data quality
- Targets & Segments
- Article
What AI Recommends—and Why: Inside the Logic of “Best” Product Choices
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 seventh experiment in our ongoing Psychology of Gen AI series, is the first phase in a study that 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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- Research & Data Quality
- Article
AI Biases We Can’t See
While we have all heard about biases in AI LLMs regarding gender and race, we wondered what other biases might be lurking beneath the surface that we can’t readily see. On April 9, we dove into a study from Galileo Research & Strategy Consultancy about Americans’ Health & Wellness behaviors and attitudes. Attendees discovered what was learned and its implications for using AI in research studies.
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