Agent effectiveness score predicts for interactions with efficient resolution and satisfaction. This score is calculated as:

[Handle time / (Predicted Satisfaction + Predicted Resolution)]

When extrapolated across a sample of interactions, this score can help identify differences in agent performance or which interaction types need focus for process improvement by looking at which interactions have a large span of Agent Effectiveness scores.

A lower score is better for this metric.

Example:

Compare two calls with the same handle time of 600 seconds (10 minutes).

Call 1

Handle time: 600 seconds

Predicted Satisfaction: 5 (high satisfaction)

Predicted Resolution: 1 (resolved)

Agent Effectiveness Score: [600 / (5 + 1)] = 100

Call 2

Handle time: 600 seconds

Predicted Satisfaction: 1 (low satisfaction)

Predicted Resolution: 0 (not resolved)

Agent Effectiveness Score: [600 / (1 + 0)] = 600

In this example the two calls each have the same handle time, however the predicted satisfaction and resolution mean Call 1 has a lower Agent Effectiveness score meaning it has been resolved with higher predicted satisfaction than Call 2.