Listen Labs

Listen Labs is an AI-led user research platform that automates the end-to-end process of conducting qualitative user interviews at scale. Designed for product managers, UX researchers, marketers, and customer insights teams, the platform replaces the traditional, labor-intensive interview workflow with an AI moderator capable of conducting hundreds or thousands of in-depth conversations simultaneously. Instead of researchers manually scheduling, moderating, transcribing, and analyzing each interview, Listen Labs handles recruitment, runs the live conversations with participants via voice or video, and synthesizes findings into structured insights ready for stakeholder review.

The platform's core innovation is its conversational AI moderator, which adapts dynamically based on participant responses—asking probing follow-up questions, clarifying ambiguous answers, and pursuing unexpected threads in much the same way a skilled human researcher would. This adaptive capability allows teams to gather rich qualitative data without sacrificing the depth that traditionally separates interviews from surveys. Traditional qualitative studies typically involve 5 to 15 participants due to the cost of human moderation, which according to industry benchmarks from UXR community surveys averages $150 to $300 per moderated session when factoring in recruiter fees, moderator time, and transcription. Because AI moderation removes most of those per-session labor costs, organizations can scale to hundreds of participants per study, producing qualitative datasets large enough for thematic saturation analysis.

Listen Labs integrates participant recruitment, providing access to panels across demographics and geographies, and supports research in multiple languages. The platform claims support for over 30 languages as of early 2026, covering major European, Asian, and Latin American markets. After interviews are completed, the platform automatically transcribes conversations, tags themes, identifies recurring patterns, and generates summaries, quote highlights, and reports. Researchers can query the entire interview corpus using natural language to surface specific feedback, segment responses by participant attributes, or trace contradictions across cohorts.

The tool is positioned for use cases including concept testing, product feedback, pricing research, brand perception studies, customer journey mapping, churn analysis, and ongoing voice-of-customer programs. According to the vendor, teams using the platform have reported reducing study timelines from an average of 4 to 6 weeks down to 3 to 5 days for studies of comparable scope, though independent verification of these claims is not publicly available. By compressing fieldwork timelines and reducing per-interview costs—potentially by 70% to 90% compared to fully human-moderated equivalents based on typical industry cost structures—Listen Labs aims to make continuous, large-scale qualitative research practical for product and growth teams that previously relied primarily on surveys or analytics. The platform targets consumer brands, B2B SaaS companies, and enterprise research teams seeking to scale qualitative insight generation without proportionally scaling research headcount.