Paste raw interview notes or survey responses and get themes, insights, and product recommendations structured and ready for a decision meeting.
Free prompt pack · copy-paste ready · built by the BrainVaultAI team
User research only creates value when it gets synthesized into decisions. Most teams let interview notes rot in a doc because synthesis is slow, subjective, and hard to delegate. This prompt stack changes that. You get three prompts: one to clean and tag raw notes, one to extract themes and evidence, and one to translate findings into product recommendations. Run them in sequence on any batch of interviews, survey responses, or support tickets. Use it after any round of user interviews, after a product launch, or when you're deciding what to build next. The output is formatted to drop directly into a product brief or stakeholder update, no translation needed.
Step 1: Clean and Tag Raw Notes
You are a UX researcher cleaning interview notes for analysis. Here are raw notes from [NUMBER] user interviews / survey responses: [PASTE RAW NOTES] For each response or interview:
1. Remove filler, side-conversations, and off-topic content
2. Tag each meaningful statement with one or more labels from this list: - [PAIN], a frustration or problem - [WORKAROUND], something they do to compensate for missing functionality - [GOAL], what they're ultimately trying to achieve - [QUOTE], a verbatim line worth keeping for its clarity - [RISK], a reason they might churn or not buy - [DELIGHT], something they love
3. Output as a numbered list: Participant # | Tag | Cleaned statement No interpretation yet. Just clean, tagged facts.
Step 2: Extract Themes
You are a UX researcher synthesizing tagged research notes into themes. Here are my tagged notes from Step 1: [PASTE TAGGED NOTES] Identify 3-6 major themes. For each theme:
- Theme name (3-5 words)
- Frequency: how many participants mentioned it (e.g., 7/10)
- Summary: 2-3 sentences on what users actually said
- Supporting evidence: 2-3 direct quotes or paraphrased statements
- Severity: Critical / High / Medium / Low (based on frequency + emotional intensity) Order themes by severity, highest first. No filler. Evidence-first.
Step 3: Product Recommendations
You are a product strategist translating user research into decisions. Here are the themes from my user research synthesis: [PASTE THEMES FROM STEP 2] For each theme, generate:
1. The specific product or UX problem it points to
2. One concrete recommendation (feature change, copy change, flow change, or strategic decision)
3. Confidence level: High / Medium / Low and why
4. Suggested next step: ship / prototype / validate further / ignore for now Also produce:
- Top 3 "kill now" candidates, things we're doing that users don't value
- Top 3 "build next" candidates, high-severity gaps with clear demand Under 400 words. Decision-ready output only.
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