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Pegasystems PEGACPDC25V1 Exam Syllabus Topics:

TopicDetails
Topic 1
  • AI and Arbitration: Explores AI-powered action arbitration, prioritization, and using business levers for action selection.
Topic 2
  • Actions and treatments: Focuses on defining and managing customer actions for web and outbound channels.
Topic 3
  • Next-Best-Action concepts: Covers one-to-one engagement fundamentals, contact center optimization, always-on outbound strategies, and next-best-action optimization.
Topic 4
  • Decision strategies: Focuses on building decision strategies with business logic to power the decisioning engine.
Topic 5
  • Channels: Covers implementing real-time containers, offer emails, and third-party integrations for multi-channel delivery.
Topic 6
  • Engagement policies: Addresses creating engagement policies, strategies, and customer journeys that govern contact timing and frequency.

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Pegasystems Certified Pega Decisioning Consultant 25 Sample Questions (Q46-Q51):

NEW QUESTION # 46
MyCo, a telecom company, recently introduced a new mobile handset offer, MyFone 14 Pro, for its premium customers. As the bank has financial targets to meet, the business decides to boost the MyFone 14 Pro offer.
As a decisioning architect, how can you ensure that the MyFone 14 Pro offer is prioritized over other offers?

Answer: B

Explanation:
The business weight is a parameter that allows you to manually adjust the priority of an offer based on your business objectives and preferences. The business weight is multiplied by the business value and the propensity to calculate the final priority score of an offer. A higher business weight means a higher priority score, making the offer more likely to be selected and presented to the customer. Therefore, if you want to boost an offer, you can increase its business weight. Verified Reference: Pega Decisioning Consultant | Pega Academy


NEW QUESTION # 47
What is the name of the property that the system computes automatically when you use an Adaptive Model decision component?

Answer: D

Explanation:
Propensity is the name of the property that the system computes automatically when you use an Adaptive Model decision component. Propensity is a measure of how likely a customer is to accept an action, based on their past behavior and profile. An Adaptive Model component uses machine learning to calculate the propensity for each action and store it in a property with the same name as the action. Verified References: Pega Academy - Decisioning Consultant - Using adaptive models


NEW QUESTION # 48
An outbound run identifies 150 Standard card offers, 75 on email, and 75 on the SMS channel. If the following volume constraint Is applied, how many actions are delivered by the outbound run?

Answer: B


NEW QUESTION # 49
As a decisioning architect, you have built a decision strategy that selects actions that are below the average printing cost. The decision strategy contains 'Black Label', 'Red Label,' and 'Blue Label" Proposition components. The printing cost of the Proposition components are calculated based on the 'BaseCost' and
'LetterCount*.

The details of the proposition components are provided in the following table:

Which propositions does the strategy output?

Answer: C


NEW QUESTION # 50
l)+ Bank uses Pega Customer Decision Hub to approve credit card limit changes requested by customers automatically. A scorecard model determines the customer credit score. The automatic approval of credit card limits are processed based on the following criteria set by the bank.

The bank wants to change the threshold value for the USD2000 credit limit from <175 to <200. How do you implement this change?

Answer: C

Explanation:
The scorecard model determines the customer credit score based on various factors, such as income, expenses, assets, liabilities, etc. The scorecard model has a Results tab where you can define the cutoff values for different segments based on the credit score. To change the threshold value for the USD2000 credit limit from
<175 to <200, you need to change the cutoff value in the Results tab of the scorecard model. Changing the cutoff value in the scorecard decision component, changing the condition in the strategy, or mapping the score value in the decision strategy will not affect the credit score calculation or segmentation.


NEW QUESTION # 51
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