[Jan 13, 2024] PEGACPDS88V1 Practice Exam Dumps - 99% Marks In Pegasystems Exam
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NEW QUESTION # 24
Configuring an adaptive model involves selecting the potential predictors. How many potential predictors are recommended for an adaptive model?
- A. At least 100 fields to reach an acceptable level of model performance
- B. All fields that have been predictive in the past
- C. All available uncorrected fields
- D. Up to 100 fields to limit the impact on model speed
Answer: D
Explanation:
Explanation
Up to 100 fields to limit the impact on model speed Reference:
When configuring an adaptive model, it is recommended to select up to 100 potential predictors to limit the impact on model speed.
NEW QUESTION # 25
As a data scientist, you are tasked with configuring two predictions that are driven by an adaptive model: one for an inbound channel and one for an outbound channel. To which setting do you need to pay extra attention?
- A. Predictor fields
- B. Response timeout
- C. Adaptive model
- D. Control group
Answer: C
Explanation:
Explanation
As a data scientist, if you are tasked with configuring two predictions that are driven by an adaptive model, you need to pay extra attention to adaptive model settings.
NEW QUESTION # 26
To build a predictive model, use____________.
- A. Pega Decision Management
- B. Pega Marketing
- C. Pega Customer Service
- D. Pega Platform
Answer: A
Explanation:
Explanation
Pega Decision Management Reference:
To build a predictive model, use Pega Decision Management. Pega Decision Management is a tool that enables businesses to make informed decisions based on data and analytics.
NEW QUESTION # 27
What are the most important aspects taken into consideration when determining the Next-Best-Action?
- A. Network bandwidth and call duration
- B. Business objectives and customer needs
- C. Product discounts and business profitability
- D. Market trends and customer satisfaction
Answer: B
Explanation:
Explanation
The most important aspects taken into consideration when determining the Next-Best-Action are business objectives and customer needs. Business objectives reflect the goals and priorities of the organization, such as increasing revenue, reducing costs, or managing risk. Customer needs reflect the preferences and expectations of the customers, such as their interests, intents, or life events. References:
https://academy.pega.com/module/one-one-customer-engagement/topic/next-best-action-designer
NEW QUESTION # 28
Which adaptive model output is automatically mapped to a strategy property?
- A. Score
- B. Propensity
- C. Evidence
- D. Performance
Answer: B
Explanation:
Explanation
Propensity is the adaptive model output that is automatically mapped to a strategy property. Propensity is the likelihood of a positive response for a given action and predictor profile. It ranges from 0 to 100. References:
https://community.pega.com/sites/default/files/help_v82/procomhelpmain.htm#rule-/rule-decision-/rule-decision
NEW QUESTION # 29
The Predictive Model Markup Language (PMML) allows for predictive models to
- A. Be easily shared between applications
- B. Use the same modeling process
- C. Be developed faster
- D. Perform better
Answer: A
Explanation:
Explanation
The Predictive Model Markup Language (PMML) allows for predictive models to be easily shared between applications. PMML is a standard XML format that describes the input parameters, output score, and mathematical formulas of predictive models. PMML enables interoperability between different tools and platforms that support PMML, such as Pega Customer Decision Hub. References:
https://community.pega.com/sites/default/files/help_v82/procomhelpmain.htm#data-/data-predictivemodel-/data-
NEW QUESTION # 30
Evidence an assessment of its viability, the Adaptive Model produces three outputs: Propensity, Performance and what is evidence in the context of an Adaptive Model? Performance and what is evidence in the context of an Adaptive Model?
- A. The number of customers who have responded to the modeled offer
- B. The number of customers who exhibited statistically similar behavior
- C. The likelihood of a statistically similar behavior
- D. The number of statistical bins used to evaluate the response
Answer: B
Explanation:
Explanation
Evidence is the number of customers who exhibited statistically similar behavior to the current customer and responded to the modeled offer. It indicates how reliable the propensity score is based on the available data.
References:
https://academy.pega.com/module/predicting-customer-behavior-using-real-time-data-archived/topic/adaptive-m
NEW QUESTION # 31
Acquiring new customers can be more costly than retaining active customers. U+ Bank uses Pega Customer Decision Hub for its customer engagement and wants to reduce the churn rate by identifying high churn risk customers and making them a retention offer.
To meet this requirement, which two artifacts created by a data scientist allow the NBA specialist to implement the decision strategy? (Choose Two)
- A. A predictive model
- B. A control group
- C. An adaptive model
- D. A prediction
Answer: A,B
Explanation:
Explanation
According to the Data Scientist Student Guide1, page 18, the correct answer is B. A predictive model and C. A control group. A predictive model is a mathematical representation of a real-world process that can be used to predict an outcome based on input data. A control group is a subset of customers who are not exposed to a treatment (such as an offer) and are used to measure the effectiveness of the treatment by comparing their behavior with the treated group.
NEW QUESTION # 32
How does a prediction help in proactive retention?
- A. The prediction predicts the customer's churn risk
- B. The prediction suggests the best offer
- C. The prediction selects the next best action
- D. The prediction identifies successful offers in past interactions
Answer: A
Explanation:
Explanation
A prediction helps in proactive retention by predicting the customer's churn risk. A prediction is an estimate of the likelihood of a future outcome based on historical data and statistical models. A prediction can help identify customers who are at risk of leaving and target them with appropriate actions to retain them.
References:
https://community.pega.com/sites/default/files/help_v82/procomhelpmain.htm#decisioning-/decisioning-strategi
NEW QUESTION # 33
U+ Bank introduces a new credit card that has no historical customer behavior data. U+ Bank wants to offer this credit card on the personalized web portal. Given the scenario, which rule type must you use?
- A. Pega machine learning model
- B. Adaptive model
- C. When rule
- D. Decision table
Answer: B
Explanation:
Explanation
Given the scenario where U+ Bank introduces a new credit card that has no historical customer behavior data and wants to offer this credit card on the personalized web portal, you must use an adaptive model.
NEW QUESTION # 34
You are the Decisioning Consultant on an Al-powered one-to-one Customer Engagement implementation project. You are asked to design the Next-Best-Action prioritization expression that balances the customer needs with the business objectives.
What factors do you consider in the prioritization expression?
- A. product eligibility rules
- B. business levers
- C. product compatibility rules
- D. customer contact rules
Answer: B
Explanation:
Explanation
Business levers are factors that you consider in the prioritization expression to balance the customer needs with the business objectives. They can include revenue, cost, risk, retention, satisfaction, or any other custom metric that reflects the value of an action. References:
https://academy.pega.com/module/creating-and-understanding-decision-strategies-archived/topic/using-business-
NEW QUESTION # 35
Pega Customer Decision Hub uses the P*C*V*L arbitration formula to select the next best action for each customer. Which description best describes the purpose of the formula?
- A. To balance customer needs with business objectives
- B. To provide insight into business processes
- C. To ensure that the customer is always given the best offer, regardless of the business objective
- D. To ensure that every customer receives the same action
Answer: A
Explanation:
Explanation
Pega Customer Decision Hub uses the PCV*L arbitration formula to select the next best action for each customer. The purpose of the formula is to balance customer needs with business objectives.
NEW QUESTION # 36
A company wants to simulate decisions that requires large amounts of data. However, the organisation's live data is inaccessible. Your advice is to use a Monte Carlo data set. The Monte Carlo method
- A. makes the organization's live data accessible
- B. combines external data sets into a larger data set
- C. enables the company to generate random data for most of its application needs
- D. generates data that the company can use as input for adaptive decisioning
Answer: D
Explanation:
Explanation
The Monte Carlo method enables the company to generate data that simulates customer behavior and can be used as input for adaptive decisioning. The generated data is based on predefined probabilities and distributions that reflect realistic scenarios. References:
https://academy.pega.com/module/demonstrating-adaptive-learning-archived/topic/creating-monte-carlo-data-set
NEW QUESTION # 37
To enable an assessment of its reliability the adaptive model produces four outputs: propensity,performance, evidence and positives.
The Performance of an adaptive model that has not collected any evidence yet is______.
- A. 0
- B. 1
- C. 2
- D. 3
Answer: A
Explanation:
Explanation
The performance of an adaptive model that has not collected any evidence yet is 50. This means that the model is not confident about its predictions and assigns equal probability to all actions. References:
https://community.pega.com/sites/default/files/help_v82/procomhelpmain.htm#rule-/rule-decision-/rule-decision
NEW QUESTION # 38
Which decision component enables you to use a PMML model?
- A. Adaptive Model
- B. Third-party Model
- C. PMML Model
- D. Predictive Model
Answer: D
Explanation:
Explanation
The decision component that enables you to use a PMML model is Predictive Model. Predictive Model is a component that references a predictive model rule that defines the input parameters and the output score of the model. You can use a predictive model component to reference a PMML model that is imported from a third-party tool and use it in your decision strategy. References:
https://community.pega.com/sites/default/files/help_v82/procomhelpmain.htm#rule-/rule-decision-/rule-decision
NEW QUESTION # 39
The outcome of a scoring model indicates the likely
- A. claim value of a health insurance
- B. response to an offer
- C. write-off value of an arrears case
- D. period in which a spare part has to be replaced
Answer: B
Explanation:
Explanation
The outcome of a scoring model indicates the likely response to an offer that is presented to a customer. For example, a scoring model can predict if a customer will accept, reject, or defer an offer for a credit card upgrade. References: https://academy.pega.com/module/predictive-analytics/topic/using-scoring-models
NEW QUESTION # 40
When building a predictive model, the Data Analysis stage is where you
- A. determine the output field
- B. create data samples
- C. group predictors
- D. select the input data
Answer: D
Explanation:
Explanation
When building a predictive model, the Data Analysis stage is where you select the input data that will be used to train and test the model. You can also filter, group, or transform the input data to improve its quality and relevance. References: https://academy.pega.com/module/predictive-analytics/topic/analyzing-data
NEW QUESTION # 41
U+ Bank promotes credit card offers on its website and uses Pega Customer Decision Hub to personalize the offer for every customer. Now, the bank wants to lower the number of customers that leave the bank by showing a proactive retention offer to high churn risk customers instead. As an NBA analyst, you are tasked with creating a new applicability setting to comply with the new business rule. Which business issue or issues do you modify?
- A. The Sales issue
- B. No modification is required
- C. The Retention issue
- D. The Sales issue and the Retention issue
Answer: C
Explanation:
Explanation
To comply with the new business rule of showing a proactive retention offer to high churn risk customers, you should modify the Retention issue.
NEW QUESTION # 42
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