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csat-root-cause

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Analyzes CSAT and NPS verbatims to surface root-cause themes and prioritize fixes by frequency and impact. Use when interpreting customer satisfaction data to inform product or process decisions.

skills/csat-root-cause/SKILL.md

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# CSAT Root Cause Analysis

Raw CSAT scores tell you that something is wrong. Verbatim comments tell you what and why. The goal of root-cause analysis is to turn hundreds of individual comments into a ranked list of fixable problems.

## Data preparation

Before analyzing, filter the dataset: remove blank verbatims, remove comments that mention only a specific agent by name (these are agent-performance signals, not product/process signals), and separate detractor verbatims (score 0-6 on NPS, 1-3 on CSAT) from promoter verbatims. Analyze detractors first - they drive churn.

## Coding scheme

Apply a two-level coding scheme. Level 1 is the broad category (product bug, slow response time, unclear communication, pricing confusion, onboarding friction, feature gap, policy frustration). Level 2 is the specific sub-theme within that category. Code each verbatim with exactly one Level 1 and one Level 2 code. If a verbatim contains multiple distinct complaints, split it into sub-comments before coding.

## Prioritization matrix
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