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Pegasystems PEGAPCDC87V1 Exam Questions
- Topic 1: Next-Best-Action concepts: This section examines personalized customer interactions, maximizing customer value in call centers, and strategies for proactive outreach.
- Topic 2: Actions and treatments: This section explores the creation and management of customer-focused actions, web-based offer presentations, and outbound action definition.
- Topic 3: Engagement policies: Discusses the development of customer engagement guidelines and the formulation of engagement strategies.
- Topic 4: Contact policy and volume constraints: Focuses on preventing excessive action exposure, especially in outbound communications, and controlling action frequency.
- Topic 5: AI and Arbitration: Investigates action arbitration techniques, AI-driven prioritization methods, and the use of business levers for action prioritization.
- Topic 6: Channels: Delves real-time container concepts, email offer delivery, and the process of sharing action information with external distribution partners.
Free Pegasystems PEGAPCDC87V1 Exam Actual Questions
Note: Premium Questions for PEGAPCDC87V1 were last updated On Apr. 08, 2026 (see below)
In a decision strategy, you can use aggregation components to_______________.
Understanding Aggregation Components: Aggregation components in Pega decision strategies are used to perform calculations based on a list of actions. This can include summing values, calculating averages, or other statistical measures.
Use Case of Aggregation Components:
Set a Text Value: This is typically handled by Set Property or Data Transform components.
Filter Actions: Filters are used for filtering actions based on priority and relevance.
Choose Between Actions: This is typically handled by a Decision or Filter component.
Aggregation is specifically used to perform calculations based on a group of actions. It can be used to sum the total value of actions, calculate the average propensity, etc.
Implementation in Decision Strategy:
Add Aggregation Component: In the decision strategy, add an Aggregation component.
Define Calculation: Specify the type of calculation (sum, average, count, etc.) and the actions to be included in the calculation.
The Pega Customer Decision Hub User Guide mentions the use of aggregation components to perform calculations on action lists, confirming their primary function is for making calculations based on a list of actions (Reference: Pega-Customer-Decision-Hub-User-Guide-85.pdf, Chapter on 'Using aggregation components in decision strategies').
Conclusion: In a decision strategy, aggregation components are used to make calculations based upon a list of actions, enabling the strategy to derive meaningful metrics from groups of actions.
U+ Bank, a retail bank, uses Pega Customer Decision Hub for their one-to-one customer engagement. The bank now wants to change its offer prioritization to consider both business objectives and customer needs.
Which two factors do you configure in the Next-Best-Action Designer to implement this change? (Choose Two)
Business Levers: These are used to apply weights to different actions or groups of actions to influence their prioritization based on business objectives.
Context Weighting: This factor is used to adjust the priority of actions based on the specific context of the customer interaction, ensuring that both business objectives and customer needs are balanced.
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 consultant, what must you do to present offers from the two groups?
To present offers from both groups and arbitrate across the two groups to select the best offer based on customer behavior, you need to map a real-time container to the Top-level or Issue-level in the Next-Best-Action Designer. This mapping allows the system to evaluate and arbitrate offers from different groups based on the defined criteria and customer behavior, ensuring the most relevant offers are presented.
Which two of these statements is true about Value Finder? (Choose Two)
Value Finder is a tool in Pega Customer Decision Hub that helps identify and visualize the distribution of under-served customers across different groups. It also highlights opportunities for improvement by pinpointing areas where the engagement policies or strategies can be optimized to better serve these customers. This helps in fine-tuning the next-best-action strategies to enhance overall customer engagement and satisfaction.
Value Finder functionality and use cases (Page 140-142)
Identifying and addressing under-served customer segments (Page 144-146)
Reference module: Leveraging predictive model.
U+, a retail bank, wants to show a retention offer to customers who are likely to leave the bank in the near future based on historical customer interaction dat
a. Which type of model do you use to implement this requirement?
Requirement:
U+ wants to show a retention offer to customers likely to leave the bank based on historical interaction data.
Model Types:
Entity Model: Used for recognizing entities within data.
Text Analytics Model: Used for analyzing text data.
Predictive Model: Used for making predictions based on historical data.
Adaptive Model: Used for real-time adaptation based on new data.
Suitable Model:
For predicting customer churn (likelihood of leaving), a predictive model is best suited because it leverages historical data to make future predictions.
Verification from Pega Documentation:
Pega documentation on leveraging predictive models for customer retention and churn analysis.
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