Marvin

Automate qualitative research with AI-driven tools, streamlining data analysis and identifying trends, to uncover deeper customer insights and inform data-driven decisions.
User Research Qualitative Research AI-Powered Analytics

Marvin is a user research platform that helps you conduct qualitative research and analyze data more efficiently. It uses AI technology to automate the more mundane aspects of research so you can spend more time finding deeper insights into your customers' needs.

Marvin is a centralized repository where you can store and organize all your user interviews, transcripts, notes, and other research artifacts. This means your entire team can access user insights and quickly find relevant information. The platform's AI technology streamlines the process of aggregating user feedback and identifying trends that may have otherwise gone unnoticed.

Some of the key features of Marvin include:

  • Accurate Time-Stamped Notes: Identify important moments without having to rewatch hours of video.
  • Automated Transcription: Get accurate transcripts of user interviews in over 40 languages.
  • Video Clips and Highlight Reels: Create interactive reports to share customer feedback.
  • Automated Tagging and Analysis: Summarize research and identify trends with AI.
  • HIPAA, GDPR, and SOC2 Compliance: Protect user data.
  • Privacy Filters: Automatically remove personal data from user interviews.
  • Integrations: Connect with tools like Zoom, Notion, Miro, Google Sheets, and Qualtrics.

Marvin offers a variety of pricing plans to suit different team sizes and needs:

  • Free: $0 per year, limited features.
  • Essentials: $50 per user/month (annual billing), great for startups.
  • Standard: $100 per user/month (annual billing), great for companies with multiple teams.
  • Enterprise: Custom pricing for large companies.

Marvin is great for product designers, researchers and students doing UX research, as well as management consulting and academic research. The AI technology can help you cut through the noise of large amounts of research data to find actionable insights, and it can be used to easily share findings with stakeholders.

Published on June 9, 2024

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