Free Pegasystems PEGAPCDC87V1 Practice Exam with Questions & Answers | Set: 4

 Context: A bank wants to use the Next-Best-Action capability of Pega Customer Decision Hub to promote offers on their website.

 Real-time Container Request: When a real-time container request is made, Pega Customer Decision Hub processes this request.

 Response Information: The response sent back to the website includes comprehensive details about the actions.

 Details Provided: According to Pega documentation, the response to a real-time container request includes treatment details (like images and descriptions) and relevant action attributes that personalize the offer for the customer​​.

Scorecard Classification - Classifications in a scorecard can segment customers based on score ranges into categories like Not Approved, Refer to Manager, and Approved.

pxSegment Property - This property holds the classification result, which can be used in decision strategies to take appropriate actions based on the classification.

Steps to Use pxSegment:

Ensure the scorecard rule includes the classification bands.

In the decision strategy, reference the pxSegment property to check the classification result.

Use this property in filters, decision points, or to route customers to different actions based on their classification.

In response to the real-time container request by Customer Decision Hub, the U+ Bank website receives only relevant action details and its treatment details. This information includes the specifics of the action to be displayed (such as the offer) and the associated treatment (such as the banner or message), enabling the website to present personalized and contextually relevant offers to customers.

 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.

 Understanding Refresh the Audience Option:

This option ensures the decision process uses the most current data available.

 Functionality:

Before each run of the schedule, the audience data is refreshed to reflect any changes or updates in customer information.

 Purpose:

This ensures decisions are made based on the latest customer profiles, improving the relevance and accuracy of recommendations.

 Verification from Pega Documentation:

Pega documentation on scheduling and audience refresh options for ensuring up-to-date customer data is used.

To select the best offer from both groups based on customer behavior, you should ensure that the propensity is enabled in the Arbitration tab. Propensity scores predict the likelihood of a customer accepting a particular offer, and by enabling propensity, you can prioritize offers that have a higher likelihood of acceptance, thus aligning offers with customer behavior.

 Introduction to Prioritize Component:

The Prioritize component in Pega Decisioning is used to order actions based on specific criteria.

This component evaluates the importance or priority of different actions to determine which should be executed first.

 Understanding Propensity:

Propensity is a prediction of the likelihood that a customer will respond positively to a particular action.

It is a key factor in decision-making processes as it reflects the customer's predicted behavior based on past interactions and other data.

 Role of Propensity in Prioritize Component:

The primary function of the Prioritize component is to rank actions.

This ranking is typically based on the propensity value, which is calculated using predictive models.

The action with the highest propensity is considered the top action because it has the highest predicted likelihood of a positive customer response.

 Verification from Pega Documentation:

According to Pega's guidelines on creating and understanding decision strategies, propensity is a standard and recommended metric for prioritizing actions within the Prioritize component.

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​​.

Contact Policy Conditions - U+ Bank has added all existing contact policy conditions, ensuring that offers comply with set business rules.

Unit Tests with Persona Testing - Before going live, it is essential to validate the implementation through persona-based unit tests. This helps verify that the strategy gives the expected results for different customer personas.

Process:

Design test personas that represent various customer segments.

Run tests to ensure that each persona receives appropriate offers.

Validate the expected outcomes, ensuring no regressions or policy breaches.