In this article, you’ll learn what Tags in statistics are, how they work, and how they can help you gain insights into your AI Agent's performance.
What are Tags in statistics?
Tags in statistics provide a clear overview of which tags have been used during conversations with your AI Agent within a selected time period. Tags are added during conversations to help categorize or label specific interactions—for example, to mark topics like “Refund request” or “Technical issue.”
By viewing the tag data in statistics, you can quickly identify the most common conversation types, spot trends, and evaluate how effectively your AI Agent is routing or handling different topics.
Why are Tags in statistics useful?
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Conversation analysis: See which tags are used most often and detect patterns in customer questions or issues.
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Performance tracking: Understand how frequently certain issues occur and whether they increase or decrease over time.
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AI Agent optimization: Use the tag data to refine your AI Agent’s instructions, fallback flows, or escalation paths.
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Team alignment: Share tag insights with your support team to adjust workflows or training materials based on what customers are asking.
Where to find Tags in statistics
You can access tag insights by going to Statistics in the Pulse section. The overview will show you:
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Which tags were used
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How many times each tag was triggered
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The selected time frame for this data
This makes it easy to monitor key trends and ensure your AI Agent is addressing the right topics.