Use AI to quickly turn raw user interview notes into clear, prioritized insights for product decisions.
When you collect user feedback from interviews or surveys, you often end up with long, messy notes that take hours to review and summarize. Instead of spending time manually sorting through them, you can feed these raw notes into AI to get a neat summary of key themes, pain points, and feature requests—all prioritized by importance. This shortcut saves you hours each week and helps you focus on what really matters to your users. To do this effectively, gather all your notes in one place, then ask the AI to highlight common patterns and prioritize them based on user impact or frequency. You can even ask the AI to suggest how these insights should influence your upcoming product decisions or backlog prioritization.
Try this prompt today
“Act as a product manager reviewing user interview notes. Summarize the main user pain points, feature requests, and positive feedback from the following raw notes. Then, prioritize these insights by how often they were mentioned and their potential impact on user satisfaction. Provide a clear list I can use to update my product backlog: [Paste raw user interview notes here]”
June 15, 2026
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