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Pegasystems PEGACPDC25V1 Exam Syllabus Topics:

SectionObjectives
Topic 1: Customer Decision Hub Overview- Engagement Policy Design
  • 1. Eligibility and applicability rules
    • 2. Constraints and suitability rules
      - Next-Best-Action (NBA) Framework
      • 1. NBA decision strategies
        • 2. Action prioritization and arbitration
          Topic 2: Reporting and Monitoring- Performance tracking
          • 1. Decision results monitoring
            • 2. Business outcome reporting
              Topic 3: AI and Adaptive Analytics- Machine learning in decisioning
              • 1. Model usage in NBA
                • 2. Feature impact and feedback cycles
                  - Adaptive models
                  • 1. Propensity scoring
                    • 2. Outcome prediction and learning loops
                      Topic 4: Decision Strategies and Configuration- Strategy building blocks
                      • 1. When, if, and decision shapes
                        • 2. Strategy results and propositions
                          - Real-time decisioning
                          • 1. Event-driven decisioning
                            • 2. Context handling in real time
                              Topic 5: Customer Engagement and Channels- Omnichannel delivery
                              • 1. Channel configuration
                                • 2. Customer interaction history

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                                  Pegasystems Certified Pega Decisioning Consultant 25 Sample Questions (Q62-Q67):

                                  NEW QUESTION # 62
                                  The U+ Bank marketing department wants to leverage the next-best-action capability of Pega Customer Decision Hub on Its website to promote new offers to each customer.
                                  Place the events in the sequential order.

                                  Answer:

                                  Explanation:

                                  1 - The website invokes the real-time container before loading the account page.
                                  2 - Customer Decision Hub evaluates offers from the associated issue/group.
                                  3 - Customer Decision Hub returns the resulting offer details to the website.
                                  4 - The website loads the account page with the content returned by Customer Decision Hub.


                                  NEW QUESTION # 63
                                  Regional Bank has a fully implemented 1:1 customer engagement solution that is in the business-as-usual phase. A business user from this bank identifies the need for a new promotional offer for customers who regularly use mobile banking services. The user has detailed requirements including eligibility criteria, treatment messaging, and implementation timeline.
                                  Which process should the business user follow to implement the new action?

                                  Answer: A


                                  NEW QUESTION # 64
                                  MyCo, a telecom company, uses Pega Customer Decision Hub to present offers to qualified customers. The business recently decided to send offer messages through the email channel. The Design department has designed an email treatment which includes dynamic placeholders.
                                  As a deaccessioning architect, what do you use in order to test the visualization and the rendering of the email content, including replacing of the placeholders with customer information?

                                  Answer: C

                                  Explanation:
                                  To test the visualization and the rendering of the email content, including replacing of the placeholders with customer information, you use a seed list from the Test email tab. A seed list is a predefined set of customers that you can use to test your email treatments before sending them to your target audience. You can select one or more customers from the seed list and send them a test email with your treatment. You can then verify how the email looks in their inbox and how the placeholders are replaced with their actual values. Verified References: [Pega Academy - Decisioning Consultant - Testing email treatments]


                                  NEW QUESTION # 65
                                  U+ Bank, a retail bank, is currently presenting a cashback offer on its website.
                                  Currently, only the customers who satisfy the following engagement policy conditions receive the cashback offer:
                                  While continuing cross-selling on the web, the bank now wants to present the cashback offer through a new channel, SMS. The bank also wants to update the suitability condition by lowering the threshold of the debt-to-income ratio from 48 to 45.
                                  As a business user, what are the two tasks that you define to update the cashback offer? (Choose Two)

                                  Answer: B,C

                                  Explanation:
                                  To update the cashback offer, you need to edit the engagement policy and the action details. Editing the engagement policy allows you to add a new channel (SMS) and update the suitability condition (lowering the debt-to-income ratio). Editing the action details allows you to specify the treatment for each channel (web and SMS). Verified Reference: [Pega Decisioning Consultant | Pega Academy]


                                  NEW QUESTION # 66
                                  U+ Bank presents various credit card offers to its customers on its website. The bank uses AI to prioritize the offers according to customer behavior. With the introduction of the Gold credit card offer, the offer click-through propensity decreased to 0.42.
                                  What does the decrease in the propensity value most likely indicate?

                                  Answer: B

                                  Explanation:
                                  The propensity is a measure of how likely a customer is to accept an offer, based on their attributes and behaviors. The propensity is calculated by using predictive analytics models that learn from historical data and feedback. A low propensity value indicates that the offer is not relevant or attractive for the customer, and that similar customers have ignored or rejected the offer in the past. Therefore, if the offer click-through propensity decreased to 0.42, it most likely indicates that similar customers ignore the offer. Verified Reference: Pega Decisioning Consultant | Pega Academy


                                  NEW QUESTION # 67
                                  ......

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