PEGACPDC25V1 Exam Dumps - Pegasystems Pega Decisioning Consultant Questions and Answers

The always-on outbound customer engagement paradigm relies on AI to select the best action for each customer at any given time, based on their profile, context, and behavior. You do not need to create separate segments or schedules for different offers or timings. You can configure the primary schedule to run daily and let the AI choose the best action based on engagement policies, such as contact policies, eligibility rules, suitability rules, and arbitration. The AI will also learn from the customer responses and optimize the action selection over time.

Propensity is the name of the property that the system computes automatically when you use an Adaptive Model decision component. Propensity is a measure of how likely a customer is to accept an action, based on their past behavior and profile. An Adaptive Model component uses machine learning to calculate the propensity for each action and store it in a property with the same name as the action. Verified References: Pega Academy - Decisioning Consultant - Using adaptive models

To access a property from an unconnected component, you use the component-dot-property construct. For example, if you want to access the property .Rank from an unconnected component named ActionRanking, you use ActionRanking.Rank. Verified References: Pega Academy - Decisioning Consultant - Accessing properties from unconnected components

To implement this requirement, you need to create an external email treatment and use an external tool to design the email. An external email treatment is a type of treatment that allows you to use a third-party email service provider to send emails to your customers. You can configure the external email treatment with the name of the provider, the authentication details, and the template ID that corresponds to the email content that you design using an external tool. This way, you can leverage your existing tools and processes for sending emails, while still using Customer Decision Hub to select the best actions and treatments for your customers. Verified References: Pega Academy - Decisioning Consultant - Creating external treatments

Next-Best-Action is a type of decision that involves selecting and prioritizing the most appropriate proposition for each customer at any given moment. Next-Best-Action can be applied to decisions that require customer-centricity, personalization, and contextualization. Determining if a borrower gets a loan is an example of such a decision, as it depends on the customer’s attributes, behaviors, preferences, and needs. The other options are examples of decisions that are not related to customer interactions, but rather to operational or analytical processes. Verified References: [Pega Decisioning Consultant | Pega Academy]