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.
Virtual influencers are computer-generated personas that engage with audiences on social media and in the metaverse. This study explores whether virtual influencers are more effective in advertising when they include real-world elements, such as interacting with real humans or endorsing real-world products. The research is grounded in the Computers Are Social Actors (CASA) framework and investigates how social cues and product types influence consumer perceptions of authenticity and attitudes toward both the influencer and the brand.
The findings suggest that virtual influencers are perceived as more authentic and favorable when they are shown alongside real humans and endorse real-world products. This perceived authenticity positively impacts consumer attitudes toward the virtual influencer and the brand, providing valuable insights for advertisers looking to leverage virtual influencers in their marketing strategies.
More analysis and the full study is available to ARF members.
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