Free Pegasystems PEGAPCDC87V1 Practice Exam with Questions & Answers | Set: 5

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.

References:

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".

In designing the next-best-action prioritization expression that balances customer needs with business objectives, you need to consider "Predicted customer behavior." This factor involves using predictive models to forecast how customers are likely to respond to different actions, ensuring that the recommended actions are both relevant to the customer and aligned with business goals.

 Arbitration Factors: To prioritize customer needs in the decision strategy, adjusting the context weighting factor is essential. This factor takes into account the situational context of each action, thereby prioritizing actions that align with customer needs.

 Implementation: By boosting context weighting, you ensure that the decision strategy considers the specific context of customer interactions, leading to more relevant and satisfactory offer presentations.

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​

To access a property from an unconnected component in Pega Customer Decision Hub, you use the component-dot-property construct. This allows you to reference properties from other components within your strategy by specifying the component name followed by the property name. This construct helps in accessing and using data across different components without directly connecting them.

 Grouping Actions: To calculate the total number of customer responses of four actions in a group, you need to use one Group By component. This component can aggregate responses across multiple actions within a strategy.

 Implementation: Add a Group By component to the decision strategy, configure it to group by the desired property, and aggregate the responses from the four actions.

To limit the number of emails sent to customers irrespective of past outcomes with a particular offer and customer, you can implement customer contact limits. Customer contact limits are used to control the number of interactions a customer can receive over a specific period on a particular channel, ensuring that customers are not overwhelmed with too many messages.

Next-Best-Action Strategy Application: Pega's Next-Best-Action strategy can be applied to various business issues to optimize decision-making and enhance customer interactions.

Collections: Used to manage and optimize debt collection processes by determining the best actions to take with customers who have outstanding debts.

Service: Enhances customer service interactions by suggesting the most relevant actions or responses to customer inquiries and issues.

Retention: Focuses on retaining customers by identifying and executing actions that are most likely to keep them engaged and loyal.

 Business Structure: Setting up the business structure to Sales/CreditCards ensures that the actions and offers are correctly categorized and managed within the appropriate business context.

 Real-Time Container: Creating and configuring a real-time container is necessary for presenting the credit card offer to customers in real-time as they log in to the website.

 Action and Web Treatment: Defining the action and configuring its web treatment ensures that the offer is ready to be displayed to the customers, complete with the necessary details and presentation format.