CART® Classification for Predict Abandonment Rate

Use CART® Classification to use complex relationships with multiple predictors to predict whether a ticket is likely to be abandoned or resolved.

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

Example

Abandonment rate is the percentage of customers that disconnect or abandon a ticket or call before they can work with an agent.

In this worksheet, Ticket Status is the response. The response event is Abandoned. Hold Time and Schedule Adherence are continuous predictors, and Call Center Location and Department are categorical predictors.

C1-T	C2	C3	C4-T	C5-T
`Ticket Status`	`Hold Time`	`Schedule Adherence`	`Call Center Location`	`Department`
Resolved	58	85	East	Billing
Resolved	45	80	East	Customer Service
Resolved	50	80	West	Billing
Abandoned	102	65	West	Customer Service

How-to

Choose Solutions Modules > Functions > Customer Contact Center KPIs, then select Launch.
Under Service Level, select Abandonment rate.
Select Predict abandonment rate, then click OK.
Select CART® Classification, then click OK.
In Response, enter the binary variable that contains the abandonment 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 abandoned ticket.
In Continuous predictors, enter the continuous variables that may explain or predict whether a ticket is abandoned. The predictors are also called X variables.
In Categorical predictors, enter the categorical variables that may explain or predict whether a ticket is abandoned. The predictors are also called X variables.
Click OK.

Tip

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