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Trace Margin

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17. What is a good AI call center resolution rate?

Trace Margin research deskSection 01Page 17 of 33Last updated

There is no useful universal target without a defined task mix, denominator and verification method. Set targets against your own baseline and separate conversational containment from successful resolution.

For this desk’s measurement framework:

Metric Recommended definition
Autonomous task completion Unique eligible tasks completed correctly without human rescue ÷ all eligible tasks assigned.
Assisted task completion Unique eligible tasks completed with human rescue ÷ all eligible tasks assigned.
Booking integrity Claimed confirmed bookings meeting every required rule ÷ all claimed confirmed bookings.
Handoff success Required handoffs reaching the intended staffed destination with necessary context ÷ all required handoffs.
Repeat contact Customers contacting again about the same unresolved task within a predefined window.
Total cost per successful task All attributable workflow costs ÷ unique verified successful tasks.

Report total routed demand alongside eligible demand so that exclusions remain visible. Freeze eligibility rules before the evaluation; do not remove difficult calls after seeing their outcomes.

Track appropriate refusals and safe escalations as separate useful outcomes. Do not silently reclassify them as completed bookings.

Verification matters: Vapi explicitly warns that a tool reporting success does not independently prove an external system changed. (docs.vapi.ai)

The right dashboard allows an operator to trace a claimed success back to the actual record and identify who corrected it, if anyone.