| Metric | Definition |
|---|---|
| Topic | The high-level theme of a conversation. Topics are the broadest unit of classification and group together interactions around the same subject. |
| Action / Task | The specific task a user is trying to accomplish within a topic. Actions sit one level below topics and provide more granular detail on user intent. |
| Query | A concise summary of a single interaction between a user and the AI. Queries are the most granular unit and represent what the user asked or expressed in a specific exchange. |
| Sentiment | The overall tone of a conversation, classified across five levels: Very Positive, Positive, Neutral, Negative, and Very Negative. |
| Emotion | The emotional state of the user, detected across 24 possible emotions for a more nuanced understanding of how users feel during interactions. |
| Conversation Length | The number of back-and-forth exchanges between a user and the AI agent in a single conversation. |
| Duration | The total time a user spends in a conversation with the AI agent. |
| Adoption Rate | The percentage of eligible users who have actively used the AI agent in a given period. |
| Error Rate | The percentage of interactions where the user did not find a satisfactory answer, either because the AI failed to respond correctly or because the user expressed frustration with the response. |
| Business Risk | Interactions where users express complaints or dissatisfaction directed at your company — not the AI itself. These are signals that may require attention from your team. |
| AI Fluency Index | A measure of how effectively users are able to interact with the AI agent — capturing the quality of their prompting and their ability to get value from the AI. |
| ROI | The estimated return on investment generated by the AI agent, calculated automatically based on standard assumptions. |
| Hours Saved | The estimated number of hours saved by automating interactions through the AI agent, calculated automatically based on standard assumptions. |