NPS/CSAT Insight Engine
Transform survey data into actionable CX insights with AI-powered sentiment analysis
What You Can Do
You can upload raw NPS/CSAT survey data and receive automated sentiment analysis, root cause identification, and segmented customer insights. The skill extracts satisfaction drivers, flags emerging issues, and produces executive-ready reports with supporting evidence—enabling you to move beyond topline scores to understand the 'why' behind customer sentiment and specific improvement levers.
Features
Automatically categorizes feedback as positive, neutral, or negative with confidence scoring and theme tagging
Extracts key satisfaction and dissatisfaction drivers from open-ended responses with frequency and impact ranking
Segments feedback by customer cohort, product line, or interaction type to surface segment-specific trends
Flags low-volume but high-concern patterns that indicate developing problems before broader impact
Produces data-backed narrative reports with charts-ready statistics and prioritized recommendations
Benchmarks current feedback themes against previous periods to track sentiment trajectory and intervention effectiveness
Delivers specific, evidence-linked improvement actions ranked by customer impact and implementation feasibility
Example Output
Input: 87 NPS responses with comments from post-purchase survey
Output Sample:
Overall Sentiment: 68 Promoters (78%), 14 Passives (16%), 5 Detractors (6%)
Top Satisfaction Drivers:
- Product quality/reliability — 34 mentions (positive sentiment 92%)
- Onboarding experience — 22 mentions (positive sentiment 89%)
- Customer support responsiveness — 18 mentions (positive sentiment 81%)
Top Dissatisfaction Drivers:
- Pricing/value perception — 12 mentions (47% of detractor feedback)
- Feature limitations vs. competitor positioning — 8 mentions (32% detractor feedback)
- Billing/account management confusion — 5 mentions (20% detractor feedback)
Segment Insight: Enterprise customers show 15% higher CSAT (77 vs 65) driven by dedicated support; SMB segment cites pricing concerns 3x more frequently.
Emerging Issue: 3 early-stage users mention onboarding friction with integration setup—currently low volume but 100% detractor segment.
What's Included
- NPS/CSAT Insight Engine SKILL.md instruction file:
- Survey data template (CSV format with required columns):
- Sentiment classification taxonomy and driver codebook:
- Executive report template with sections for sentiment summary, driver analysis, segment comparison, and prioritized recommendations:
- Emerging issue detection checklist:
Who It's For
- CX Managers — Analyzing post-purchase and post-interaction survey feedback at scale to inform product and experience strategy
- Customer Success Leaders — Identifying root causes of churn risk and satisfaction gaps across customer segments
- Product Managers — Understanding feature priorities and competitive positioning gaps from customer voice
- Executive Stakeholders — Consuming data-backed CX insights and trend narratives for strategic planning and board reporting
- Customer Research Teams — Accelerating qualitative feedback analysis to support research cycles and hypothesis testing
Best For
- Monthly/quarterly NPS/CSAT reporting cycles with high comment volume (50+ responses per cycle)
- Root cause analysis when NPS drops, plateaus, or shows unexpected shifts
- Segment-specific sentiment comparison (product vs. support vs. sales feedback; customer tier vs. cohort comparison)
- Competitive positioning analysis from customer feedback
- Emerging risk detection and early-warning system for developing customer issues
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