CART® Regression for Predict Average Speed Of Answer

Use CART® Regression to use complex relationships with multiple predictors to predict speed of answer.

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

Example

Speed of answer is the time from when a customer enters the queue to the time when an agent responds to the ticket.

In this worksheet, Speed of Answer is the response. Schedule Adherence and Call Volume are the continuous variables. Call Center Location and Department are the categorical variables. The predictors may explain differences in speed of answer.

C1	C2	C3	C4-T	C5-T
`Speed of Answer`	`Schedule Adherence`	`Call Volume`	`Call Center Location`	`Department`
38	60	30	East	Billing
28	80	18	East	Customer Service
22	76	15	West	Billing
18	80	20	West	Customer Service

How-to

Choose Solutions Modules > Functions > Customer Contact Center KPIs, then select Launch.
Under Service Level, select Average speed of answer.
Select Predict average speed of answer, then click OK.
Select CART® Regression, then click OK.
In Responses, enter the column that contains the speed of answer data. The response is also called the Y variable.
In Continuous predictors, enter the columns of numeric data that may explain or predict changes in speed of answer. The predictors are also called X variables.
In Categorical predictors, enter the categorical classifications or group assignments that may explain or predict changes in speed of answer. The predictors are also called X variables.
Click OK.

Tip

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