Conversation Analysis Dashboard

Comprehensive insights into chatbot interactions, escalations, engagement patterns, and sentiment analysis

Escalation Analysis

Explore patterns in conversation escalations, trigger phrases, and resolution strategies

  • Escalation types and distribution
  • Trigger keywords analysis
  • Time-based patterns
  • Pre-escalation behavior
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Engagement Analysis

Understand conversation dynamics, response patterns, and user engagement metrics

  • Conversation flow analysis
  • Response time metrics
  • Engagement by time periods
  • Thread-level insights
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Sentiment Analysis

Analyze emotional patterns, sentiment transitions, and their impact on enrollment

  • Sentiment flow transitions
  • Enrollment vs sentiment correlation
  • Contact timing effectiveness
  • Emoji usage patterns
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Overall Insights

High Engagement, Mixed Outcomes: The system successfully engages all 18,916 students with relatively positive sentiment (0.181) and reasonable response times (965.7 minutes), yet achieves only a 38.2% enrollment rate despite generating 27,339 escalations, suggesting that while the communication infrastructure effectively reaches and maintains contact with students, significant barriers remain in converting engagement into enrollment outcomes. This captures the central paradox revealed across all the data - strong operational metrics (universal reach, positive sentiment, active escalation monitoring) alongside modest conversion results.

Quick Overview

18,916
Total Students
7,225
Enrolled Students
38.2% enrollment rate
4,252
Total Escalations
965.7
Avg Response Time (mins)
0.181
Avg Sentiment
Positive scale