Free Pegasystems PEGAPCDC87V1 Practice Exam with Questions & Answers | Set: 3

 Understanding the Requirement:

Myco wants to understand the impact on revenue if a new data plan offer is introduced.

This involves simulating the potential effects of adding a new offer to the existing strategy.

 Pega Scenario Planner:

Scenario Planner is used to simulate "what-if" scenarios to forecast results and understand the impact of changes to the Next-Best-Action Designer configuration.

It allows businesses to compare the effects of different strategies and adjust levers to align with business objectives.

 Running the Simulation:

Create and run an audience simulation with the new data plan offer included.

Use Scenario Planner to compare the projected reach, accepts, and value capture with and without the new offer.

 Steps to Use Scenario Planner:

Log in to the Pega Customer Decision Hub portal.

Navigate to Discovery -> Scenario Planner.

Create a new simulation, including the new data plan offer.

Run the simulation and compare the results to understand the impact on revenue.

 Verification from Pega Documentation:

The Pega Customer Decision Hub User Guide explains how to use Scenario Planner to simulate business changes and understand their impact​​​​.

To implement the change in the threshold value for the USD 2000 credit limit from “<175” to “<200”, as a Strategy Designer, you should change the cutoff value in the results tab of the scorecard decision component. This adjustment ensures that the decision logic used to automatically approve credit card limits reflects the new threshold, thereby updating the conditions under which customers qualify for the specified credit limit.

Referencing Customer Properties: In Pega decision strategies, customer properties are accessed by prefixing the property name with "Customer." This convention helps in clearly identifying the context of the properties being used.

 Volume Constraints Implementation: To implement a policy that limits the sending of more than 500 emails per day, you need to configure volume constraints. Volume constraints allow you to set limits on the number of actions delivered within a specified period.

 Configuration: Create a volume constraint rule and set the maximum volume to 500 emails per day.

 Understanding the Decision Table:

The decision table provided returns a label based on a customer's credit score and average balance.

The rules are evaluated in order, and the first matching rule determines the result.

 Evaluating the Customer Data:

The customer has a credit score of 115 and an average balance of 15000.

We will evaluate each row of the decision table to see where these values fit.

 Rule Evaluation:

First Rule: Credit Score >= 130 and Average Balance >= 30000

Customer's Credit Score: 115 (not >= 130)

This rule does not match.

Second Rule: Credit Score >= 110 and Average Balance >= 20000

Customer's Credit Score: 115 (>= 110) but Average Balance: 15000 (not >= 20000)

This rule does not match.

Third Rule: Credit Score >= 90 and Average Balance >= 10000

Customer's Credit Score: 115 (>= 90) and Average Balance: 15000 (>= 10000)

Both conditions match, so the result is "C".

Fourth Rule: Credit Score >= 70 and Average Balance >= 1000

This rule is not evaluated because the previous rule matched.

 Conclusion:

According to the decision table, the result for a customer with a credit score of 115 and an average balance of 15000 is "B".

Scorecard Component - This component in Pega CDH is designed to evaluate attributes and produce a score based on those attributes. It is commonly used for calculating credit scores, risk scores, etc.

Steps to Use Scorecard:

In the decision strategy, add a Scorecard component.

Configure the scorecard to include relevant customer attributes (e.g., payment history, credit utilization).

Set the rules and weights for each attribute to calculate the final credit score.

Use the score in further decision logic (e.g., filtering out customers with a score below 500).

 Best Practice for Emails: To ensure that emails load quickly and correctly across various email clients, it's best practice to provide links to images rather than embedding them directly or attaching them. This method ensures better compatibility and avoids large email sizes.

 Implementation: Including image links allows the email client to fetch images from a server, ensuring that the email content remains lightweight and is displayed properly.

A solid arrow from a "Set Property" component to a "Filter" component in a Pega decision strategy indicates that a property set by the "Set Property" component is being referenced or used by the "Filter" component. This relationship ensures that the data set in the "Set Property" component influences the filtering criteria in the "Filter" component, allowing for more dynamic and contextually relevant decisions.

 Placement Type in Treatment Design: To present the Rewards Card offer on the top right of the customer’s account page, you should use the "Tile" placement type. This type is specifically designed to position content in a compact, visually distinct block that can be placed in specific areas of a webpage, such as the top right corner.

 Implementation: In the treatment configuration within Pega, you can specify the placement type as "Tile" to ensure the offer is displayed correctly on the account page.

 Requirement:

The bank wants to avoid sending promotional emails related to credit card offers to a customer if they have already received one within a limited time period.

 Configuring Suppression Policy:

A suppression policy needs to be defined to prevent over-contacting customers.

Suppression policies automatically put an action on hold after specific criteria are met, such as a customer having already received a promotional email.

This ensures that customers are not bombarded with repeated offers, improving customer experience and adhering to communication limits.