Research & Analysis
User Feedback Analyzer
Analyze qualitative user feedback at scale using thematic analysis and impact prioritization.
When to use this prompt
When analyzing user feedback from surveys, support tickets, reviews, or interview transcripts to inform product decisions.
The Prompt
You are a UX researcher skilled in thematic analysis. Analyze this user feedback to extract actionable insights.
FEEDBACK DATA:
{{feedback}}
CONTEXT:
- Feedback source: {{source}}
- Time period: {{period}}
- User segment: {{segment}}
- Research question: {{question}}
---
## ANALYSIS OUTPUT
### Executive Summary
[3-4 sentences: Key finding, biggest opportunity, recommended action]
---
### Quantitative Overview
| Metric | Value |
|--------|-------|
| Total feedback items | [N] |
| Positive sentiment | [%] |
| Negative sentiment | [%] |
| Neutral/Mixed | [%] |
---
### Thematic Analysis
**Theme 1: [Theme Name]**
- Frequency: [X mentions / Y% of feedback]
- Sentiment: [Positive/Negative/Mixed]
- Representative quotes:
- "[Verbatim quote 1]"
- "[Verbatim quote 2]"
- Underlying need: [What job-to-be-done does this reveal?]
- Implication: [What should we do about this?]
**Theme 2: [Theme Name]**
[Same structure...]
---
### Pain Points Prioritization
| Pain Point | Frequency | Severity | Solvability | Priority Score |
|------------|-----------|----------|-------------|----------------|
| [Pain 1] | [Low/Med/High] | [Low/Med/High] | [Low/Med/High] | [Calculate] |
Priority formula: Frequency × Severity × Solvability (where High=3, Med=2, Low=1)
---
### Feature Requests Analysis
| Request | Frequency | Fits Strategy? | Effort | Recommendation |
|---------|-----------|----------------|--------|----------------|
| [Request] | [Count] | [Y/N + why] | [S/M/L] | [Build/Defer/Decline] |
---
### Competitive Mentions
[Who did users compare us to? What did they say?]
| Competitor | Mentions | Context | Insight |
|------------|----------|---------|---------|
| [Name] | [Count] | [Why mentioned] | [What we learn] |
---
### Segments Analysis
[Are there differences by user segment?]
| Segment | Primary Concern | Unique Need | Opportunity |
|---------|-----------------|-------------|-------------|
| [Segment] | [Main issue] | [Specific need] | [How to serve better] |
---
### Recommendations
**Quick Wins (Low effort, High impact):**
1. [Action] — Based on: [Theme/Pain point]
**Strategic Investments (High effort, High impact):**
1. [Action] — Based on: [Theme/Pain point]
**Monitor (Emerging patterns):**
1. [Pattern] — Watch for: [Trigger to act]
---
### Methodology Notes
- Analysis approach: [Thematic analysis / Affinity mapping / etc.]
- Limitations: [What this analysis can't tell us]
- Recommended follow-up: [Additional research needed]Try it in:
Variables to customize
| Variable | Description | Example |
|---|---|---|
{{feedback}} | The feedback data to analyze | [Paste feedback from survey, support tickets, reviews, etc.] |
{{source}} | Where this feedback came from | NPS survey follow-up responses |
{{period}} | Time period covered | Q4 2024 |
{{segment}} | User segment if known | Enterprise customers on annual plans |
{{question}} | What you're trying to learn | Why did NPS drop 10 points this quarter? |
Expected output
Structured analysis with themes, prioritized pain points, feature request evaluation, and actionable recommendations.
Variations
Churn analysis
Analyze this churn feedback: {{feedback}}. Identify: 1) Primary churn reasons (ranked by frequency), 2) Preventable vs. non-preventable churn, 3) Early warning signals we missed, 4) Recommended retention interventions. Be specific about timing and triggers.