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

Compute SUM of PROFIT = Group BY

Determine target budget to retain a customer = Set Property

Determine customer credit score = Scorecard

Divide customers into risk segment = Decision Table

 Placement Type in Treatment Design: To present the Rewards Card offer on the top right of the customer’s account page, you should use the "Tile" placement type. This type is specifically designed to position content in a compact, visually distinct block that can be placed in specific areas of a webpage, such as the top right corner.

 Implementation: In the treatment configuration within Pega, you can specify the placement type as "Tile" to ensure the offer is displayed correctly on the account page.

 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.