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Support Ticket Analysis & Trends

Executive Summary​

Based on analysis of support tickets from the SUP project (Jan-May 2025), we've identified critical patterns that require immediate attention.

Top Issues by Category​

1. AI Model Errors (35% of tickets)​

  • Red error messages with Claude models
  • Model selection issues
  • Response generation failures
  • High reasoning mode errors

Root Causes:

  • Model version compatibility issues
  • Token limit exceeded
  • API rate limiting
  • Configuration mismatches

2. File Embedding & Sync Issues (25% of tickets)​

  • SharePoint integration failures
  • Slow file embeddings
  • Files failing to embed
  • Sync status stuck
  • Missing files in Knowledge Base

Root Causes:

  • Large file processing bottlenecks
  • Integration authentication expiry
  • Embedding queue congestion
  • Vector database performance

3. UI/UX Problems (20% of tickets)​

  • Missing scroll bars
  • Overlap in History Panel
  • Configuration panel not opening
  • Vertical scroll issues
  • Missing labels on icons

Root Causes:

  • CSS conflicts
  • Responsive design gaps
  • Component state management
  • Browser compatibility

4. Integration Issues (15% of tickets)​

  • SharePoint drive visibility
  • Client secret expiration
  • Folder deletion problems
  • Permission issues

Root Causes:

  • OAuth token expiration
  • API permission changes
  • Tenant configuration
  • Network connectivity

5. Performance Issues (5% of tickets)​

  • Slow response times
  • Spinning circles with no output
  • Application freezes

Trend Analysis​

Monthly Ticket Volume​

January 2025:  ~85 tickets
February 2025: ~95 tickets
March 2025:    ~110 tickets
April 2025:    ~125 tickets
May 2025:      ~140 tickets (projected)

Growth Rate: 15-20% month-over-month increase

Severity Distribution​

  • Highest Priority: 15%
  • High Priority: 45%
  • Medium Priority: 30%
  • Low Priority: 10%

Customer Impact Analysis​

Most Affected Customers​

  1. Aerobodies - Repeated Claude model errors, web scraping issues
  2. St. George Tanaq - Persistent red errors with file attachments
  3. Bowhead - SharePoint integration problems
  4. Vivsoft - Slow file embedding performance
  5. A-P-T Research - Shared file embedding failures

Business Impact​

  • Customer Churn Risk: High for top 5 affected customers
  • Support Load: 140+ tickets/month requiring ~280 engineering hours
  • Revenue Impact: Potential loss of $500K+ ARR if issues persist

Immediate Action Items​

Priority 1 - Critical Fixes (Week 1-2)​

  1. AI Model Stability

    • Implement robust error handling for Claude models
    • Add automatic retry logic with exponential backoff
    • Create model health monitoring dashboard

  2. File Embedding Pipeline

    • Optimize embedding queue processing
    • Implement progress indicators
    • Add embedding status webhooks

Priority 2 - High Impact (Week 3-4)​

  1. UI/UX Fixes

    • Comprehensive CSS audit
    • Cross-browser testing suite
    • Responsive design improvements

  2. Integration Reliability

    • Automated token refresh
    • Integration health checks
    • Better error messaging

Priority 3 - Long-term (Month 2)​

  1. Performance Optimization

    • Implement request caching
    • Database query optimization
    • CDN configuration

  2. Monitoring Enhancement

    • Real-time error tracking
    • Customer-specific dashboards
    • Automated alerting

1. Incident Response​

  • Create runbooks for common issues
  • Implement automated ticket routing
  • Set up customer-specific alerts

2. Quality Assurance​

  • Expand E2E test coverage for critical paths
  • Add integration tests for AI models
  • Implement chaos engineering practices

3. Communication​

  • Weekly customer health reports
  • Proactive issue notifications
  • Public status page

4. Documentation​

  • Customer-facing troubleshooting guides
  • Video tutorials for common tasks
  • API documentation updates

Strategic Recommendations​

Short-term (Q2 2025)​

  1. Dedicated Support Engineering Team

    • 2-3 engineers focused on stability
    • Rotating on-call schedule
    • Direct customer communication

  2. Technical Debt Sprint

    • 2-week focused effort on top issues
    • No new features during this period
    • All hands on stability

Long-term (Q3-Q4 2025)​

  1. Architecture Review

    • Microservices evaluation
    • Database sharding strategy
    • Multi-region deployment

  2. AI Infrastructure

    • Self-hosted model options
    • Fallback model strategies
    • Response caching layer

Success Metrics​

Target Improvements (90 days)​

  • Ticket Volume: Reduce by 50%
  • Resolution Time: < 24 hours for High priority
  • Customer Satisfaction: > 4.5/5 rating
  • System Uptime: 99.9% availability

Monitoring KPIs​

  1. Mean Time to Resolution (MTTR)
  2. Ticket recurrence rate
  3. Customer health score
  4. Engineering hours per ticket
  5. Feature adoption post-fix

Risk Mitigation​

High-Risk Areas​

  1. Claude API Dependency

    • Multiple model provider fallbacks
    • Local model experimentation
    • Response caching strategy

  2. File Processing Scale

    • Queue system redesign
    • Horizontal scaling plan
    • Storage optimization

  3. Integration Complexity

    • Standardized integration framework
    • Better error boundaries
    • Customer sandbox environments

Next Steps: Review with engineering team, prioritize fixes, and establish weekly progress reviews with affected customers.