Quiz 2026 Pegasystems PEGACPDC25V1: Certified Pega Decisioning Consultant 25 Perfect Current Exam Content

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Pegasystems PEGACPDC25V1 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Decision strategies14%- Strategy design
  • 1. Build decision strategies
  • 2. Use predictive analytics
  • 3. Test decision logic
Topic 2: Engagement policies15%- Customer engagement rules
  • 1. Customer journeys
  • 2. Create an engagement strategy
  • 3. Define customer engagement policies
Topic 3: Next-Best-Action concepts12%- One-to-one customer engagement
  • 1. Optimize the next-best-action strategy
  • 2. Define the starting population
  • 3. Essentials of always-on outbound
  • 4. Optimize the customer value in the contact center
  • 5. Customer engagement blueprint
Topic 4: Business agility in one-to-one customer engagement12%- Agile customer engagement
  • 1. Support business-driven changes
  • 2. Optimize customer experiences
  • 3. Adapt engagement strategies quickly
Topic 5: Actions and treatments12%- Manage customer actions
  • 1. Define and manage customer actions
  • 2. Present a single offer on the web
  • 3. Define an action for outbound
Topic 6: Contact policy and volume constraints13%- Contact governance
  • 1. Apply volume constraints
  • 2. Configure contact policies
  • 3. Control customer contact frequency
Topic 7: AI and arbitration12%- Decision optimization
  • 1. Apply arbitration logic
  • 2. Prioritize actions
  • 3. Use AI in decisioning
Topic 8: Channels10%- Multi-channel engagement
  • 1. Cross-channel engagement
  • 2. Outbound channel setup
  • 3. Web channel configuration

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Pegasystems Certified Pega Decisioning Consultant 25 Sample Questions (Q77-Q82):

NEW QUESTION # 77

U+ Bank wants to offer credit cards only to low-risk customers. The customers are divided into various risk segments from Good to Very Poor. The risk segmentation rules that the business provides use the Average Balance and the customer Credit Score.
As a decisioning architect, you decide to use a decision table and a decision strategy to accomplish this requirement in Pega Customer Decision Hub.
Using the decision table, which label is returned for a customer with a credit score of 240 and an average balance 35000?

Answer: A

Explanation:
Using the decision table, you can find the label for a customer with a credit score of 240 and an average balance of 35000 by following these steps:
* Start from the top row and check if the customer's credit score is less than 150. If yes, then the label is Very Poor. If no, then move to the next row.
* Check if the customer's credit score is less than 175 and their average balance is less than 25000. If yes, then the label is Poor. If no, then move to the next row.
* Check if the customer's credit score is less than 200 and their average balance is less than 50000. If yes, then the label is Fair. If no, then move to the next row.
* Check if the customer's credit score is less than 250 and their average balance is less than 75000. If yes, then the label is Good. If no, then move to the last row.
* The last row applies to all other cases that do not match any of the previous conditions. The label for this row is Very Poor.
In this case, the customer's credit score is not less than 150, so the first row does not apply. The customer's credit score is less than 175, but their average balance is not less than 25000, so the second row does not apply either. The customer's credit score is not less than 200, so the third row does not apply. The customer's credit score is less than 250 and their average balance is less than 75000, so the fourth row applies. Therefore, the label for this customer is Poor.


NEW QUESTION # 78
U+ Bank has decided to use the Pega Customer Decision Hub, M to recommend more relevant banner ads to its customers when they visit the personal portal. Select each placement type on the left and drag it to the correct requirement on the right.

Answer:

Explanation:


NEW QUESTION # 79
As a decisioning architect, you advise the board on the business issues for which they must use the Next-Best- Action strategy. Which three business issues do you recommend? (Choose Three)

Answer: C,D,E

Explanation:
The Next-Best-Action strategy is a customer-centric approach that aims to deliver the most relevant and valuable proposition for each customer at any given moment. You can use the Next-Best-Action strategy to address various business issues that involve customer interactions, such as service, retention, and collections.
Service is the process of providing assistance and support to customers who have questions or problems.
Retention is the process of preventing customers from leaving or switching to competitors. Collections is the process of recovering unpaid debts from customers who are delinquent or defaulting on their obligations.
These are all business issues that can benefit from using the Next-Best-Action strategy. Verified References:
[Pega Decisioning Consultant | Pega Academy]


NEW QUESTION # 80
U+ Bank wants to offer a Gold credit card to customers who have an annual income of more than USD150000. What do you configure in the Next-Best-Action Designer to achieve this outcome7

Answer: D

Explanation:
An engagement policy condition is a rule that determines whether a customer is eligible, applicable, or suitable for an offer. You can use engagement policy conditions to filter customers based on their attributes or behaviors. In this case, the bank wants to offer a Gold credit card to customers who have an annual income of more than USD150000, so creating an engagement policy condition based on the income attribute is the best option. Verified References: [Pega Decisioning Consultant | Pega Academy]


NEW QUESTION # 81
Pega Customer Decision Hub enables organizations to make Next-Best decisions. To which type of a decision is Next-Best-Action applied?

Answer: B

Explanation:
Next-Best-Action is a type of decision that involves selecting and prioritizing the most appropriate proposition for each customer at any given moment. Next-Best-Action can be applied to decisions that require customer-centricity, personalization, and contextualization. Determining if a borrower gets a loan is an example of such a decision, as it depends on the customer's attributes, behaviors, preferences, and needs. The other options are examples of decisions that are not related to customer interactions, but rather to operational or analytical processes. Verified Reference: [Pega Decisioning Consultant | Pega Academy]


NEW QUESTION # 82
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