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

To manage the communication between Pega Customer Decision Hub and external channels for promoting new offers to each customer on their website, you need to configure a Real-time Container. Real-time Containers are used to deliver personalized content and actions to customers in real-time, based on their interactions with the website and other channels. They ensure that the most relevant offers are presented to each customer in a timely and contextually appropriate manner.

 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 implement the change in the threshold value for the USD 2000 credit limit from “<175” to “<200”, as a Strategy Designer, you should change the cutoff value in the results tab of the scorecard decision component. This adjustment ensures that the decision logic used to automatically approve credit card limits reflects the new threshold, thereby updating the conditions under which customers qualify for the specified credit limit.