Analyzes customer emotional tone at conversation close to support QM reviews, supervisor follow-up, and agent coaching.
Analyzes the customer's emotional tone and overall experience based on the conversation transcript. It helps teams understand whether the customer interaction ended positively, neutrally, or negatively. The feature is especially useful for supervisors, QA teams, and reporting users who need to identify dissatisfied customers, recurring pain points, and conversations that may require follow-up or coaching.
The sentiment result is generated from the full conversation context rather than a single message. This allows the AI to consider the customer's initial problem, the agent's response, escalation events, resolution status, and the customer's final tone. In Conversation Studio, this feature can also be configured to analyze sentiment during an active conversation at any required point, based on the business use case.
How to enable it
Conversation Sentiment Configuration Guide
How It Works
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The conversation is completed or reaches a configured analysis point in the conversation studio.
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The system collects the full chat transcript or voice transcript.
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AI analyzes the customer tone, language, and outcome.
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The conversation is classified as positive, neutral, or negative.
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The result is saved with the conversation record and can be used in QA, reporting, and supervisor review.
Value
Conversation Sentiment helps organizations quickly locate interactions that need attention. Negative sentiment can be used to prioritize QM reviews, supervisor follow-up, and agent coaching. Positive sentiment can help identify successful handling patterns and high-quality agent behavior.