QUESTION: 93

A bank developed a scorecard to automate the loan approval process. In the scorecard rule, there is a classification implemented using three score bands: Not Approved, Refer to Manager, and Approved.
Which property allows you to use the result of this classification in a decision strategy?

pyPropensity
pxSegment
PropertyHasValue
pyOutcome

Answer(s): B

Explanation:

Scorecard Classification - Classifications in a scorecard can segment customers based on score ranges into categories like Not Approved, Refer to Manager, and Approved. pxSegment Property - This property holds the classification result, which can be used in decision strategies to take appropriate actions based on the classification.
Steps to Use pxSegment:
Ensure the scorecard rule includes the classification bands. In the decision strategy, reference the pxSegment property to check the classification result. Use this property in filters, decision points, or to route customers to different actions based on their classification.

Reference:

Pega Customer Decision Hub User Guide 8.6, Section "Using Scorecard Classifications in Strategies" details how to leverage the pxSegment property.

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QUESTION: 94

U+ bank uses a decision table to return a label for a customer. Examine the above decision table and select which label is returned for a customer with a CLV score of 550 and a LOW propensity to leave

Answer(s): A,B

Explanation:

Decision Table Evaluation - Decision tables evaluate conditions in a specified order and return a result based on the first matching condition.
Conditions and Labels - Based on the decision table provided, the CLV score of 550 and LOW propensity to leave match the condition for label B.
Process:
Evaluate the CLV score condition.
Evaluate the propensity to leave condition.
The matching row in the decision table specifies the label to return.

Reference:

Pega Customer Decision Hub User Guide 8.7, Section "Creating and Using Decision Tables" explains how decision tables are evaluated and used in strategies.

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QUESTION: 95

U+ Bank promotes credit card offers on its website and uses Pega Customer Decision Hub to personalize the offer for every customer. Now, the bank wants to lower the number of customers that leave the bank by showing a proactive retention offer to high churn risk customers instead. As an NBA analyst, you are tasked with creating a new applicability setting to comply with the new business rule.
Which business issue or issues do you modify?

The Sales issue
The Retention issue
No modification is required
The Sales issue and the Retention issue

Answer(s): B

Explanation:

Business Issues and Groups in Pega CDH - Business issues (like Sales, Service, Retention) categorize customer engagement strategies. Each issue can have multiple groups representing specific goals (e.g., credit cards, loans under Sales).
Retention Issue - Since the objective is to retain customers who are at high risk of leaving, modifying the Retention issue aligns the strategy with the goal of reducing churn.
Steps to Modify Retention Issue:
Navigate to the Next-Best-Action Designer.
Select the Retention issue.
Update or create new applicability settings to identify high churn risk customers. Configure actions (proactive retention offers) to be presented to these customers.

Reference:

Pega Customer Decision Hub User Guide 8.7, Section "Managing issues and groups," explains how to configure and manage business issues including Retention.

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QUESTION: 96

MyCo, a telecom company, has a new requirement to track customer responses over a period of 20 days.
What do you need to create to start tracking customer responses for the given period of time?

Interaction History component
Data Join component
Interaction History summary rule
Group By component

Answer(s): C

Explanation:

Interaction History Summary - This rule aggregates data like customer responses, action outcomes, and interactions over a set time period.

Steps to Create the Rule:
In Dev Studio, go to Configure -> Decisioning -> Decisions -> Data Sources -> Interaction History Summaries.
Create a new summary rule.
Set the time period to 20 days.
Define the interaction data to be tracked (e.g., accepts, rejects). Benefits - Enables precise tracking of customer engagement and responses, facilitating better decision strategies based on historical data.

Reference:

Pega Customer Decision Hub User Guide 8.5, Section "Adding more tracking time periods for contact policies," outlines how to create and configure Interaction History summary rules.

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QUESTION: 96

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