AI in customer support.
Evaluate resolution quality, repeat contacts, and the handoffs that still need a person.
- 1
Source
Support ticket received
- 2
Agent activity
Triage & resolution
- 3
Review
Reopened cases reviewed
- Available source
- CSV / API
- Measurement
- Agent performance and implementation maturity
Where agents work.
- Tier-1 ticket triage
- Reads inbound tickets, tags severity and topic, drafts the first reply, and escalates to a human when required.
- Deflection bot
- Resolves common questions in chat or email before a ticket enters the queue.
- Escalation router
- Identifies at-risk tickets early, routes them to the correct tier, and pauses when a human takes the conversation.
- KB / macro suggester
- Recommends the macro or KB article matching the ticket and learns from rep selections.
- QA reviewer
- Audits a sample of human and agent replies for tone, accuracy, and policy compliance.
What to measure.
- Resolution rate
- Agent-touched tickets closed without a human reply.
- Time to first response
- Median time from inbound to first agent message.
- CSAT lift
- CSAT delta on agent-touched tickets versus baseline.
- Escalation rate
- Share of tickets the agent handed to a human.
- Human override rate
- Frequency of rep replacement of agent drafts.
Measurement depends on your source records and mapping. These are signals to evaluate, not automatically collected metrics.
Source coverage and outcome attribution depend on the records you provide.
Review setup optionsEvaluate your workflow.
We’ll review your source data and agree what to measure.
Discuss your workflow