Key Metrics
- Net Sentiment Score (NSS)
The average sentiment across a conversation or set of conversations. - Sentiment Shift Score (SSS)
Measures how sentiment changes throughout the chat (e.g., going from frustrated → reassured). - Lowest Sentiment Point
Highlights the most negative user message with its sentiment score and detected emotion. - Actionable Recommendations
AI-powered suggestions for next steps to resolve issues and improve customer experience.
Sentiment Scoring Guide
Each user message is scored between -5 and +5, based on the emotion expressed.| Score | Canonical Emotion Label | Umbrella Meaning |
|---|---|---|
| +5 | Ecstatic | Peak positivity — delight, gratitude, or joy |
| +4 | Delighted | Very positive satisfaction and excitement |
| +3 | Pleased | Moderately happy, content, optimistic |
| +2 | Satisfied | Mild approval or relief; things are on track |
| +1 | Reassured | Slight positive calm after concern |
| 0 | Neutral | No strong emotion; observational |
| -1 | Uncertain | Mild doubt, hesitation, or confusion |
| -2 | Concerned | Noticeable worry or disappointment |
| -3 | Frustrated | Clear irritation or dissatisfaction |
| -4 | Angry | Strong negative feeling, indignation |
| -5 | Furious | Extreme negativity — outrage or despair |
Track both NSS (overall mood) and SSS (direction of mood) to understand not just how customers feel, but whether their experience improved or worsened during the conversation.
Use Cases
- Identify at-risk customers with consistently low sentiment.
- Review Lowest Sentiment Points to detect recurring issues.
- Use Actionable Recommendations to guide agent training and automation improvements.
- Track sentiment trends across teams, workflows, and time periods to measure impact of changes.