Free Practice Questions for Pegasystems PEGAPCDC87V1 Exam

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.

 Understanding the Requirement:

Myco wants to find new opportunities to improve marketing during the ideation stage of a project for presenting post-paid offers.

This involves identifying gaps and underserved customer segments that can be targeted with new or improved offers.

 Pega Value Finder:

Pega Value Finder is designed to analyze the distribution of actions across different customer segments.

It helps identify customers who are not receiving any actions or are receiving only low-propensity actions, thus highlighting opportunities to improve the strategy.

 Running the Simulation:

In Pega Value Finder, you can run simulations to discover underserved customers.

The tool provides insights into customer groups that are not well-engaged, allowing businesses to adjust their strategies and create more relevant actions or treatments.

 Steps to Run Value Finder:

Log in to the Pega Customer Decision Hub portal.

Navigate to Discovery -> Value Finder.

Create a new simulation and select the relevant issue and group.

Run the simulation to analyze customer distribution and identify underserved segments.

 Verification from Pega Documentation:

The Pega Customer Decision Hub User Guide details the process and benefits of using Value Finder to discover gaps and opportunities in customer engagement strategies​​​​.

Identifying the Requirement:

The bank wants to leverage Pega CDH’s Next-Best-Action capability to promote new offers on their website.

The task is to determine what information Pega CDH sends back to the website in response to a real-time container request.

Evaluating Pega CDH Capabilities:

Pega CDH’s Next-Best-Action Designer is designed to handle real-time interactions and provides personalized recommendations.

The system returns comprehensive details to ensure the website can properly display and execute the recommended actions.

Process Overview:

Real-Time Container Request:

When the website sends a real-time container request, Pega CDH processes the request and identifies the most relevant actions based on customer data and engagement policies.

Response Details:

The response includes treatment details such as the action’s visual elements (image URLs, descriptions) and relevant action attributes (e.g., offer type, benefits, eligibility criteria).

References and Supporting Documentation:

The Pega Customer Decision Hub User Guide clearly outlines that in response to a real-time container request, the system sends back the treatment details and relevant action attributes to ensure the offer can be presented accurately on the website.

References:

Pega-Customer-Decision-Hub-User-Guide-85.pdf

Pega-Customer-Decision-Hub-User-Guide-86.pdf

Pega-Customer-Decision-Hub-User-Guide-87.pdf​

 Requirement:

U+ Bank has added five new actions to the Credit Cards group and wants to enable these actions in the email channel.

 Configuring Each Action with an Email Treatment:

Each action must be configured with an appropriate treatment for the email channel.

Treatments define how the actions are presented in the channel, including the content and format of the email.

This step ensures that the actions are prepared to be sent via email with the correct content.

 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.

Best practices for designing an action flow in Pega Customer Decision Hub emphasize reusability and efficient configuration:

Reusable Flows:

Step 1: When creating a flow that will be reused across multiple actions, it is recommended to use the "Specify Treatment" option.

Step 2: This approach allows you to configure the flow with a specific treatment, making it easier to apply the same flow logic to different actions without having to redesign the flow each time.

Flow Configuration:

Using the "Specify Treatment" option ensures that the treatment details are dynamically inserted when the action is executed, providing flexibility and consistency across various actions.

This method helps maintain a modular design, where flows can be reused and updated independently of the actions they are associated with.

Avoid Redundancy:

Step 1: Reusing flows across multiple actions reduces redundancy and simplifies maintenance.

Step 2: Any changes to the flow logic need to be made only once, and these changes will be reflected across all actions using that flow.

Example:

If you have a standard email flow for promotional offers, you can configure this flow with the "Specify Treatment" option and reuse it for different promotional actions such as discounts, new product launches, or seasonal offers.

References:

Pega-Customer-Decision-Hub-User-Guide-85.pdf: "Configuring the delivery of an email treatment with the Send Email shape" section.

To ensure that a customer does not see offers on their account page if they have already received three home loan offers in the last two weeks, you need to define customer contact limits. These limits allow you to control the number of times a customer can be contacted with specific types of offers within a given timeframe, thus preventing overexposure and enhancing customer satisfaction.

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.

Understanding Aggregation Components: Aggregation components in Pega decision strategies are used to perform calculations based on a list of actions. This can include summing values, calculating averages, or other statistical measures.

Use Case of Aggregation Components:

Set a Text Value: This is typically handled by Set Property or Data Transform components.

Filter Actions: Filters are used for filtering actions based on priority and relevance.

Choose Between Actions: This is typically handled by a Decision or Filter component.

Aggregation is specifically used to perform calculations based on a group of actions. It can be used to sum the total value of actions, calculate the average propensity, etc.

Implementation in Decision Strategy:

Add Aggregation Component: In the decision strategy, add an Aggregation component.

Define Calculation: Specify the type of calculation (sum, average, count, etc.) and the actions to be included in the calculation.

The Pega Customer Decision Hub User Guide mentions the use of aggregation components to perform calculations on action lists, confirming their primary function is for making calculations based on a list of actions (Reference: Pega-Customer-Decision-Hub-User-Guide-85.pdf, Chapter on "Using aggregation components in decision strategies").

Conclusion: In a decision strategy, aggregation components are used to make calculations based upon a list of actions, enabling the strategy to derive meaningful metrics from groups of actions.

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.

References:

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