Fit Regression Model for Predict Average Age Of Ticket

Use Fit Regression Model to use multiple predictors to predict ticket age.

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

Example

The age of a ticket measures the length of time an unresolved ticket is open if not resolved on first contact.

In this worksheet, Ticket Age is the response. Schedule Adherence is a continuous predictor, and Call Center Location is a categorical predictor. The predictors may explain differences in ticket age.

C1	C2	C3-T
`Ticket Age`	`Schedule Adherence`	`Call Center Location`
17.5	60	East
16.3	80	East
14.5	76	West
15.0	80	West

How-to

Choose Solutions Modules > Functions > Customer Contact Center KPIs, then select Launch.
Under Ticket Resolution, select Average age of ticket.
Select Predict average age of ticket, then click OK.
Select Fit Regression Model, then click OK.
In Responses, enter the column that contains the ticket age 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 ticket age. The predictors are also called X variables.
In Categorical predictors, enter the categorical classifications or group assignments that may explain or predict changes in ticket age. The predictors are also called X variables.
Click OK.

Tip

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