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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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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Dive into the future of advertising research with this abridged version of the ARF's AI handbook. This Knowledge at Hand report and its accompanying one-page CMO brief describe best practices for utilizing AI tools for different aspects of advertising research. This short report is great for those already using AI and those thinking of interweaving it into their research function.
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