PEGAPCDC87V1 Exam Dumps : Certified Pega Decisioning Consultant (PCDC) 87V1

Ensuring Latest Customer Information: To ensure that the outbound run always uses the latest customer information, you need to select the "Refresh the audience" option. This setting ensures that the audience is refreshed with the most recent customer data before the campaign is executed.

Implementation: Navigate to the campaign configuration and select the option to refresh the audience before running the campaign. This guarantees that any changes or updates to the customer data are taken into account.

 Requirement:

U+ wants to show a retention offer to customers likely to leave the bank based on historical interaction data.

 Model Types:

Entity Model: Used for recognizing entities within data.

Text Analytics Model: Used for analyzing text data.

Predictive Model: Used for making predictions based on historical data.

Adaptive Model: Used for real-time adaptation based on new data.

 Suitable Model:

For predicting customer churn (likelihood of leaving), a predictive model is best suited because it leverages historical data to make future predictions.

 Verification from Pega Documentation:

Pega documentation on leveraging predictive models for customer retention and churn analysis.

The best way to organize customer actions applicable to various business issues in Pega Customer Decision Hub is into a three-level hierarchy: Business issue > Group > Actions. This structure allows for clear categorization and management of actions based on their business purpose and relevance. The "Business issue" represents the high-level goal (e.g., Retention, Acquisition), "Group" categorizes the actions under each issue (e.g., Credit Cards, Mortgages), and "Actions" are the specific offers or recommendations.