
Survey Sentiment & Thematic Analysis
Extract sentiment patterns and themes from survey responses with structured NLP analysis
What You Can Do
You can systematically analyze 50+ survey responses to classify sentiment distributions, extract recurring themes and pain points, and rank insights by frequency and business impact. Claude identifies patterns across open-ended feedback, surfaces contradictions, and generates quantified summaries with direct quote evidence—turning qualitative data into prioritized action items for product and service improvements.
Features
Categorize responses as positive, negative, neutral, or mixed with confidence scores for statistical reporting
Automatically identify recurring topics, pain points, and opportunity areas across all responses
Rank themes by frequency, customer impact, and implementation feasibility to guide prioritization
Generate summaries with direct quotes and response counts so stakeholders can verify findings
Track sentiment and theme changes across multiple survey periods to measure improvement
Surface conflicting feedback patterns that reveal customer segment differences
Create stakeholder-ready reports with key metrics, top themes, and recommended actions
Example Output
Input: 127 responses to "What's your biggest frustration with our product?"
Output:
Sentiment Distribution:
- Positive: 34% (43 responses)
- Neutral: 28% (36 responses)
- Negative: 38% (48 responses)
Top Themes (by frequency & impact):
-
Onboarding Complexity — 31 mentions (24%)
- Actionability: High | Effort: Medium
- "Setup took 3 hours and we still needed support"
- "Documentation is outdated"
-
Mobile Experience Gaps — 22 mentions (17%)
- Actionability: High | Effort: High
- "Can't complete workflows on mobile"
-
Pricing Transparency — 18 mentions (14%)
- Actionability: Medium | Effort: Low
- Quick-win: Update pricing page with feature-to-tier mapping
What's Included
- SKILL.md: Complete instruction file with sentiment classification rubric, thematic coding framework, and actionability scoring matrix
- Response Analysis Template: Pre-structured prompt for batch sentiment + theme extraction with confidence thresholds
- Wave Comparison Checklist: Framework for tracking themes across multiple survey periods and measuring sentiment shifts
- Executive Summary Generator: Template for converting raw analysis into stakeholder-ready reports with metrics and recommendations
- Contradiction Detector: Guided workflow to surface and interpret conflicting feedback patterns by customer segment
Who It's For
- Voice of Customer (VoC) Analysts — Transform survey data into structured insights and trend reports
- Product Managers — Prioritize improvements based on quantified customer feedback and impact scoring
- Customer Experience Leaders — Identify recurring pain points and track sentiment improvements over time
- UX Researchers — Analyze open-ended feedback alongside quantitative ratings for comprehensive findings
- Customer Success Teams — Surface themes for proactive outreach and churn prevention strategies
Best For
- Analyzing 50+ open-ended survey responses for themes and sentiment patterns
- Prioritizing product improvements based on customer feedback frequency and impact
- Generating executive summaries with quoted evidence from survey data
- Comparing sentiment and themes across multiple survey waves or campaigns
- Identifying contradictions in feedback to uncover customer segment differences







