Four hundred survey responses. Twenty Notion pages of Slack threads. Sticky notes that all say some version of “just make it simpler.”
That’s what landed on one designer’s desk labeled as a “design brief.” Happens every sprint somewhere.
Raw user feedback is chaos. People ramble. Half the comments contradict each other. Real insights hide between complaints about the font color and feature requests nobody actually needs. Your job is to extract the signal. Until now, that took hours of painful manual synthesis, usually followed by a meeting where someone rewrites everything anyway.
One prompt does it in minutes.
🎯 Why This Actually Matters
Most product teams treat user research like a tax. Something to endure before the real work starts. So they rush it, skim it, and build based on gut instinct plus the loudest voices in the room.
Then they ship a feature nobody actually wanted.
The cost is not just the wasted sprint. It’s the follow-up tickets, the redesign, and the quiet erosion of trust when users notice that their feedback went nowhere. That cycle repeats until someone decides to actually read the data.
A structured feedback-to-brief prompt flips that process. Instead of reading every comment and trying to synthesize it inside your head, you dump the raw mess into the AI and it hands back a document with goals, pain points, feature requests, and contradictions separated into clean sections.
That last part is the most underrated bit. The AI will flag where it doesn’t have enough information. Which means you stop building on assumptions you didn’t even know you were making.
🔧 How to Use It
Copy the prompt below. Paste your raw feedback where it says [PASTE RAW USER FEEDBACK HERE]. Run it in ChatGPT, Claude, or whatever you’re using. Get a structured design brief back.
No special setup. No custom GPT. Just paste and go.
ROLE: You are an expert UX researcher and product designer tasked with synthesizing raw user feedback into an actionable design brief.
TASK: Analyze the provided user feedback and extract the following information, structuring it into a clear markdown document. The goal is to transform unstructured, often rambling, comments into a focused brief that guides the design process.
INPUT FEEDBACK:
* [PASTE RAW USER FEEDBACK HERE]
OUTPUT FORMAT:
Design Brief
Project Goals
* List the primary objectives users are trying to achieve or the problems they want solved. Focus on the ‘why’ behind their requests.
User Needs / Pain Points
* Detail the specific difficulties, frustrations, or unmet needs expressed by users. What are they struggling with that the design should address?
Key Feature Requests / Desired Functionality
* Summarize any specific features or functionalities users are asking for, directly or implied.
Constraints / Considerations
* Note any limitations, preferences, or context mentioned by users that might impact the design (e.g., “I don’t want it to look like X”, “needs to work on mobile”, “I hate pop-ups”).
Unclear / Further Research Needed
* Identify any areas where user feedback is contradictory, vague, or insufficient, requiring further investigation.
💡 Tips and Tricks
Feed it specifics, not vibes. “It’s bad” gives the AI nothing to work with. “It’s bad because I can’t find the cancel button and the pricing page shows three different numbers” gives it everything. The quality of what you get out tracks directly with what you put in. If your feedback is mostly one-word reactions, add a line at the top of the prompt asking the AI to note where more context would help.
Treat the Unclear section as your research queue. When the AI flags something as needing more data, that’s your actual interview guide. It’s pointing at the exact gaps you need to fill before touching a single wireframe. Screenshot that section and bring it to your next user call.
Chunk feedback by user type. Run the prompt separately for power users versus new users. Two different briefs often reveal two completely different products hiding inside one vague feature request. A power user asking for “more control” and a new user asking for “less confusion” can look like the same problem until you look at them side by side.
Don’t sanitize the input. Drop in the messy, unedited comments. The prompt is built for chaos. Cleaning it up first just loses context the AI could have used.
🚀 Steal This Workflow
Next time a feedback dump lands on your desk, don’t open a new doc and start highlighting manually. Run this prompt first. See what comes back in under two minutes.
You’ll probably catch at least one insight you would have buried under the noise. And you’ll have something you can actually hand off to a developer or designer instead of a chaotic Notion page no one wants to read. Better yet, the brief becomes a shared reference point, so everyone stops arguing about what users “really meant.”
Turn the chaos into structure before you touch a single pixel. That’s the whole move.
THE prompt for User Feedback -> Design Brief
by u/promptoptimizr in ChatGPTPromptGenius