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Pegasystems PEGACPDC25V1 Exam Syllabus Topics:

Section	Weight	Objectives
Business agility in one-to-one customer engagement	12%	- Agile customer engagement 1. Optimize customer experiences 2. Adapt engagement strategies quickly 3. Support business-driven changes
AI and arbitration	12%	- Decision optimization 1. Use AI in decisioning 2. Prioritize actions 3. Apply arbitration logic
Contact policy and volume constraints	13%	- Contact governance 1. Apply volume constraints 2. Configure contact policies 3. Control customer contact frequency
Channels	10%	- Multi-channel engagement 1. Web channel configuration 2. Outbound channel setup 3. Cross-channel engagement
Engagement policies	15%	- Customer engagement rules 1. Create an engagement strategy 2. Customer journeys 3. Define customer engagement policies
Next-Best-Action concepts	12%	- One-to-one customer engagement 1. Optimize the customer value in the contact center 2. Essentials of always-on outbound 3. Customer engagement blueprint 4. Define the starting population 5. Optimize the next-best-action strategy
Decision strategies	14%	- Strategy design 1. Build decision strategies 2. Use predictive analytics 3. Test decision logic
Actions and treatments	12%	- Manage customer actions 1. Present a single offer on the web 2. Define and manage customer actions 3. Define an action for outbound

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Pegasystems Certified Pega Decisioning Consultant 25 PEGACPDC25V1 Prüfungsfragen mit Lösungen (Q83-Q88):

83. Frage
A bank has been running traditional marketing campaigns for many years. One such campaign sends an offer email to qualified customers on day one. On day five, the bank presents a similar offer if the first email is ignored.
If you re-implement this requirement by using the always-on outbound customer engagement paradigm, how do you approach this scenario?

A. Create two segments to identify the target audience for each of the two offer emails: day one, and day five. Set up two schedules per day for the two segments.
B. Configure the primary schedule to run daily and let the artificial intelligence (AI) choose the best action based on engagement policies.
C. Configure a primary schedule for the original offer email and setup an ad-hoc schedule to send the second email.
D. Create an action with a flow that contains two Send Email shapes, one for each email. Set appropriate wait times between the shapes.

Antwort: B

Begründung:
The always-on outbound customer engagement paradigm relies on AI to select the best action for each customer at any given time, based on their profile, context, and behavior. You do not need to create separate segments or schedules for different offers or timings. You can configure the primary schedule to run daily and let the AI choose the best action based on engagement policies, such as contact policies, eligibility rules, suitability rules, and arbitration. The AI will also learn from the customer responses and optimize the action selection over time.

84. Frage
You are a deaccessioning architect on a next-best-action project and are responsible for designing and implementing decision strategies. Select each component on the left and drag it to the correct requirement on the right.

Antwort:

Begründung:
A close-up of a list of words AI-generated content may be incorrect.

85. Frage
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?

A. A list of customer email addresses from the Test email tab
B. Preview section from the email content editor
C. A seed list from the Test email tab
D. Schedule an outbound run with a limited number of customers

Antwort: C

Begründung:
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 Reference: [Pega Academy - Decisioning Consultant - Testing email treatments]

86. Frage
GlobalRetail operates in a fast-changing digital marketplace where customer preferences and competitor offers change weekly. Their marketing team struggles with lengthy approval processes that prevent quick responses to market trends, often causing them to miss critical engagement opportunities.
What does agility represent in the context of customer engagement projects?

A. Automating all business processes through artificial Intelligence and machine learning algorithms
B. An organization's ability to react quickly to marketplace changes and emerging trends
C. Eliminating all testing requirements to completely accelerate software deployment cycles
D. Outsourcing decision-making processes to external vendors for faster implementation speeds

Antwort: B

87. Frage
U+ Bank has recently defined two contact policies:
1. Suppress a group of credit card offers for 30 days if any credit card offer is rejected three times in any channel in the past 15 days.
2. Suppress the Reward card offer, part of the credit card group, for 7 days if it is rejected twice in any channel in the last 7 days. Paul, an existing U+ Bank customer, no longer sees the Reward card offer. What is the reason that Paul cannot see the offer?

A. Paul rejected the Reward card offer once in contact center.
B. Paul rejected other credit card offers twice on the web channel and once in contact center.
C. Paul rejected other credit card offers once on the web channel and once in the contact center.
D. Paul rejected the Reward card offer once on the web channel.

Antwort: B

Begründung:
Paul cannot see the Reward card offer because he rejected other credit card offers twice on the web channel and once in contact center in the past 15 days. This triggers the first contact policy that suppresses a group of credit card offers for 30 days if any credit card offer is rejected three times in any channel in the past 15 days.
The Reward card offer is part of the credit card group, so it is suppressed for Paul for 30 days. The second contact policy that suppresses the Reward card offer for 7 days if it is rejected twice in any channel in the last
7 days does not apply because Paul did not reject the Reward card offer twice in any channel in the last 7 days. Verified References: [Certified Pega Decisioning Consultant | Pega Academy], Suppression policies system Following is the description of the image that was sent with question no:5:
* This is a screenshot of a table with four columns and two rows.
* The table has a header row with white text on a blue background.
* The header row reads "Constraint name", "Constraint mode", "Constraint value", and "Channel".
* The second row has black text on a white background.
* The second row reads "Standard card", "Return any action that does not exceed", "100", and "Daily".
* The table has a gray border and a light blue background.

88. Frage
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