AI & Automation

What is Sentiment Analysis?

Quick Definition

Sentiment analysis uses AI to detect emotions and attitudes in speech or text — identifying whether a caller is happy, frustrated, urgent, or neutral — to prioritize and route calls appropriately.

Sentiment Analysis explained

Sentiment analysis (also called opinion mining or emotion AI) is a natural language processing technique that identifies and categorizes the emotional tone of spoken or written communication. In phone systems and AI receptionists, sentiment analysis processes the caller's speech in real time to detect emotional states: positive (satisfied, happy), negative (frustrated, angry, upset), neutral (informational inquiry), or urgent (emergency, time-sensitive). This capability enables intelligent call handling: frustrated callers can be immediately escalated to a manager, urgent calls can be prioritized for immediate transfer, and positive interactions can be noted for follow-up sales opportunities. Sentiment analysis also powers post-call analytics — businesses can review call sentiment trends to identify common frustrations, measure customer satisfaction over time, and train staff to handle negative interactions better. For service businesses, sentiment-aware AI receptionists can differentiate between a routine appointment request and an emergency plumbing call based on vocal urgency, routing each appropriately.

Where is sentiment analysis used?

Call centers, customer service, AI receptionists, social media monitoring.

Related terms

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