As generative AI tools increasingly shape how consumers search, shop, compare and evaluate products, understanding how they make recommendations has become critical for marketers. This eighth report in our ongoing Psych of Gen AI series examines how large language models (LLMs), like ChatGPT and Claude, determine what qualifies as the “best” product—and reveals that their recommendations are far from neutral. Instead, they tend to rely on narrow, repetitive sets of familiar brands and structured response patterns that may reinforce existing market leaders. The findings highlight important implications for brand visibility, competitive dynamics and how marketers should position their products in AI-driven environments.
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Advertisers frequently feature both products and human models in print and digital campaigns—but how large each element appears relative to the other can significantly influence consumer responses. This Journal of Advertising Research study shows that the effectiveness of this visual design choice depends on product type. Across a field experiment and multiple online studies, the researchers find that hedonic products perform better when the model is larger than the product, while utilitarian products benefit when the product itself is larger than the model. The reason: these pairings create greater conceptual fluency for consumers, making the advertisement feel more cognitively “right” and leading to stronger product evaluations and purchase intentions.
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New research reveals that virtual influencers, despite their growing popularity and flexibility, are less effective than human influencers in driving engagement and brand outcomes. The reason lies in consumer psychology: people perceive virtual influencers as less deserving of success, which reduces feelings of envy—an emotion that typically drives social media engagement. However, this disadvantage can be mitigated when virtual influencers are paired with futuristic, technology-focused brands, where their artificial nature feels more congruent.
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