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What is the PEGACPDC25V1 Certified Pega Decisioning Consultant 25 Exam?

The PEGACPDC25V1 Certified Pega Decisioning Consultant 25 Exam is a professional certification exam designed to validate your ability to design and implement decisioning solutions using Pega Customer Decision Hub. This certification focuses on AI-driven customer engagement, helping organizations deliver the Next-Best-Action (NBA) to customers across multiple channels in real time.

Professionals who pass this exam demonstrate their ability to:

● Design customer-centric engagement strategies

● Implement Next-Best-Action Designer

● Manage 1:1 Operations Manager

● Build decision strategies and predictive models

● Apply AI-driven action arbitration

● Deliver personalized offers across channels

By earning this certification, candidates prove they can help organizations optimize customer engagement using data, AI, and business rules within the Pega ecosystem.

Who is the PEGACPDC25V1 Exam For?

The PEGACPDC25V1 exam is intended for professionals who are involved in designing and implementing Pega Customer Decision Hub solutions.

Typical candidates include:

● Pega Decisioning Consultants

● Pega Developers

● Customer Decision Hub Specialists

● Customer Engagement Architects

● Business Analysts working with Pega decisioning

● Marketing technology professionals

This certification is particularly valuable for professionals who work with AI-driven marketing, customer engagement platforms, and intelligent automation solutions.

PEGACPDC25V1 Exam Overview

Number of Questions: 60

Exam Duration: 90 minutes

Passing Score: 70%

Language: English

Question Type: Multiple-choice

The exam evaluates your ability to apply decisioning strategies, customer engagement design principles, and AI-driven arbitration within the Pega platform.

Skills Measured in the PEGACPDC25V1 Exam

The exam measures your knowledge across several core domains of Pega Customer Decision Hub.

1. Next-Best-Action Concepts (12%)

Candidates must understand the fundamentals of Next-Best-Action decisioning, including:

One-to-one customer engagement

Customer engagement blueprint

Optimizing customer value in contact centers

Always-on outbound engagement

Defining the starting population

Optimizing next-best-action strategies

2. Actions and Treatments (12%)

This section focuses on defining customer offers and interactions, including:

Creating and managing customer actions

Presenting single offers on web channels

Configuring outbound customer actions

3. Engagement Policies (15%)

Candidates must know how to govern customer interactions through engagement rules.

Key concepts include:

Defining customer engagement policies

Creating engagement strategies

Managing customer journeys

4. Contact Policy and Volume Constraints (13%)

This topic ensures organizations avoid overwhelming customers with too many offers.

Areas covered include:

Preventing overexposure to actions

Limiting outbound action frequency

Managing contact policies and action volume

5. AI and Arbitration (8%)

This section focuses on AI-based prioritization and decision logic.

Candidates should understand:

Action arbitration

AI-driven action prioritization

Using business levers to influence decision outcomes

6. Channels (10%)

Candidates must understand how actions are delivered across different communication channels.

Topics include:

Real-time containers

Creating real-time decision containers

Sending offer emails

Sharing actions with third-party distributors

7. Decision Strategies (15%)

Decision strategies are the core logic behind intelligent customer engagement.

Candidates should be able to:

Create and analyze decision strategies

Use customer data such as credit scores

Implement engagement strategies based on analytics

8. Business Agility in 1:1 Customer Engagement (15%)

This domain focuses on operational agility and change management.

Key topics include:

Change management processes

Managing business operations teams

Life cycle of change requests

Launching and updating offers

Managing actions using Revision Manager

Using Pega GenAI for brand voice

Updating actions in bulk

Using the enhanced email editor

How to Prepare for the PEGACPDC25V1 Exam

Preparing for the PEGACPDC25V1 exam requires a combination of theoretical knowledge and hands-on experience with the Pega platform.

1. Study the Official Exam Topics

Carefully review each domain in the exam blueprint and focus on high-weight topics such as decision strategies, engagement policies, and business agility.

2. Gain Hands-On Experience

Practical experience with Pega Customer Decision Hub is essential. Try to practice:

Building Next-Best-Action strategies

Creating engagement policies

Designing decision strategies

Configuring channels and containers

3. Use Structured Study Materials

Prepare using:

Official Pega documentation

Online training courses

Study guides

Technical tutorials

4. Practice with Realistic Exam Questions

Practice questions help you:

Understand real exam question formats

Identify weak knowledge areas

Improve exam speed and confidence

How to Use PEGACPDC25V1 Practice Questions Effectively

Practice questions are one of the most effective ways to prepare for certification exams.

Step 1: Start With Topic-Based Practice

Focus on questions from one domain at a time, such as Next-Best-Action or Decision Strategies.

Step 2: Review Detailed Explanations

Always review explanations for both correct and incorrect answers to understand the reasoning behind them.

Step 3: Simulate Real Exam Conditions

Take full-length practice exams under timed conditions (90 minutes) to improve time management.

Step 4: Analyze Weak Areas

Identify topics where you frequently make mistakes and review the relevant study material again.

Practice Questions for the PEGACPDC25V1 Exam

Using PEGACPDC25V1 practice questions with detailed explanations helps candidates become familiar with the exam structure and improve their problem-solving skills.

Benefits of using practice questions include:

● Understanding real-world decisioning scenarios

● Learning how Next-Best-Action strategies are implemented

● Practicing AI-based prioritization logic

● Mastering engagement policy configuration

● Improving exam readiness and confidence

High-quality practice questions closely mirror the actual exam format, helping candidates build the skills needed to pass the certification successfully.

Question#1

HOTSPOT
U+ Bank's marketing department wants to use the always-on outbound approach to send promotional emails about credit card offers to qualified customers. As a part of this promotion, the bank wantsto identify the starting population by defining a few high-level criteria ina segment.
For each condition below, select which two conditions should be defined in Segment and which three conditions should be defined in Engagement policy as best practice

Question#2

A customer qualifies for Standard card (priority 60), Rewards card {priority 40), and Premium card {priority 30). Standard card volume is exhausted. Rewards card has remaining volume, and Premium card has remaining volume. The system uses "Return any action that does not exceed constraint" mode.
Which actions does the customer receive in this scenario?

A. Standard card only as highest priority action

B. No actions due to Standard card volume exhaustion

C. Premium card only as lowest priority available action

D. Rewards card and Premium card as available actions

Question#3

Maximum 25 Daily with Action: MyFone AirPods Pro, 0 remaining
A customer, CUST-01, qualifies for all the three actions.
Given this scenario, how many actions does the system select for CUST-01 in the outbound run?

A. 3

B. 0

C. 2

D. 1

Question#4

Refer to the exhibit.

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?

A. Very Poor

B. Good

C. Fair

D. Poor

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.

Question#5

MyCo, a mobile company, uses Pega Customer Decision Hub™ to display offers to customers on its website. The company wants to present more relevant offers to customers based on customer behavior.
The following diagram is the action hierarchy in the Next-Best-Action Designer.

The company wants to present offers from both the groups and arbitrate across the two groups to select the best offer based on customer behavior.
As a decisioning architect, what must you do to present offers from the two groups?

A. Enable an engagement policy for the second group.

B. Map a real-time container to the Top-level or Issue-level.

C. Set contact limits for both the groups.

D. Create a decision strategy at the Issue-level

Explanation:
To present offers from the two groups, you must map a real-time container to the Top-level or Issue-level. A real-time container is a configuration that defines how to deliver offers and treatments to a specific channel, such as a website or a mobile app. By mapping a real-time container to the Top-level or Issue-level, you can enable all the offers under that level to be available for delivery through that channel.
Verified Reference: Pega Academy - Decisioning Consultant - Configuring real-time containers

Disclaimer

This page is for educational and exam preparation reference only. It is not affiliated with Pegasystems, Data Scientist, or the official exam provider. Candidates should refer to official documentation and training for authoritative information.

Exam Code: PEGACPDC25V1Q & A: 106 Q&AsUpdated: 2026-04-10

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