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Phase 6 Implementation Guide - Analytics Dashboard

Phase: Week 9
Status: 🚀 Starting Implementation
Goal: Track conversations, monitor performance, gain insights

🎯 Phase 6 Overview​

Objective: Build comprehensive analytics dashboard for chatbot monitoring and optimization

Deliverables:

  1. Conversation analytics engine
  2. Agent performance metrics
  3. Plotly Dash dashboard
  4. Real-time monitoring
  5. Report generation & export

Timeline: 1 week

📊 What We're Building​

The Analytics Stack​

┌─────────────────────────────────────┐
│     Plotly Dash Dashboard           │  ← User-facing analytics
│  (Real-time charts & metrics)       │
└─────────────┬───────────────────────┘
              │
┌─────────────┴───────────────────────┐
│     Analytics Engine                │  ← Processing & aggregation
│  (Metrics computation)              │
└─────────────┬───────────────────────┘
              │
┌─────────────┴───────────────────────┐
│     Data Collection                 │  ← Raw data
│  (Conversations, events, metrics)   │
└─────────────┬───────────────────────┘
              │
┌─────────────┴───────────────────────┐
│     Existing Systems                │
│  (Memory, Logs, Metrics) ✅         │
└─────────────────────────────────────┘

📋 Components to Build​

1. Conversation Analytics Engine​

File: packages/analytics/conversation_analytics.py

Metrics to Track:

  • Volume Metrics

    • Total conversations
    • Messages per conversation
    • Active users
    • Peak usage times

  • Engagement Metrics

    • Conversation completion rate
    • Average conversation length
    • User retention
    • Return rate

  • Quality Metrics

    • User satisfaction (from feedback)
    • Response accuracy
    • Escalation rate
    • Error rate

  • Performance Metrics

    • Average response time
    • Processing time by component
    • Token usage
    • Cost per conversation

2. Agent Performance Metrics​

File: packages/analytics/agent_metrics.py

Metrics to Track:

  • Success Metrics

    • Query success rate
    • Intent recognition accuracy
    • Entity extraction accuracy
    • Response relevance

  • Usage Metrics

    • Queries per agent
    • Tool usage frequency
    • Knowledge base hits
    • Popular queries

  • Efficiency Metrics

    • Average processing time
    • Steps per query
    • Cost per query
    • Token efficiency

  • Quality Metrics

    • User feedback scores
    • Escalation rate
    • Error rate
    • Retry rate

3. Plotly Dash Dashboard​

File: apps/analytics_dashboard/app.py

Pages:

Page 1: Overview​

  • Key metrics at a glance
  • Real-time conversation count
  • Active users
  • Response time trends

Page 2: Conversation Analytics​

  • Conversation volume over time
  • Message distribution
  • Popular queries
  • User engagement

Page 3: Agent Performance​

  • Agent comparison
  • Success rates
  • Processing times
  • Cost analysis

Page 4: User Insights​

  • User segmentation
  • Engagement patterns
  • Satisfaction scores
  • Feedback analysis

Page 5: System Health​

  • Error rates
  • Response times
  • Resource usage
  • Uptime monitoring

4. Real-Time Monitoring​

Features:

  • Live conversation tracking
  • Real-time metrics updates
  • Alert system for anomalies
  • Performance degradation detection

5. Report Generation​

Features:

  • Scheduled reports (daily, weekly, monthly)
  • Custom date ranges
  • Export to PDF/Excel
  • Email delivery
  • Customizable metrics

🛠️ Implementation Plan​

Day 1-2: Analytics Engine​

  • Build conversation analytics engine
  • Implement metric collectors
  • Create aggregation functions
  • Add time-series tracking

Day 3-4: Dashboard​

  • Build Dash application
  • Create charts and visualizations
  • Add filtering and drill-down
  • Implement real-time updates

Day 5: Reports & Integration​

  • Report generation
  • Export functionality
  • Integration with existing observability
  • Documentation

Let's build the analytics system! 🚀