Free Practice Questions for Pegasystems PEGAPCDC87V1 Exam

Paul cannot see the Reward card offer due to the contact policies defined by U+ Bank:

Contact Policies Defined:

Policy 1: Suppress a group of credit card offers for 30 days if any credit card offer is rejected three times in any channel in the past 15 days.

Policy 2: Suppress the Reward card offer for 7 days if it is rejected twice in any channel in the last 7 days.

Paul’s Rejection History:

Paul has rejected other credit card offers twice on the web channel and once in the contact center within the last 15 days.

Reason for Suppression:

Due to Policy 1, since Paul has rejected any credit card offer (not specifically the Reward card) three times in any channel in the past 15 days, all credit card offers, including the Reward card offer, are suppressed for 30 days.

Understanding the Suppression Logic:

Step 1: The decision strategy evaluates the rejection history of offers.

Step 2: It applies the contact policies to determine which offers should be suppressed.

Step 3: In this case, the policy conditions are met due to multiple rejections of credit card offers, leading to the suppression of the Reward card offer.

References:

Pega-Customer-Decision-Hub-User-Guide-85.pdf: "Setting constraints, contact policy limits, and controls" section.

Pega documentation on "Managing contact policies".

If the volume constraint shown in the image (Maximum 75 Daily with Channel: Action: StandardCard, Maximum 50 Daily with Channel: Email, Maximum 50 Daily with Channel: SMS) is applied, the outbound run will deliver 75 actions in total. This includes actions across different channels, adhering to the specified limits.

Next-Best-Action in Pega Customer Decision Hub is primarily applied to customer engagement and decisioning scenarios:

Purpose of Next-Best-Action:

Step 1: Next-Best-Action aims to provide personalized recommendations and decisions that are most relevant to the customer at any given moment.

Step 2: It uses predictive and adaptive analytics to determine the most appropriate actions based on customer data and business rules.

Application in Loan Decisions:

Step 1: In the context of determining if a borrower gets a loan, Next-Best-Action evaluates various factors such as creditworthiness, loan history, and current financial status.

Step 2: It leverages AI models to assess the risk and likelihood of repayment, ensuring that loan offers are extended to eligible and suitable customers.

Implementation Steps:

Step 1: Set up decision strategies in Pega Customer Decision Hub to include criteria for loan eligibility, such as credit scores and income levels.

Step 2: Configure predictive models to analyze customer data and predict loan approval probabilities.

Step 3: Use engagement policies to ensure that the loan offers are aligned with business objectives and regulatory requirements.

Benefits:

Applying Next-Best-Action to loan decisions helps in making data-driven and objective decisions, reducing the risk of defaults and improving customer satisfaction by offering relevant financial products.

References:

Pega-Customer-Decision-Hub-User-Guide-85.pdf: "Understanding Next-Best-Action Designer basics" section.

Pega documentation on "Decision management and AI in financial services".

Value Finder is a tool in Pega Customer Decision Hub that helps identify and visualize the distribution of under-served customers across different groups. It also highlights opportunities for improvement by pinpointing areas where the engagement policies or strategies can be optimized to better serve these customers. This helps in fine-tuning the next-best-action strategies to enhance overall customer engagement and satisfaction.

Designing Reusable Action Flows:

When creating an action flow intended for reuse, it's important to configure it with specific treatments.

The Specify Treatment option allows the flow to dynamically apply the appropriate treatment based on the action context.

This approach ensures consistency and flexibility, making it easier to manage and update the flows.

Updating Scorecard in Decision Strategy: When a scorecard rule is updated to include a new property such as customer income, it is essential to reflect this change in the decision strategy. The scorecard properties must be correctly mapped to ensure the new calculations are utilized.

When implementing the Next-Best-Action paradigm to offer the new data plan, the mobile company should focus on "Customer relevancy and business profitability." This means that the company needs to ensure that the offers are relevant to individual customers based on their needs, preferences, and behavior, while also aligning these offers with the company's business objectives to ensure profitability. This customer-centric approach leverages Pega's predictive and adaptive analytics to personalize offers and maximize both customer satisfaction and business outcomes.

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 " where "" 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 , 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.

References:

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

Pega documentation on "Defining an action for outbound".

Action Flow Template: To implement the requirement of using the same action flow template for all credit card actions, configure the email treatment. This allows you to define the desired flow pattern and reuse it across different credit card actions.

Configuration: Create an email treatment template that includes the specific flow pattern, and then apply this template to all the relevant credit card actions.