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AI Agent Analytics

Last updated 2026-04-18

AI agent analytics help you understand how effectively your AI is handling customer conversations and where it needs improvement.

Key metrics

  • AI-handled vs escalated — how many conversations the AI resolved without human help
  • Escalation reasons — why the AI escalated to a human agent
  • Response quality — feedback ratings (good/bad) from your team
  • Tool usage — which integration actions the AI used most often
  • Containment rate — percentage of conversations fully handled by AI

Workflow execution stats

View how often the AI triggers workflows, which workflows it uses most, and the success rate of AI-triggered automations. This helps you understand how the AI leverages your workflow library.

Improving AI performance

Use analytics to identify gaps. If the AI frequently escalates on a specific topic, add more knowledge base content for that area. If feedback ratings are low for certain response types, refine the agent's instructions.

Review AI analytics weekly to keep your knowledge base current and your AI agent effective. Small, regular updates lead to better results than infrequent large changes.

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