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Beginner10 min

Sentiment Analysis Basics

Use sentiment analysis to spot frustrated customers and improve responses.

Understanding Sentiment Analysis

Sentiment analysis detects customer emotions in real-time, helping you identify frustrated users before they escalate and spot satisfied customers who might become advocates.

Sentiment Categories

😊
Positive

"Thanks so much!", "This is exactly what I needed"

😐
Neutral

"Okay", "I see", factual questions

😤
Negative

"This is ridiculous", "I've been waiting forever"

How We Detect Sentiment

  1. Keyword Analysis: Detects words like "frustrated", "angry", "love", "thanks"
  2. Punctuation Patterns: Multiple exclamation marks, all caps, excessive question marks
  3. Message Length: Long, rambling messages often indicate frustration
  4. Response Time: Quick, curt replies may signal impatience
  5. Context: Repeated questions suggest the AI isn't helping

Using Sentiment Data

  • Auto-escalate when sentiment drops below threshold
  • Alert managers to intervene in real-time
  • Adjust AI tone to be more empathetic when negativity detected
  • Track trends to identify systemic issues

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