This study examines user interactions with AI assistants to infer purchase intent. By analyzing the text of user-initiated interactions, researchers build a bipartite network of nouns and verbs and measure the distance of specific words to "golden" purchasing words like "purchase," "buy" or "order." The study uses large language models, specifically Chat-GPT4, to annotate data with a measure of purchase intent and validates this method by comparing the results with cost-per-click (CPC) for keywords in Google Ads. The findings suggest that words used in an exchange with an AI assistant can predict purchase intent without customer tracking across interactions.
These findings have implications for using customized small versus large language models and can potentially inform advertising decisions. The study highlights the importance of understanding consumer behaviors in interactions with AI assistants. It provides a method to predict purchase intent based solely on the textual content of these interactions.
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At this Insights Studio, researchers from top institutions presented pioneering work addressing the evolving landscape of advertising. Topics of discussion included: an exploration of virtual influencers and the effectiveness of virtual influencers in real-world versus virtual-world settings, a comprehensive synthesis of over 250 studies examining the complex relationship between advertising and a company’s stock price, and a deep dive into the emerging world of the metaverse with a study on how the presence of employee avatars in virtual stores influences consumer behavior.
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The study explores the relationship between consumers' AI literacy and their receptivity to this emerging technology. What is AI literacy you ask? This refers to a person's degree of objective knowledge about AI, while receptivity refers to the extent to which a consumer is interested in having AI complete tasks. The study finds that contrary to popular belief, people with lower AI literacy exhibit greater receptivity towards AI-based products and services. What’s more, this relationship persists across a broad range of receptivity measures.
The research offers both theoretical and practical contributions. Theoretically, it contributes to the growing literature on psychological responses to AI, by focusing on understanding whether systematic differences across individuals predict differences in AI receptivity. Practically, the results suggest that attempts to increase the adoption of AI-based products and services through targeting consumers with greater AI literacy or increasing knowledge of AI may not be the most effective.
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Before the resurgence in interest in AI, virtual reality was the technology everyone was excited about. Despite the hype, advertisers have been slow to adopt VR environments. Why is this? This study, which was recently made available early online on the Journal of Advertising Research’s website, explores the potential and challenges of VR environments for advertising in its current state.
Widespread adoption has stalled, the study finds, due to obstacles such as limited reach, anticipated lack of ROI, lack of technical expertise and poor interoperability. However, the metaverse offers unique opportunities for advertisers, leaving a sort of resonating impact that other media cannot convey, because they do not engage the user in as immersive an experience as VR offers.
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