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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