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

To address the issue where customers have ignored a particular mortgage offer and the bank wants to offer the action 30% more frequently, we need to configure the appropriate arbitration factor in Pega Customer Decision Hub.

Arbitration Overview: Arbitration in Pega CDH determines how actions are prioritized and selected for presentation to the customer. It involves factors like business value, propensity, and action weighting.

Action Weighting: Action weighting is used to adjust the frequency and priority of specific actions. By increasing the action weighting, you effectively make the action more likely to be selected during the arbitration process.

Implementation:

Navigate to the Next-Best-Action Designer in Pega CDH.

Locate the action for the mortgage offer that needs increased frequency.

Adjust the action weighting to increase by 30%. This adjustment modifies the priority calculation, making the action more likely to be selected.

 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.

To enable the website to communicate with the Pega Customer Decision Hub and show the Reward Card offer to qualified customers, you need to:

Enable the web channel in the Next-Best-Action Designer's Channel tab. This step activates the web channel for inbound interactions, allowing the system to deliver personalized actions to customers visiting the website.

Map the real-time container to a business structure level. This ensures that the container is correctly linked to the business context, allowing the system to deliver the right offers based on the customer’s interactions with the website.