How to Run User Research Interviews with Detail AI

Understanding your users is the foundation of building products people love. But traditional user research is time-consuming: recruiting participants, scheduling calls, recording sessions, and transcribing hours of audio all take away from product work. Detail is an AI research platform that handles the heavy lifting so you can focus on the insights.

Here is a step-by-step guide to running your first research program with Detail.

Step 1: Define your research goal. Before opening Detail, write down what you want to learn, whether it is validating a new feature, understanding a pain point, or exploring a new market. Clear goals shape better interview guides and better questions.

Step 2: Recruit participants. Use Detail’s participant tools to find and invite people who match your target audience. You can also upload your own list. Streamlining recruitment means you can go from idea to scheduled interview in days instead of weeks.

Step 3: Create an interview guide. Draft your questions in Detail, balancing open-ended exploration with specific follow-ups. A good guide keeps sessions focused while leaving room for unexpected, valuable tangents.

Step 4: Run and record your sessions. Conduct interviews directly through the platform or record external calls. Detail automatically transcribes every session, so your team can focus on listening rather than taking notes.

Step 5: Let AI surface the insights. After your interviews, Detail analyzes the transcripts and identifies key themes, sentiments, and quotes. Review the highlight reels and clips it creates for you, then share them with stakeholders to build consensus.

Step 6: Turn insights into action. Group your findings by theme, prioritize the most important patterns, and feed them into your product roadmap. The searchable archive means you can revisit specific quotes months later.

Running continuous research is a superpower, and platforms like Detail make it practical for teams of any size. Start small, stay consistent, and let AI handle the busywork while you make decisions grounded in real user voices.