Council, offers advertising researchers a deep dive into the privacy-first landscape, covering regulatory impacts, measurement challenges and practical identity solutions—from synthetic IDs to advanced modeling—to enable successful targeting and attribution in a fragmented ecosystem.

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Too Much of a Good Thing? How Personalization in AI-Generated Ads Affects Consumer Attitudes

  • ARF
  • JOURNAL OF ADVERTISING RESEARCH

AI-generated advertising promises scalable personalization—but how much is too much? This study explores how different levels of personalization in AI-generated ads influence consumer attitudes. Through a series of experiments, the authors identify an inverted U-shaped effect: while moderate personalization enhances ad effectiveness, excessive tailoring can lead to consumer discomfort, triggering concerns about manipulation and privacy. The findings provide timely guidance for marketers navigating the trade-offs of hyper-personalized messaging in the age of generative AI.

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