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Customer Feedback Aggregation

Aggregate and analyze customer feedback from multiple sources for product insights

SKILL.md

Full skill instructions

Customer Feedback Aggregation Skill

Overview

Specialized skill for aggregating and analyzing customer feedback from multiple sources. Enables product teams to synthesize voice-of-customer data into actionable insights for product decisions.

Capabilities

Data Collection

  • Parse support tickets for feature requests
  • Analyze NPS/​CSAT verbatim responses
  • Extract themes from sales call notes
  • Monitor app store reviews
  • Aggregate feedback from Intercom/​Zendesk
  • Process customer interview transcripts

Analysis

  • Calculate feature request frequency
  • Track sentiment trends over time
  • Identify emerging themes and patterns
  • Segment feedback by customer type
  • Correlate feedback with customer attributes
  • Detect urgency and impact signals

Synthesis

  • Generate feedback summary reports
  • Create feature request rankings
  • Build customer pain point matrices
  • Generate insight recommendations
  • Create feedback-to-feature mapping

Target Processes

This skill integrates with the following processes:

  • jtbd-analysis.js - Voice of customer for jobs analysis
  • feature-definition-prd.js - Customer-driven requirements
  • rice-prioritization.js - Reach and impact scoring
  • customer-advisory-board.js - CAB feedback synthesis

Input Schema

{
  "type": "object",
  "properties": {
    "sources": {
      "type": "array",
      "items": {
        "type": "object",
        "properties": {
          "type": { "type": "string", "enum": ["support-tickets", "nps-verbatim", "sales-calls", "app-reviews", "interviews", "surveys"] },
          "data": { "type": "array", "items": { "type": "object" } },
          "dateRange": { "type": "object" }
        }
      },
      "description": "Feedback data sources"
    },
    "analysisScope": {
      "type": "string",
      "enum": ["all", "feature-requests", "pain-points", "sentiment", "trends"],
      "description": "Focus area for analysis"
    },
    "segmentation": {
      "type": "array",
      "items": { "type": "string" },
      "description": "Dimensions to segment feedback by"
    },
    "timeRange": {
      "type": "object",
      "properties": {
        "start": { "type": "string", "format": "date" },
        "end": { "type": "string", "format": "date" }
      }
    }
  },
  "required": ["sources"]
}

Output Schema

{
  "type": "object",
  "properties": {
    "summary": {
      "type": "object",
      "properties": {
        "totalFeedbackItems": { "type": "number" },
        "sourceBreakdown": { "type": "object" },
        "dateRange": { "type": "object" },
        "overallSentiment": { "type": "string" }
      }
    },
    "themes": {
      "type": "array",
      "items": {
        "type": "object",
        "properties": {
          "theme": { "type": "string" },
          "frequency": { "type": "number" },
          "sentiment": { "type": "string" },
          "examples": { "type": "array", "items": { "type": "string" } },
          "segments": { "type": "object" }
        }
      }
    },
    "featureRequests": {
      "type": "array",
      "items": {
        "type": "object",
        "properties": {
          "feature": { "type": "string" },
          "requestCount": { "type": "number" },
          "customerSegments": { "type": "array", "items": { "type": "string" } },
          "urgencyScore": { "type": "number" },
          "impactEstimate": { "type": "string" },
          "representativeQuotes": { "type": "array", "items": { "type": "string" } }
        }
      }
    },
    "painPoints": {
      "type": "array",
      "items": {
        "type": "object",
        "properties": {
          "painPoint": { "type": "string" },
          "severity": { "type": "string" },
          "frequency": { "type": "number" },
          "customerImpact": { "type": "string" }
        }
      }
    },
    "trends": {
      "type": "object",
      "properties": {
        "emerging": { "type": "array", "items": { "type": "string" } },
        "declining": { "type": "array", "items": { "type": "string" } },
        "sentimentTrend": { "type": "string" }
      }
    },
    "recommendations": {
      "type": "array",
      "items": {
        "type": "object",
        "properties": {
          "recommendation": { "type": "string" },
          "priority": { "type": "string" },
          "evidence": { "type": "array", "items": { "type": "string" } }
        }
      }
    }
  }
}

Usage Example

const feedbackAnalysis = await executeSkill('feedback-aggregation', {
  sources: [
    {
      type: 'support-tickets',
      data: supportTickets,
      dateRange: { start: '2026-01-01', end: '2026-01-24' }
    },
    {
      type: 'nps-verbatim',
      data: npsResponses
    },
    {
      type: 'app-reviews',
      data: appStoreReviews
    }
  ],
  analysisScope: 'all',
  segmentation: ['plan_type', 'company_size', 'tenure']
});

Dependencies

  • NLP capabilities
  • Support platform APIs (Intercom, Zendesk)
  • App store APIs