Livestreaming is rapidly transforming e-commerce, but which strategy works best—brand-led sessions or influencer promotions? This study of 163 apparel brands reveals that in-house livestreaming delivers more consistent sales boosts than most influencer collaborations, offering key insights for marketers navigating the live commerce boom.
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This research explores the downstream and upstream effects of consumer-to-consumer (C2C) gift subscriptions compared to personal subscriptions in the context of live streaming. It reveals that C2C subscriptions significantly enhance customer lifetime value by encouraging more tips and comments and highlights the importance of creator performance quality in driving subscription behaviors.
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The ARF's 7th Annual Privacy Study surveyed 1,242 American consumers to understand their attitudes towards online privacy, data sharing and trust in institutions. This impactful perennial survey for the first time this year even gauged people’s feelings on AI. The study revealed a decline in perceived knowledge about online privacy, with only 40% of respondents feeling well-informed, down from 46% in 2023. Trust in media and brands also declined, particularly among younger demographics, while medical and financial institutions retained higher trust levels.
The study also highlighted increased resistance to data collection, even when tied to personalization or improved ad experiences. Consumers showed a growing aversion to sharing sensitive information and a heightened sensitivity to data breaches. Emerging concerns about AI and its impact on privacy were also noted, with AI platforms ranking among the least trusted institutions.
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This study explores how dialect wording in advertisements can enhance consumer recall and deepen brand connections. By examining six studies conducted in China, the research demonstrates that dialect advertisements evoke a stronger feeling of groundedness, leading to better recall compared to standard Mandarin ads. The findings are supported by both adjusted recognition scores and eye-tracking data. The study also identifies boundary conditions such as bicultural identity integration, traveler versus settler orientation, and brand characteristics (warm versus competent) that influence the effectiveness of dialect advertising. These insights provide valuable guidance for marketers in choosing the appropriate advertising language to enhance consumer engagement and memory.
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The household is a crucial unit of consumption that involves joint decision-making. While many studies have focused on individual-level advertising impacts, the interactions among household members have been largely overlooked. This study investigates a dyad-exposure advertising method that targets both spouses as decision-makers in purchasing household products. The findings reveal that dyad exposure significantly increases conversion rates by stimulating intra-couple interaction.
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This study explores how mega- and micro-influencers manage authenticity in their sponsored content based on social network theory, which argues that individuals, groups and organizations are embedded within webs of social relations and interactions that impact their beliefs and actions. It compares their strategies and engagement rates, providing insights into the effectiveness of different influencer types.
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This study explores the potential of large language models (LLMs) to revolutionize marketing research. By partnering with a Fortune 500 food company, the authors replicated qualitative and quantitative studies using GPT-4. The findings indicate that LLMs can effectively generate synthetic respondents, moderate in-depth interviews and perform data analysis tasks, matching or even surpassing human performance in certain aspects. The study highlights the benefits of a Human-LLM hybrid approach, where LLMs assist in various stages of the research process, from study design to data analysis. This approach not only enhances efficiency but also uncovers new insights that might be overlooked by human researchers alone.
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This study investigates how the adoption of GPT-4, the first paid GenAI service, influenced early adopters' payments to other digital services. The research provides insights into the payment behavior of early GPT-4 adopters and how it might help calibrate investor expectations of the GenAI market. The study uses a difference-in-differences approach to analyze payment data and offers a comprehensive view of the impact of GPT-4 on consumer payments for other digital services.
The findings suggest that early GPT-4 adopters were significantly more likely to pay for other AI tools like Github Copilot, which offers coding assistance. The study also highlights the potential of GenAI services to replace traditional web-based search tools and automate various service industries.
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