CART® Classification for Predict Service Level

Use CART® Classification to use complex relationships with multiple predictors to predict whether a service level agreement is likely to be met.

This example applies to the Customer Contact Center Module. For more information, go to www.minitab.com/customer-contact-center-module.

Example

Service level is the ability to meet the standards in a Service Level Agreement (SLA).

In this worksheet, Service Level is the response. The response event is Not met. Schedule Adherence is a continuous predictor, and Call Center Location and Department are categorical predictors.

C1-T	C2	C3-T	C4-T
`Service Level`	`Schedule Adherence`	`Call Center Location`	`Department`
Not met	70	East	Billing
Met	80	East	Customer service
Met	82	West	Billing
Met	76	West	Customer service

How-to

Choose Solutions Modules > Functions > Customer Contact Center KPIs, then select Launch.
Under Service Level, select Service level.
Select Predict service level, then click OK.
Select CART® Classification, then click OK.
In Response, enter the binary variable that contains the service level agreement data. Binary variables are categorical variables that have two possible levels, such as pass/fail or true/false. The response is also called the Y variable.
In Response event, select the value that represents an unmet service level agreement.
In Continuous predictors, enter the continuous variables that may explain or predict whether a service level agreement is not met. The predictors are also called X variables.
In Categorical predictors, enter the categorical variables that may explain or predict whether a service level agreement is not met. The predictors are also called X variables.
Click OK.

Tip

For more information about this analysis, click Help in the main dialog box.