Sentiment Analysis
Sentiment Analysis
AI
AI-powered analysis of text to determine the emotional tone (positive, negative, neutral) of customer messages.
What is Sentiment Analysis?
Sentiment analysis uses AI to detect emotional tone in text, helping prioritize and route customer communications appropriately.
Sentiment categories:
- Positive (happy, satisfied)
- Negative (angry, frustrated)
- Neutral (informational)
- Urgent (needs immediate attention)
Applications:
- Prioritize angry customers
- Route to specialized agents
- Track satisfaction trends
- Identify at-risk customers
- Measure brand perception
Beyond basic sentiment:
- Emotion detection (anger vs. disappointment)
- Intent classification
- Topic extraction
Example
For example, a message saying "This is the third time my order is late and I am done" would be tagged negative and urgent and moved to the front of the queue, while "Can I change my scent next month?" is neutral and can wait its turn.
Why Sentiment Analysis Matters
Sentiment analysis helps prioritize responses and identify customers who need special attention.
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