Pegasystems PEGACPDC88V1 Dumps

A priority communication is a type of outbound interaction that allows you to send urgent messages to customers that are not related to any specific offer or proposition. You can use priority communications to inform customers about important events or changes that affect their relationship with your organization. In this case, the bank wants to share the new temporary contact details with all customers over an SMS, so creating a priority communication is the best option. Verified References: [Pega Decisioning Consultant | Pega Academy]

To introduce a new group of offers called Tablets for all customers, you need to create valid actions that represent propositions that you want to present to your customers. In this case, two valid actions are Netflix subscription for 12 months and 5% discount on the price. These are examples of benefits or incentives that can attract customers to buy tablets from MyCo. Tablet serial number and tablet operating system are not valid actions because they are not propositions that can be offered to customers; they are attributes or features of the tablets themselves. Verified References: Pega Academy - Decisioning Consultant - Creating actions and treatments

To implement this requirement, you need to select the Refresh the audience checkbox in the outbound run configuration. This option allows you to refresh the audience data before each run by executing a data flow that reads from your customer data source and updates your customer data set. This way, you can ensure that the outbound run always uses the latest customer information available in your system. Verified References: Pega Academy - Decisioning Consultant - Configuring outbound runs

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

A dotted line from a “Group By” component to a “Filter” component means that a property from the “Group By” is referenced by the “Filter” component. For example, if you group customers by age and then filter them by average spending, you need to reference a property from the “Group By” component, such as .pxSegment, in the “Filter” component. A dotted line does not indicate a one-to-one relationship, an evaluation order, or a copying of information between components

To implement this requirement, you need to select the Refresh the audience checkbox in the outbound run configuration. This option allows you to refresh the audience data before each run by executing a data flow that reads from your customer data source and updates your customer data set. This way, you can ensure that the outbound run always uses the latest customer information available in your system. Verified References: Pega Academy - Decisioning Consultant - Configuring outbound runs

To implement this requirement, you need to create an action and the associated web treatment, a real-time container, and a business structure. An action is a proposition that you want to present to a customer, such as a credit card offer. A treatment is the way you present the action to a customer, such as an image or a text message. A real-time container is a configuration that defines how to deliver actions and treatments to a specific channel, such as a website or a mobile app. A business structure is a hierarchy of business groups and business issues that organizes actions into meaningful categories. Verified References: Pega Academy - Decisioning Consultant - Creating actions and treatments, Pega Academy - Decisioning Consultant - Configuring real-time containers, [Pega Academy - Decisioning Consultant - Defining business structure]

The outbound run delivers 75 emails and 25 SMSes for the Standard card offer because the volume constraint is set to limit the number of actions per channel per day. The email channel has a limit of 75 actions per day, so all 75 email offers are delivered. The SMS channel has a limit of 25 actions per day, so only 25 SMS offers are delivered. The remaining 50 SMS offers are not delivered because they exceed the volume constraint.

The prioritization expression is a formula that calculates the priority score of each offer for each customer, based on various factors that reflect the customer needs and the business objectives. One of the most important factors is the predicted customer behavior, which is measured by the propensity. The propensity is a value that indicates how likely a customer is to accept an offer, based on their attributes and behaviors. The propensity is calculated by using predictive analytics models that learn from historical data and feedback. The higher the propensity, the higher the priority score, making the offer more relevant and valuable for the customer. Verified References: [Pega Decisioning Consultant | Pega Academy]

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]

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 implement this requirement, you need to configure a dynamic template in Customer Decision Hub. A dynamic template is a type of template that allows you to define a common action flow pattern for a group of actions that share similar characteristics, such as channel, issue, or group. You can specify which properties and components are required for each action in the group, and how they are mapped to the action flow template. This way, you can reuse the same action flow template for all the credit card actions, while still allowing some variations in their content and configuration. Verified References: Pega Academy - Decisioning Consultant - Creating dynamic templates

A suppression policy allows you to define conditions that prevent customers from receiving an action or a group of actions. You can use a suppression policy to implement the requirement that customers do not see home loan offers on their account page if they have already received three home loan offers in the last two weeks. You can configure the suppression policy to suppress the home loan group based on the number of times the customer received any action from that group in the past 14 days. Applicability rules are used to determine whether an action is relevant for a customer based on their profile or context, not based on the number of times they received an action. Customer contact limits are used to limit the number of times a customer can be contacted per channel per time period, not based on the number of times they received an action. Volume constraints are used to limit the number of times an action is presented to customers across one or more channels, not based on the number of times they received an action. Verified References: [Certified Pega Decisioning Consultant | Pega Academy], Suppression policies

An engagement policy condition is a rule that determines whether a customer is eligible, applicable, or suitable for an offer. You can use engagement policy conditions to filter customers based on their attributes or behaviors. In this case, the bank wants to offer a Gold credit card to customers who have an annual income of more than USD150000, so creating an engagement policy condition based on the income attribute is the best option. Verified References: [Pega Decisioning Consultant | Pega Academy]