Free PEGACPDS88V1 Exam Braindumps certification guide Q&A [Q24-Q38] – Unlimited Lifetime Access Free Exams PDF

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Free PEGACPDS88V1 Exam Braindumps certification guide Q&A

PEGACPDS88V1 Certification Overview Latest PEGACPDS88V1 PDF Dumps

Q24. When implementing Next-Best-Action, the Customer Lifetime Value Threshold is typically used to_________.

prioritize high value propositions

prioritize customers

determine if the customer is eligible

calculate the customer’s lifetime value

Explanation
The Customer Lifetime Value Threshold is typically used to prioritize customers based on their expected long-term value to the business. Customers who have a higher lifetime value than the threshold are considered high-value customers and receive more personalized and relevant offers. References:
https://academy.pega.com/module/one-one-customer-engagement/topic/next-best-action-designer

Q25. What is the difference between predictive and adaptive analytics?

Predictive models can predict a continuous value.

Predictive models predict customer behavior.

Adaptive models use the customer data as predict*

Predictive models have evidence.

Explanation
The difference between predictive and adaptive analytics is that adaptive models use the customer data as predictors, while predictive models use the customer data as outcomes. Adaptive models learn from real-time customer interactions and update their predictions accordingly. Predictive models use historical customer data to train and validate their predictions. References:
https://academy.pega.com/module/predicting-customer-behavior-using-real-time-data-archived/topic/adaptive-m

Q26. Adaptive models can start to learn without historical evidence. What is the starting propensity of every action?

0.5

Explanation
Adaptive models can start to learn without historical evidence. The starting propensity of every action is 0.5.

Q27. As a data scientist, you are tasked with creating a new prediction that estimates a customers’ likelihood to leave the business in the near future. The NBA analyst wants to move forward and use the prediction in Pega Customer Decision Hub to test the application. To unblock the NBA specialist, which task do you prioritize?

Create the prediction

Create the customer data model

Create a placeholder scorecard to drive the prediction

Create the predictive model that drives the prediction

Explanation
To unblock the NBA specialist, as a data scientist, you should prioritize creating the predictive model that drives the prediction.

Q28. Through analysis of customer lifecycles, Next-Best-Action

anticipates retention issues

provides future sales reports

provides fulfillment services

identifies global sales targets

Explanation
Through analysis of customer lifecycles, Next-Best-Action anticipates retention issues and takes proactive actions to prevent customer churn. It uses predictive analytics to identify customers who are at risk of leaving and offers them incentives or solutions to retain them. References:
https://academy.pega.com/module/one-one-customer-engagement/topic/proactive-retention

Q29. What two tasks does a system architect need to perform to export historical data? (Choose Two)

Switch to a resilient repository

Set the sample percentage for positive and negative outcomes

Export the data set

Validate the predictors used by the adaptive models

Create a data set

Explanation
Two tasks that a system architect needs to perform to export historical data are export the data set and create a data set.

Q30. Which statement about predictive models is true?

You need past experience to create a predictive model.

They need unstructured big data.

They are always associated with a proposition.

They need to be specified in a data attribute.

Q31. As a data scientist, you want to use a predictive model to detect potential churn for a telecom company.
Which three options do you have? (Choose Three)

Import a third party PMML model

Use a Google ML model

Create a Text extraction model

Create an adaptive self-learning model

Use Pega machine learning to build a model

Use a machine learning service

* Import a third party PMML model : PMML stands for Predictive Model Markup Language, which is an XML-based standard for representing predictive models. You can import a PMML model that was created by another tool or platform into Pega and use it in your strategies.
* Create an adaptive self-learning model : An adaptive model is a type of predictive model that learns from customer responses and adapts its predictions over time. You can create an adaptive model in Pega and configure its parameters, such as learning rate, decay rate, and performance goal.
* Use Pega machine learning to build a model1: Pega machine learning is a feature that allows you to build predictive models using various algorithms, such as decision trees, logistic regression, neural networks, and random forests. You can use Pega machine learning to build a model from your data and evaluate its performance.

Q32. From two churn models with the similar performance, we chose the one the_____

Highest churn rate

Highest number of predictors

Most evidence

Fewest number of predictors

Explanation
The principle of parsimony states that from two models with similar performance, we choose the one with the fewest number of predictors. This is because a simpler model is easier to understand, maintain, and deploy.
References: https://academy.pega.com/module/predictive-analytics/topic/evaluating-predictive-models

Q33. U+ Telecom wants to engage in proactive retention to reduce churn. As a data scientist, you create a prediction that calculates the probability that a client is likely to cancel a subscription. What type of prediction do you create?

Case management_____

Customer Decision Hub

Text analytics

Explanation
As a data scientist, you create a prediction that calculates the probability that a client is likely to cancel a subscription. The type of prediction you create is Customer Decision Hub.

Q34. 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?

one

twelve

three

two

Explanation
If a strategy designer has created 10 actions in the Sales/Credit Cards group and 10 actions in the Sales/Mortgages group and would like to import all 10 actions from the Credit Cards group and only two actions from the Mortgage group into one decision strategy, the minimum number of Proposition Data components he needs to use in his strategy is three.

Q35. In a strategy defined in the “Retension” issue and the “X-Sell” group, you can import________

Actions from all groups under the “Retention” issue

Actions from “X-Sell” group

Actions from the “Sales” issue

All active actions

Explanation
According to the Pega Academy1, a strategy is a unit of reasoning that defines how to select an action for a customer. A strategy can be defined in different issues and groups, which are categories that help organize actions. An issue represents a business goal (such as retention or sales), and a group represents a subcategory of an issue (such as cross-sell or up-sell).
In a strategy defined in the “Retention” issue and the “X-Sell” group, you can import actions from all groups under the “Retention” issue1. This allows you to use actions that are relevant to your business goal and compare them with other actions in the same issue.

Q36. An adaptive model instance is created when you________

Execute a strategy containing the adaptive model component

Open the Adaptive model management landing page

Restart the Adaptive Decision Manager Service

Save the Adaptive model rule

Explanation
An adaptive model instance is created when you execute a strategy containing the adaptive model component.
The adaptive model component references an adaptive model rule that defines the predictors and the outcome of the model. The adaptive model instance stores the data and the statistics of the model for a specific context and action. References:
https://community.pega.com/sites/default/files/help_v82/procomhelpmain.htm#rule-/rule-decision-/rule-decision

Q37. A contact center application recommends relevant actions for each customer. The business team wants to know the possible ways in which these actions can be ordered so that the contact center agent can discuss one proposition at a time, starting from the top.
As a strategy designer, what are your two options if you use a Prioritize component to order the actions?
(Choose Two)

In a random order

In alphabetical order based on the action name

In descending order based on a numerical value

In ascending order based on a numerical value

Explanation
The prioritize component is used to order actions based on a numerical value, such as priority, propensity, or custom expression. You can choose to sort the actions in descending or ascending order. References:
https://academy.pega.com/module/creating-and-understanding-decision-strategies-archived/topic/prioritizing-act

Q38. An online store is interested in increasing its revenues from cross-selling and wants to predict the acceptance rate of the offers presented on their website. A customer’s propensity to accept an offer increases when_________.

Similar offers were rejected by the customer

The offer was rejected by similar customers

Similar offers were accepted by the customer

The offer was accepted by similar customers

Explanation
This is because a customer’s propensity to accept an offer depends on their past behavior and preferences. If a customer has accepted similar offers in the past, they are more likely to accept a new offer that matches their interests
https://academy.pega.com/sites/default/files/media/documents/2020-12/Mission20301-2-EN-StudentGuide.pdf

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Pegasystems PEGACPDS88V1 certification exam is designed for professionals who are interested in validating their expertise in the field of data science using Pega platforms. Certified Pega Data Scientist 88V1 certification exam assesses the candidate’s ability to use data science concepts and techniques to solve business problems using Pega’s predictive analytics tools. Passing the PEGACPDS88V1 exam indicates that the candidate has a deep understanding of data science and can effectively apply it to real-world scenarios.

Pegasystems PEGACPDS88V1 certification exam is targeted towards data scientists who want to validate their skills and demonstrate their expertise in using the Pega platform for data science. PEGACPDS88V1 exam is ideal for professionals who are already working in the data science field and want to enhance their skills and improve their career prospects.

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