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The ARF Member AI Workshop

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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ARF Attention Measurement Validation Initiative: Phase 2 Report

  • ARF ORIGINAL RESEARCH

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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How to Calculate Reach and Frequency Using Virtual IDs (VIDs)

Current existing methods used to calculate reach and frequency of a campaign or media schedule are known to have deficiencies in measuring cross-device ad exposure. Restrictions to protect digital privacy complicate cross-platform exposure measurement even further. Multiple global research organizations have turned to a concept known as “virtual people,” to overcome these limitations in order to produce aggregate reach and frequency estimates. This report by the ARF Analytics Council provides a foundational overview of VIDs for a broad audience, providing ARF members with a stronger understanding of this vital topic.

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Predicting Attention to Advertising Through Machine Learning

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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