Reach3 Insights announced AI Listening, a research solution that helps organizations understand how generative AI recommends brands, products, services, and content. Built on Reach3's conversational research methodologies and expertise in understanding consumer decision-making, the solution measures how recommendations vary by audience and buying context, helping organizations identify opportunities to improve their visibility across leading AI platforms.

Reach3's AI Listening solution can be applied across consumer goods, retail, financial services, health care, travel, entertainment and other industries where consumers are turning to AI for recommendations. For example, Warner Bros. Discovery is using the methodology to better understand how audiences discover entertainment content.

"The way people discover content is changing, and AI is becoming part of that process," said Sofia Gomez Garcia, executive director of Innovation, Special Projects & Global Community Management at Warner Bros. Discovery. "Understanding how our content is recommended, why it appears for different audiences and in different situations, and how those recommendations change depending on user prompt, gives us another way to think about discoverability."

AI Listening combines client-defined audience personas with demand spaces, or buying occasions, to recreate real-world decision scenarios. The full framework combines qualitative interviews, quantitative research, in-the-moment mobile ethnography, proprietary AI monitoring and vetting of recommendations with real consumers. Organizations can measure AI visibility, understand why recommendations occur and evaluate whether those recommendations resonate with their intended audiences.

"AI doesn't respond to everyone in the same way," said Patricia Chapin Bayley, Senior Vice President and product innovation lead for AI Listening at Reach3 Insights. "It responds differently depending on what it knows about the user and the occasion or context they are in. We built AI Listening to recreate those real-world situations at scale so organizations can understand how their brands appear in AI recommendations across different audiences, why they're being recommended and where they have opportunities to strengthen their AI visibility."