customer-feedback-taxonomy

gtmagents's avatarfrom gtmagents

Standardized tagging schema for personas, lifecycle stages, drivers, and sentiment.

⭐31stars🔀7forks📁View on GitHub🕐Updated Dec 23, 2025
[Voice of Customer Insights]

When & Why to Use This Skill

This Claude skill provides a comprehensive and standardized framework for tagging customer feedback across multiple dimensions including personas, lifecycle stages, and sentiment. It enables organizations to transform fragmented qualitative data from surveys, interviews, and support logs into structured, actionable insights for better product and business decision-making.

Use Cases

  • Voice of Customer (VoC) Data Normalization: Standardizing diverse feedback sources like NPS surveys, support tickets, and community discussions into a unified tagging schema for consistent analysis.
  • Customer Journey Mapping: Categorizing feedback based on lifecycle stages (onboarding, adoption, renewal) to pinpoint specific friction points and opportunities in the user experience.
  • Sentiment and Driver Analysis: Systematically tracking the relationship between product drivers and customer sentiment to prioritize the roadmap based on urgency and impact.
  • Cross-functional Data Governance: Establishing a shared taxonomy and governance checklist to ensure data consistency across product, marketing, and customer success teams.
namecustomer-feedback-taxonomy
descriptionStandardized tagging schema for personas, lifecycle stages, drivers,

Customer Feedback Taxonomy Skill

When to Use

  • Normalizing surveys, interviews, support logs, or community chatter before synthesis.
  • Auditing existing VoC datasets for drift or inconsistencies.
  • Onboarding new teams to shared tagging standards.

Framework

  1. Persona Layer – map ICP, role, and influence level.
  2. Lifecycle Layer – awareness, onboarding, adoption, expansion, renewal, advocacy.
  3. Driver Layer – product, service, pricing, experience, relationship, outcomes.
  4. Sentiment Layer – strength, urgency, confidence, sample size.
  5. Metadata Layer – ARR, region, industry, channel, last touch.

Templates

  • CSV/Sheet taxonomy with dropdowns and validation rules.
  • JSON schema for tagging automation or webhook ingestion.
  • Governance checklist for quarterly taxonomy refresh.

Tips

  • Keep taxonomy lean (<30 drivers) to encourage adoption.
  • Version every change so historical analyses remain comparable.
  • Pair with run-voc-listening-tour to auto-tag new signals.