Sentiment Analysis
Sentiment analysis is an NLP technique that identifies and classifies the emotional tone behind text, determining whether a message expresses positive, negative, or neutral sentiment.
In Depth
In customer support, sentiment analysis is critical for prioritizing and routing conversations effectively. When a customer writes an angry message about a failed delivery, sentiment analysis detects the negative emotion and can trigger priority routing to experienced agents or adjust the AI agent's response tone to be more empathetic. Beyond simple positive/negative classification, advanced sentiment analysis can detect frustration, urgency, satisfaction, confusion, and sarcasm.
It can track sentiment changes within a conversation — if a customer starts neutral but becomes increasingly frustrated, the system can proactively escalate. GuruSup uses real-time sentiment analysis to adapt agent responses, trigger escalation protocols when frustration is detected, and generate CSAT predictions before surveys are even sent.
Related Terms
Natural Language Processing
Natural Language Processing (NLP) is a branch of AI that enables computers to understand, interpret, and generate human language in a meaningful way.
CSAT Score
CSAT (Customer Satisfaction Score) is a metric that measures how satisfied customers are with a specific interaction or overall service, typically collected through post-interaction surveys.
Escalation
Escalation is the process of transferring a customer support interaction from one level of support to a higher level — from AI to human, or from junior to senior agent — when the current handler cannot resolve the issue.
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