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Pegasystems PEGACPDS88V1 is a certification exam designed for individuals who want to demonstrate their expertise in data science and Pega technologies. Pega is a leading provider of business process management (BPM) and customer relationship management (CRM) software solutions. With this certification, individuals can demonstrate their ability to use Pega's data science tools to solve complex business problems.
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The Pegasystems PEGACPDS88V1 exam is an essential certification for data scientists who want to demonstrate their proficiency in using Pega's platform and tools. The certification is globally recognized and demonstrates a candidate's expertise in solving complex business problems using Pega tools and techniques. Candidates can enroll in Pega's training courses to gain the necessary skills and knowledge to pass the exam and advance their careers in data science.
NEW QUESTION # 91
How does a prediction help in proactive retention?
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 # 92
When implementing Next-Best-Action, the Customer Lifetime Value Threshold is typically used to_________.
Answer: B
Explanation:
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
NEW QUESTION # 93
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?
Answer: C
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 # 94
What is the difference between predictive and adaptive analytics?
Answer: D
Explanation:
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
NEW QUESTION # 95
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?
Answer: D
Explanation:
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.
NEW QUESTION # 96
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