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NEW QUESTION # 89
U+ Bank has recently implemented a cross-sell on the web microjourney and is satisfied with the results. The bank now wants these Next-Best-Action recommendations to be delivered via outbound communication channels. Select two outbound channels that U+ bank can use to deliver Next-Best-Action recommendations.
(Choose Two).
- A. Contact Center
- B. Email
- C. Mobile application
- D. SMS
- E. Google
Answer: B,D
Explanation:
Context:
* U+ Bank wants to use outbound communication channels for Next-Best-Action recommendations.
Available Outbound Channels:
* Mobile Application: Typically considered an inbound channel.
* Google: Used for online advertising but not a direct outbound channel.
* SMS: Commonly used outbound channel for direct customer communication.
* Email: Widely used outbound channel for direct customer communication.
* Contact Center: Usually an inbound channel where customers call in.
Selection:
* SMS and Email are the most suitable outbound channels for sending Next-Best-Action recommendations directly to customers.
Verification from Pega Documentation:
* Pega documentation on configuring and using SMS and Email as outbound channels for Next-Best-Action delivery.
NEW QUESTION # 90
U+ Bank uses Pega Customer Decision Hub to display an offer to its customers on the U+ Bank website.
The bank wants to ensure that Silver credit cards are not offered to customers under 27 years of age. They also want to ensure that Platinum cards are offered only to customers who had a positive balance in the last year.
What do you configure in the Next-Best-Action Designer to achieve this outcome?
- A. Customer segments
- B. Arbitration rules
- C. Engagement policies
- D. Contact policy rules
Answer: C
Explanation:
To ensure that Silver credit cards are not offered to customers under 27 years of age and that Platinum cards are offered only to customers who had a positive balance in the last year, you need to configure "Engagement policies" in the Next-Best-Action Designer. Engagement policies allow you to set criteria such as eligibility, applicability, and suitability for actions. For this scenario, you would set the eligibility criteria to ensure the age and balance conditions are met before the offers are presented.
NEW QUESTION # 91
A bank developed a scorecard to automate the loan approval process. In a decision strategy, how do you use the raw score value computed by the scorecard?
- A. Map a new property in the Score Mapping tab
- B. Use the PropertyHasValue function
- C. Use the pyOutcome property
- D. Use the pxSegment property
Answer: A
Explanation:
* Score Mapping Tab - This tab in the scorecard rule is used to map the raw score to a property that can
* be used in decision strategies.
* Steps to Map a New Property:
* Open the scorecard rule in Dev Studio.
* Navigate to the Score Mapping tab.
* Add a new mapping for the raw score to a property (e.g., pyRawScore).
* Save the scorecard rule.
* Using the Mapped Property:
* In the decision strategy, reference the mapped property to utilize the raw score value.
* Apply this property in conditions, filters, or other decision components as needed.
NEW QUESTION # 92
U+ Bank a retail bank, has recently implemented a project in which credit card offers are presented to qualified customers when they log in lo the web self-service portal. The bank added engagement policy conditions to show the offers based on the banks requirements.
In the Answer Area select the correct engagement policy for each condition.
Answer:
Explanation:
Explanation:
Correct Engagement Policy Configuration:
* The customer must not be flagged as a defaulted borrower
* Engagement policy: Eligibility
* Customer already owns a higher-value offer
* Engagement policy: Applicability
* Must be a resident of New York City
* Engagement policy: Eligibility
* The savings product offers are relevant only if the customer has not explicitly opted out of direct marketing
* Engagement policy: Applicability
* Inappropriate for customers with a credit score < 300 as they are likely to default
* Engagement policy: Suitability
* The customer must not be flagged as a defaulted borrower
* Eligibility: Eligibility conditions determine whether a customer qualifies for an offer at a basic level. Being flagged as a defaulted borrower is a fundamental criterion to disqualify a customer from receiving certain offers.
NEW QUESTION # 93
Reference module: Analyzing customer distribution using Pega Value Finder Which two of the following statements are true about Value Finder? (Choose Two)
- A. Provides recommendations to loosen strict conditions
- B. Shows the distribution of under-served customers across different groups
- C. Projects estimated value of the subsequent next-best-action run
- D. Identifies engagement policy conditions with bias
Answer: A,B
Explanation:
Value Finder in Pega Customer Decision Hub identifies under-served customer segments and provides recommendations to optimize engagement policies. It helps in understanding how different customer groups are being served and suggests adjustments to engagement conditions to ensure a more inclusive and effective customer outreach.
NEW QUESTION # 94
Reference module: Creating eligibility rules using customer risk segments.
U+ Bank uses a decision table to return a label for a customer. Examine this decision table and select which label is returned for a customer with a credit score of 115 and an average balance of 15000.
- A. A
- B. D
- C. B
- D. C
Answer: D
NEW QUESTION # 95
Reference module: Creating eligibility rules using customer risk segments.
U+ Bank uses a decision table to return a label for a customer. Examine this decision table and select which label is returned for a customer with a credit score of 115 and an average balance of 15000.
- A. C
- B. A
- C. B
- D. D
Answer: C
Explanation:
Understanding the Decision Table:
* The decision table provided returns a label based on a customer's credit score and average balance.
* The rules are evaluated in order, and the first matching rule determines the result.
Evaluating the Customer Data:
* The customer has a credit score of 115 and an average balance of 15000.
* We will evaluate each row of the decision table to see where these values fit.
Rule Evaluation:
* First Rule: Credit Score >= 130 and Average Balance >= 30000
* Customer's Credit Score: 115 (not >= 130)
* This rule does not match.
* Second Rule: Credit Score >= 110 and Average Balance >= 20000
* Customer's Credit Score: 115 (>= 110) but Average Balance: 15000 (not >= 20000)
* This rule does not match.
* Third Rule: Credit Score >= 90 and Average Balance >= 10000
* Customer's Credit Score: 115 (>= 90) and Average Balance: 15000 (>= 10000)
* Both conditions match, so the result is "C".
* Fourth Rule: Credit Score >= 70 and Average Balance >= 1000
* This rule is not evaluated because the previous rule matched.
Conclusion:
* According to the decision table, the result for a customer with a credit score of 115 and an average balance of 15000 is "B".
NEW QUESTION # 96
U+ Bank wants to offer credit cards only to customers with a low-risk profile. The customers are divided into various risk segments from AAA to CCC. The risk segmentation rules that the business provides use the Age and the customer Credit Score based on the following table. The bank uses a scorecard model to determine the customer Credit Score.
As a decisioning consultant, how do you implement the business requirement?
- A. Add a decision table to a decision strategy and reference it in the scorecard component.
- B. Add the risk segmentation rules in the Results tab of the scorecard rule.
- C. Add three contact policies that correspond to the three risk segments.
- D. Add a decision table to a decision strategy and pass the credit score as the parameter.
Answer: D
NEW QUESTION # 97
U+, a retail bank, runs an audience simulation with only engagement policies in scope (no arbitration) to understand how its engagement policy conditions perform for its sampled customers. The image above shows the results of this simulation. What do the action-level numbers indicate?
- A. Number of times an action was presented as the top offer
- B. Number of customers who qualify for a particular action
- C. Number of customers who receive a particular action as the top action
- D. Number of times an action was presented to customers
Answer: B
Explanation:
Understanding Audience Simulation:
Audience simulations help understand how engagement policies and actions perform for a sample set of customers.
The simulation in question focuses solely on engagement policies without arbitration, meaning it evaluates which actions customers qualify for based on predefined criteria.
Interpreting the Simulation Results:
The numbers shown next to each action represent the count of customers who meet the engagement policy criteria for that action.
This count indicates the number of customers who qualify for each action based on eligibility, applicability, and suitability rules.
Detailed Explanation:
Rewards card (202): 202 customers meet the engagement criteria for the Rewards card.
Rewards Plus card (456): 456 customers meet the engagement criteria for the Rewards Plus card.
Premier Rewards card (25): 25 customers meet the engagement criteria for the Premier Rewards card.
Verification from Pega Documentation:According to the Pega Customer Decision Hub User Guide, running an audience simulation with engagement policies helps identify how many customers qualify for each action based on the policies applied.
NEW QUESTION # 98
Reference module: Creating and understanding decision strategies. In a decision strategy, to use a customer property in an expression, you _____.
- A. prefix the property with the keyword Customer
- B. define the property as a strategy property
- C. define the Customer page in Pages and Classes
- D. use the property as defined without a prefix
Answer: A
Explanation:
* Customer Properties - These are attributes related to the customer, such as demographics, behavior, and engagement history.
* Expression Syntax:
* When defining expressions in decision strategies, customer properties must be prefixed with
"Customer."
* For example, to use the customer's age, you write Customer.Age.
* Steps:
* In the decision strategy, select the component where you need to use the customer property.
* Write the expression using the "Customer" prefix.
NEW QUESTION # 99
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?
- A. Create a decision strategy at the Issue-level.
- B. Set contact limits for both the groups.
- C. Map a real-time container to the Top-level or Issue-level.
- D. Enable an engagement policy for the second group.
Answer: A
NEW QUESTION # 100
Myco, a telco, wants to present their customers with new 5G data plans - the Unlimited plan, the 500GB plan, and the 100GB plan - on their web portal. As a Decisioning Consultant, you want to test how the three new offers will be distributed by running a distribution test that only considers eligibility without arbitration. In this scenario, which report will test this requirement?
- A. Action Distribution Report
- B. Bias Report
- C. Action Priority Report
- D. Channel Report
Answer: A
NEW QUESTION # 101
A strategy designer has created 10 actions in the Sales/Credit Cards group and 10 actions in the Sales/Mortgages group. He would like to import all 10 actions from the Credit Cards group and only two actions from the Mortgage group into one decision strategy. What is the minimum number of Proposition Data components he needs to use in his strategy?
- A. one
- B. two
- C. three
- D. twelve
Answer: C
NEW QUESTION # 102
To reference a customer property in a strategy, you need to prefix the property name with the keyword______________.
- A. No prefix. Use directly the property name.
- B. "Data."
- C. "Customer."
- D. '' .''
Answer: C
Explanation:
Referencing Customer Properties: In Pega decision strategies, customer properties are accessed by prefixing the property name with "Customer." This convention helps in clearly identifying the context of the properties being used.
NEW QUESTION # 103
Using Pega Customer Decision Hub, a mobile company transitions from a one-to-many to a one-to-one marketing approach. The company is introducing a new data plan.
Which two channels can the company use to present the new data plan to a customer? (Choose Two)
- A. Billboard
- B. Chatbot
- C. Retail store
- D. Television
Answer: B,C
NEW QUESTION # 104
DRAG DROP
You are a decisioning consultant responsible for configuring offer prioritization for home loan offers based on the business requirements.
Select each prioritization factor on the left and drag it to the correct condition on the right.
Answer:
Explanation:
NEW QUESTION # 105
U+ Bank, a retail bank, wants to begin promoting credit card offers via email to qualified customers. The business would like to ensure that the outbound run always uses the latest customer information.
What do you configure to implement this requirement?
- A. Select Refresh the audience
- B. Select different audience sample with similar profile
- C. Trigger an external ETL (Extract-Transform-Load) process
- D. Run the starting population segment daily
Answer: A
NEW QUESTION # 106
An outbound run identifies 100 Standard Card offers, 50 on email and 50 on the SMS channel. If the above volume constraint is applied, how many actions will be delivered by the outbound run?
- A. 0
- B. 1
- C. 50 SMSes and 25 emails
- D. 50 emails and 25 SMSes
Answer: A
NEW QUESTION # 107
The U+ Bank marketing department currently promotes various home loan offers to qualified customers. Now, the bank does not want customers to receive more than four promotional emails per quarter, regardless of past responses to that action by the customer.
Which option allows you to implement the business requirement?
- A. Suitability rules
- B. Customer contact limits
- C. Volume constraints
- D. Suppression policies
Answer: B
Explanation:
To ensure that customers do not receive more than four promotional emails per quarter, you can use customer contact limits. This setting allows you to define the maximum number of contacts a customer can receive over a specific period, regardless of their responses to previous actions. By setting this limit, you can prevent overcommunication and enhance customer experience.
NEW QUESTION # 108
A bank developed a scorecard to automate the loan approval process. In the scorecard rule, there is a classification implemented using three score bands: Not Approved, Refer to Manager, and Approved. Which property allows you to use the result of this classification in a decision strategy?
- A. pxSegment
- B. PropertyHasValue
- C. pyOutcome
- D. pyPropensity
Answer: A
NEW QUESTION # 109
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 consultant, you decide to use a decision table and a decision strategy to accomplish this requirement in Pega Customer Decision Hub.
In addition to the credit risk requirement, U+ Bank wants to offer credit cards to customers whose age is greater than 25.
As a best practice, which part of Customer Decision Hub do you access to ensure that credit cards are offered only to customers with age greater than 25?
- A. Extend the decision table: Age > 25
- B. Constraints tab in the Next-Best-Action Designer
- C. Engagement Policy tab in the Next-Best-Action Designer
- D. Add a Filter component in the generated strategy
Answer: C
Explanation:
* Identify the Requirement: U+ Bank wants to offer credit cards only to customers with specific risk segments and also ensure that the age of the customer is greater than 25 years. This involves setting eligibility criteria for credit card offers.
* Understand Engagement Policies: Engagement policies in Pega CDH are used to define rules that govern when specific actions are relevant for a customer. This includes eligibility, applicability, and suitability conditions.
* Access Next-Best-Action Designer: To implement these criteria, navigate to the Next-Best-Action Designer within Pega Customer Decision Hub.
* Engagement Policy Tab:
* Eligibility Criteria: Set the criteria to include customers with an age greater than 25 years.
* Define the other conditions based on Credit Score and Average Balance to segment customers into Good, Fair, Poor, and Very Poor risk categories.
According to the Pega Customer Decision Hub User Guide, the engagement policy tab allows users to define when specific actions or groups of actions are appropriate for customers (Reference:
Pega-Customer-Decision-Hub-User-Guide-85.pdf, Chapter on "Understanding Next-Best-Action Designer engagement policies").
* Implementing the Criteria:
* Navigate to the Engagement Policy tab: This is within the Next-Best-Action Designer.
* Add a New Policy: Create a new engagement policy where you define the eligibility criteria for the credit card offer.
* Set Age Condition: Ensure the age condition (Age > 25) is part of the eligibility criteria.
* Validation:
* Ensure the conditions are tested thoroughly to verify that the credit card offers are only presented to customers meeting the set criteria.
* Additional Resources:
* For detailed steps on configuring engagement policies, refer to the Pega documentation on
"Configuring engagement policies for actions" (Reference:
Pega-Customer-Decision-Hub-User-Guide-85.pdf).
Conclusion: The best practice to ensure that credit cards are offered only to customers with age greater than
25 is to use the Engagement Policy tab in the Next-Best-Action Designer, where you can set the eligibility conditions appropriately.
NEW QUESTION # 110
When a customer is offered an action that they already accepted, this is because_________.
- A. the strategy is not customized to exclude previously accepted offers
- B. there are no suppression rules defined
- C. the actions are filtered based on eligibility
- D. the customer intent was captured incorrectly
Answer: A
Explanation:
Identify the issue: When a customer receives an offer they have already accepted, it suggests that the decision strategy did not consider previous interactions.
Check strategy customization: Strategies in Pega CDH can be customized to include rules that prevent the same offer from being presented again.
Confirm the exclusion of previous offers: Specifically, you need to ensure that there is a suppression rule or a logic to check the Interaction History to exclude previously accepted offers.
Reference: Refer to the section on "Next-Best-Action Designer constraints" and "Engagement policies" in the Pega Customer Decision Hub User Guide. These sections explain how to configure rules to prevent repetitive offers.
NEW QUESTION # 111
Reference module: Analyzing the effect of business changes using Pega Scenario Planner U+ Bank, a retail bank, completed an implementation to present Credit Card offers to customers on their self-service portals. You want to estimate the business value that the subsequent next-best-action run creates using the selected configuration. Which simulation do you run to get the required information?
- A. Pega Scenario Planner
- B. Pega Value Finder
- C. Distribution Test
- D. Audience Simulation
Answer: A
NEW QUESTION # 112
An outbound run identifies 100 Standard Card offers, 50 on email and 50 on the SMS channel. If the above volume constraint is applied, how many actions will be delivered by the outbound run?
- A. 0
- B. 1
- C. 50 SMSes and 25 emails
- D. 50 emails and 25 SMSes
Answer: A
NEW QUESTION # 113
U+ Bank wants to offer a 10% discount for customers whose CLV value is higher than 400. Which strategy component should you use to meet the new requirement?
- A. Filter
- B. Prioritize
- C. Set Property
- D. Group By
Answer: A
Explanation:
* Customer Lifetime Value (CLV) - The bank wants to offer a discount based on the customer's CLV.
* Filter Component - The Filter component is used in decision strategies to include or exclude actions
* based on specific criteria, such as CLV.
* Implementation:
* Add a Filter component in the decision strategy.
* Configure the filter to check if the CLV value is greater than 400.
* If true, proceed with the 10% discount offer.
NEW QUESTION # 114
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