Pegasystems PEGAPCDC87V1 Certified Pega Decisioning Consultant (PCDC) 87V1 Exam Practice Test

Answer : C

To implement the required changes for the mortgage offers, you should create two separate change requests in the 1:1 Operations Manager portal. This ensures each change is tracked and managed individually.

Update Suitability Condition for Fifteen-Year Fixed-Rate Mortgage Offer:

Step 1: Log into the 1:1 Operations Manager Portal.

Step 2: Create a change request for updating the suitability condition of the Fifteen-Year Fixed-Rate Mortgage offer.

Step 3: Specify the details of the change, including the new suitability condition (Credit Score > 450).

Step 4: Submit the change request for approval and implementation.

Introduce a New Offer - Twenty-Year Fixed-Rate Mortgage:

Step 1: In the 1:1 Operations Manager Portal, create a new change request for introducing the Twenty-Year Fixed-Rate Mortgage offer.

Step 2: Define the new offer, including its eligibility, applicability, and suitability conditions (Credit Score > 600).

Step 3: Configure the necessary treatments and engagement policies for the new offer.

Step 4: Submit this change request for approval and implementation.

Best Practices:

Creating separate change requests ensures that each modification is properly documented and approved, reducing the risk of errors and making it easier to track changes.

This approach also allows for independent testing and validation of each change before it goes live.

Pega-Customer-Decision-Hub-User-Guide-85.pdf: 'Managing business-as-usual changes with Pega 1:1 Operations Manager' section.

Pega documentation on 'Creating change requests in 1:1 Operations Manager'.

By following these steps, U+ Bank can effectively manage the changes to their mortgage offers, ensuring that both the updated suitability condition and the new offer are correctly implemented.

Answer : B

Email treatments in Pega Customer Decision Hub allow for personalization, including customizing the email subject to address the customer by name or other personalized data.

Definition and Purpose:

Email treatments are used to define the content and presentation of email communications sent to customers as part of outbound campaigns.

Personalization enhances the relevance and engagement of these emails by including customer-specific information.

Capabilities of Email Treatments:

Personalization Tags: Pega supports the inclusion of dynamic tags in the email subject and body, allowing for personalized greetings, offers, and other content. For example, 'Dear <customer name>' where '<customer name>' is dynamically replaced with the actual name of the customer.

HTML Content: Design rich email content using HTML, which can include images, links, and other multimedia elements.

Steps to Personalize Email Subjects:

Step 1: Create or edit an email treatment in Pega.

Step 2: In the subject line field, use the syntax for personalization tags. For example, 'Dear <customer name>, check out our new offers!'.

Step 3: Map the personalization tags to the appropriate customer data fields to ensure the correct information is inserted when the email is sent.

Testing Personalization:

Use seed lists to test personalized emails. Seed lists are groups of test email addresses used to preview how the email will look when sent to actual customers.

Ensure that personalization attributes appear correctly in the received test emails.

Best Practices:

Always test personalized emails thoroughly before launching a campaign to ensure that the tags are working correctly and the content renders as expected.

Use personalization to enhance customer engagement by making emails feel more relevant and tailored to individual recipients.

Pega-Customer-Decision-Hub-User-Guide-85.pdf: 'Configuring email treatments' section.

Pega documentation on 'Defining an action for outbound'.

Answer : B

Enrichment decision components in Pega Customer Decision Hub provide the ability to set customer properties. These components are used to enhance the customer data within a decision strategy by adding or updating information about the customer. This allows for more personalized and contextually relevant decisions.

Definition and Purpose:

Enrichment components are used within decision strategies to add or update customer data, ensuring that the decisioning process has the most relevant and up-to-date information.

This can include setting properties like customer preferences, behaviors, or other attributes that might influence the decision outcome.

Types of Enrichment Components:

Set Property: This is the primary enrichment component used to set a value to a property within the strategy.

Data Import: Importing data from external sources to enrich the customer profile.

Data Transform: Applying transformations to data to format or manipulate it as needed within the strategy.

Usage in Decision Strategies:

When designing a decision strategy, enrichment components are typically used in the initial stages to ensure that all necessary customer data is available and accurate before proceeding to decision logic components.

For example, before evaluating eligibility or applicability, you might use an enrichment component to update the customer's credit score or recent transaction history.

Implementation Steps:

Step 1: Drag the enrichment component into the decision strategy canvas.

Step 2: Configure the component by selecting the property to set and defining the value or expression to be used.

Step 3: Connect the enrichment component to other components within the strategy to ensure the enriched data is utilized in subsequent decision-making steps.

Example:

Consider a scenario where a bank wants to offer personalized loan options based on the customer's recent financial activities. An enrichment component can be used to update the customer's profile with their latest transaction data, ensuring that the loan offer is tailored to their current financial status.

Pega-Customer-Decision-Hub-User-Guide-85.pdf: 'Understanding the Next-Best-Action strategy framework' section, which describes the use of enrichment components in decision strategies.

Pega documentation on 'Creating and understanding decision strategies'.

Answer : B

To define a suppression rule in Pega for the scenario where a group of mortgage offers should be suppressed for 15 days if a customer ignores three offers from the mortgage group, follow these steps:

Define the Suppression Rule:

Create a contact policy in Pega Customer Decision Hub to suppress the group of mortgage actions.

Specify the Condition:

Set the condition to suppress the group of actions if there are 3 rejects (ignored offers) for any channel. This means the suppression applies regardless of whether the offers were displayed on the web, mobile, email, etc.

Set the Suppression Duration:

Configure the suppression period to be 15 days. This ensures that the group of actions will not be shown to the customer for 15 days after they have ignored three offers.

Apply the Contact Policy:

Ensure the contact policy is associated with the relevant group of actions (mortgage offers) and that it is enforced by the strategy framework.

Test and Validate:

Test the suppression rule to verify it works as expected and that the offers are suppressed correctly after three rejects.

Pega Customer Decision Hub User Guide 8.7: Adding more tracking time periods for contact policies, Creating a contact policy, Contact policy library.

Answer : C

To use a customer property in an expression within a decision strategy in Pega, follow these steps:

Identify the Customer Property:

Determine the specific customer property you want to use in your strategy.

Prefix with 'Customer':

In Pega, customer properties are accessed by prefixing them with the keyword Customer. This ensures that the property is correctly referenced from the customer data.

Use the Property in Expression:

When defining an expression in a decision strategy, include the Customer prefix. For example, if the property is Age, use Customer.Age.

Verify Property Definition:

Ensure that the property is correctly defined in the data model and accessible within the strategy context.

Pega Customer Decision Hub User Guide 8.6: Understanding the Context Dictionary, Configuring the Context Dictionary.

Answer : D

Understanding Audience Simulation:

Audience simulations help understand how engagement policies and actions perform for a sample set of customers.

The simulation in question focuses solely on engagement policies without arbitration, meaning it evaluates which actions customers qualify for based on predefined criteria.

Interpreting the Simulation Results:

The numbers shown next to each action represent the count of customers who meet the engagement policy criteria for that action.

This count indicates the number of customers who qualify for each action based on eligibility, applicability, and suitability rules.

Detailed Explanation:

Rewards card (202): 202 customers meet the engagement criteria for the Rewards card.

Rewards Plus card (456): 456 customers meet the engagement criteria for the Rewards Plus card.

Premier Rewards card (25): 25 customers meet the engagement criteria for the Premier Rewards card.

Verification from Pega Documentation:

According to the Pega Customer Decision Hub User Guide, running an audience simulation with engagement policies helps identify how many customers qualify for each action based on the policies applied.

Answer : C

To determine which of the new credit card offers (Diamond, Platinum, and Gold) will be the best performing action, the Action Distribution Report is used. This report helps in running a distribution test to analyze how the different offers are being distributed among the customer base, providing insights into which offer might perform the best based on initial distribution and eligibility criteria.

Action Distribution Report for testing and analysis (Page 153-155)

Evaluating the performance of different actions using distribution tests (Page 157-159)