Sentiment Analysis
Also known as: call sentiment, tone analysis
Sentiment analysis is the automatic assessment of a caller's emotional tone (positive, neutral, or negative) from the words and delivery in a recorded call.
Sentiment analysis reads a transcribed conversation and estimates how the caller felt, scoring the call as positive, neutral, or negative. It gives teams a fast way to triage which conversations need attention without listening to every one.
As part of conversation intelligence, sentiment pairs well with lead scoring: a high-intent but negative-sentiment call is a clear save-the-customer signal.
Frequently asked questions
How is call sentiment useful?
Sentiment flags calls that went badly so a manager can follow up, highlights happy callers worth asking for reviews, and reveals patterns (such as a campaign that sends frustrated, poorly matched callers) that raw call counts would hide.
What are the four main steps of sentiment analysis?
In a call context: capture and transcribe the conversation, clean and break the text into analyzable units, classify the tone of each as positive, neutral, or negative, then roll those up into an overall score you can act on. Modern conversation intelligence runs all four automatically on every call.
Related terms
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