Start with resolution quality
Deflection can look good even when customers leave frustrated. Measure whether the answer was correct, complete and appropriate for the case.
- Accuracy
- Resolution completeness
- Repeat contact
- Policy adherence
Agent performance
How to measure an AI customer support agent beyond deflection rate.
A support agent is only useful if it resolves the right work, escalates the right cases and protects the customer experience. Volume alone cannot tell you that.
Measure the boundary between AI and human support
A strong agent knows when to stop. Escalation quality should be measured alongside automated resolution because both are part of the same customer journey.
- Correct escalations
- Missed escalations
- Context passed to the human
- Time to human resolution
Add customer-experience signals
Quality scores explain how the agent behaved. Sentiment and recurring themes explain how the customer experience is changing.
- Sentiment by topic
- Pain-point frequency
- Complaint themes
- Feature requests
Use the measures to improve the system
Performance data should change knowledge, prompts, routing, human training and scope. A static scorecard is less valuable than a feedback loop.
- Improve knowledge gaps
- Adjust automation scope
- Update escalation rules
- Coach human owners