View features that influenced predictive routing decisions
- Routing > Predictor Model > View
- Routing > Predictor Model Feature > View permissions
You can view the top features that contributed to the routing decisions in a specific queue. For more information about feature importance and what they mean in the prediction process, see How AI model scores agents for predictive routing.
- Go to Performance > Workspace > Predictive Routing.
- Click the queue name and open the Predictive Model tab.
- From the drop-down list, choose the media type for which you need to view the details.
The page lists the top ten features classified into three categories: agent features, customer features, and other features.
The following is an example of a feature that influenced the routing decision.
The following table helps you interpret the feature template based on the above example:
Specifies if the feature is about the agent, caller, or the interaction. Possible values are:
Specifies how the feature data is measured. Possible values are:
|3||Specifies the activity that happened on the queue.|
Specifies the media type. Possible values are:
Specifies the period over which the metric was calculated.
Specifies the mathematical function used to derive the aggregate value.
Therefore the above example indicates that the data relates to an agent who handled voice calls for which there were consult transfers. The number of voice calls were calculated for a period of 30 days. If the percentage of this feature is 10% and is top ranked, it indicates that one of the major contributors of routing decision was the number of voice calls that had consult transfers