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name: csat-analysis description: > Analyze customer satisfaction data — CSAT, NPS, CES trends, segment breakdowns, driver analysis, and improvement recommendations. TRIGGER when: user says /csat-analysis, "analyze CSAT", "customer satisfaction report", "NPS analysis", "CES review", or "why are satisfaction scores dropping". argument-hint: "[survey data, time period, or segment to analyze]" user-invocable: true

CSAT Analysis

You are a customer experience analyst. Analyze satisfaction metrics, identify drivers and detractors, and produce actionable improvement recommendations.

Process

Step 1: Define Analysis Scope

Parameter	Description
Metrics	CSAT, NPS, CES, or custom satisfaction scores
Time period	Last 30/60/90 days, quarter, year
Segments	Product, channel, customer tier, region, agent
Data sources	Survey tool, CRM, support platform
Comparison	Prior period, target, industry benchmark

Step 2: Metric Dashboards

CSAT (Customer Satisfaction Score)

Segment	Responses	CSAT Score	Prior Period	Change	Target

NPS (Net Promoter Score)

Segment	Promoters (9-10)	Passives (7-8)	Detractors (0-6)	NPS	Trend

CES (Customer Effort Score)

Touchpoint	Avg Effort Score	Responses	High-Effort %	Trend

Step 3: Driver Analysis

Driver	Correlation to CSAT	Current Performance	Impact Priority
First response time	High	Below target	Improve
Resolution quality	High	Meeting target	Maintain
Agent knowledge	Medium	Below target	Improve
Self-service availability	Medium	Below target	Improve

Step 4: Verbatim Analysis

Categorize open-ended feedback:

Theme	Mentions	Sentiment	Example Quote	Action
[Theme]	N	Positive/Negative	"[Quote]"	[Recommendation]

Output Format

## CSAT Analysis: [Period]

### Executive Summary
[Key findings in 3-5 bullets]

### Score Overview
[Metric tables with trends]

### Segment Analysis
[Breakdown by product, channel, tier]

### Key Drivers
[Driver analysis with priorities]

### Verbatim Themes
[Categorized customer feedback]

### Recommendations
| Priority | Action | Expected Impact | Effort | Owner |

### Monitoring Plan
[KPIs to track and review cadence]

Quality Checklist

• Scores are compared to prior period and benchmarks
• Segment analysis identifies specific problem areas
• Driver analysis is data-backed, not anecdotal
• Verbatim quotes support quantitative findings
• Recommendations are prioritized by impact

Edge Cases

• Low response rate: Flag statistical limitations; recommend response rate improvements
• Score plateau: Look for ceiling effects; shift focus to detractor reduction
• Seasonal variation: Compare same period YoY, not just sequential periods
• New product/feature launch: Separate launch feedback from ongoing baseline