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
You might also like
You can architect enterprise-scale knowledge bases by analyzing support ticket patterns and customer segment needs to identify high-value content opportunities. Claude helps you map customer journey stages to content positioning, create tiered content models based on business impact, and establish governance workflows that optimize for first-contact resolution and support cost reduction. You'll translate fragmented support data into coherent content strategies with measurable KPIs.
You can leverage Claude to perform comprehensive taxonomy audits that identify term inconsistencies, semantic gaps, and governance breakdowns across your knowledge management infrastructure. This skill enables you to develop and enforce governance policies, map compliance requirements to classification schemes, and plan taxonomy migrations with confidence that stakeholder alignment and regulatory needs are addressed.
You can consolidate fragmented customer research—surveys, interviews, support tickets, behavioral data—into stage-based journey maps that identify moments of truth and experience gaps. The skill helps you weight insights by impact, pinpoint where customers struggle most, and build executive-ready maps that justify CX investment decisions with specific evidence rather than assumptions.
You can analyze support ticket patterns to uncover content gaps, map customer journeys to identify missing information, audit existing articles for consistency and completeness, and establish content governance frameworks. Claude helps you prioritize content creation based on support volume impact, restructure your knowledge base architecture for better findability, and measure whether your content strategy actually reduces support workload.
You can generate production-ready web interfaces, dashboards, forms, and navigation structures grounded in actual design system best practices. This skill provides access to 60+ documented UI component patterns sourced from industry standards, ensuring your designs follow modern conventions for restraint, typography hierarchy, color strategy, and spacing. Every interface Claude generates will feel polished and professional—not templated.
Convert raw Voice of Customer data—surveys, reviews, support tickets, social media—into structured journey maps that pinpoint exactly where customers experience friction, delight, or abandonment. You'll categorize touchpoints by journey stage, quantify sentiment at each interaction, and surface actionable insights about pain points and moments of truth that drive strategic improvements.
Process large volumes of unstructured customer feedback across multiple channels to identify recurring themes, sentiment patterns, and business impact. Claude synthesizes hundreds of feedback entries simultaneously, revealing subtle patterns humans might miss, and translates raw customer voice into executive-ready insights with clear strategic recommendations for product prioritization and experience enhancement.
Transform raw NPS and CSAT feedback data into structured root cause analyses that drive measurable experience improvements. You'll detect recurring themes across hundreds of comments, calculate the percentage of detractors citing specific issues, correlate feedback to customer segments, and receive prioritized intervention recommendations ranked by scope and fixability. This skill bridges the gap between data collection and strategic action.