CART® Regression for Predict Average Call Length

Use CART® Regression to use complex relationships with multiple predictors to predict call length.

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

Example

Average call length is the average length of time an agent spends on a call.

In this worksheet, Call Length is the response. Hold Time Supervisor and Training Hours are the continuous variables. Call Center Location and Department are the categorical variables. The predictors may explain differences in call length time.

C1	C2	C3	C4-T	C5-T
`Call Length`	`Hold Time Supervisor`	`Training Hours`	`Call Center Location`	`Department`
12.8	4.8	3	East	Billing
8.3	0	7	West	Billing
5.7	0	9	East	Customer Service
10.1	3.9	9	West	Customer Service

How-to

Choose Solutions Modules > Functions > Customer Contact Center KPIs, then select Launch.
Under Time Management, select Average call length.
Select Predict average call length, then click OK.
Select CART® Regression, then click OK.
In Responses, enter the column that contains the call length 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 call length time. The predictors are also called X variables.
In Categorical predictors, enter the categorical classifications or group assignments that may explain or predict changes in call length time. The predictors are also called X variables.
Click OK.

Tip

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