Forecasting is a valuable tool to help businesses reduce risk and operate more effectively and efficiently. At FORECASTING 2024, leading practitioners and academics shared how they are building forecasting models to understand purchase journeys, the impact of major events on businesses and how brands can reach buyers amidst the lack of first-party data.
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This study explores how divergent delivery in A-B testing affects the accuracy of online advertising experiments. It highlights the role of algorithmic targeting and user heterogeneity in confounding test results, offering guidance for marketers to improve their experimental designs.
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The ARF Member AI workshop introduced members to the potentialities of various AI platforms and tools to boost their work productivity. The workshop covered how LLMs such as Copilot, ChatGPT, Gemini and Claude can be employed in three main areas: presentations and reports, advertising research and meetings. Issues such as privacy and security of using AI, as well as the current limitations and challenges of the technology were also discussed. The hands-on, interactive workshop was an opportunity for all those interested in best practices and guidelines for using AI to learn how to interweave such programs into their daily work processes.
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Explore the latest findings from the ARF Attention Measurement Validation Initiative. The phase two report is a comprehensive examination of various attention measurement methods used in creative testing. It concludes with reflections on the challenges of attention measurement, as well as some suggestions for advertisers on how to choose and evaluate attention measurement providers.
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This study explores the potential of generative AI, specifically large language models (LLMs) and multimodal models (LMMs), to revolutionize generational study within consumer research. It examines how these advanced AI tools can enhance various stages of the research process, from idea generation to reporting.
Privacy regulations have served as the impetus for a renewed interest in contextual targeting. To be effective, an ad must be related to its context but different enough to stand out. This working paper from the Marketing Science Institute (MSI) at the ARF presents a comprehensive model leveraging eye-tracking data and XGBoost algorithms to forecast the effectiveness of ad placements in real time.
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