PEGACPDC88V1 Certified Pega Decisioning Consultant 8.8 V1 Questions and Answers

Using the decision table, you can find the label for a customer with a credit score of 240 and an average balance of 35000 by following these steps:

• Start from the top row and check if the customer’s credit score is less than 150. If yes, then the label is Very Poor. If no, then move to the next row.
• Check if the customer’s credit score is less than 175 and their average balance is less than 25000. If yes, then the label is Poor. If no, then move to the next row.
• Check if the customer’s credit score is less than 200 and their average balance is less than 50000. If yes, then the label is Fair. If no, then move to the next row.
• Check if the customer’s credit score is less than 250 and their average balance is less than 75000. If yes, then the label is Good. If no, then move to the last row.
• The last row applies to all other cases that do not match any of the previous conditions. The label for this row is Very Poor.

In this case, the customer’s credit score is not less than 150, so the first row does not apply. The customer’s credit score is less than 175, but their average balance is not less than 25000, so the second row does not apply either. The customer’s credit score is not less than 200, so the third row does not apply. The customer’s credit score is less than 250 and their average balance is less than 75000, so the fourth row applies. Therefore, the label for this customer is Poor.

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To present offers from the two groups, you must map a real-time container to the Top-level or Issue-level. A real-time container is a configuration that defines how to deliver offers and treatments to a specific channel, such as a website or a mobile app. By mapping a real-time container to the Top-level or Issue-level, you can enable all the offers under that level to be available for delivery through that channel. Verified References: Pega Academy - Decisioning Consultant - Configuring real-time containers

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]

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

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 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 customer might receive an action that they already accepted if the volume constraint for that action is not configured to exclude previously accepted offers. This option can be enabled by selecting the Exclude previously accepted actions checkbox in the volume constraint configuration. The action suitability conditions are used to determine whether an action is suitable for a customer based on their propensity, priority, or other criteria, not based on their previous responses. The suppression rules are used to exclude customers from receiving an action based on certain conditions, such as opt-out preferences or recent purchases, not based on their previous responses. The actions are filtered based on eligibility before applying the volume constraints, so this option does not explain why a customer might receive an action that they already accepted. Verified References: Certified Pega Decisioning Consultant | Pega Academy, Volume constraints

According to the best practice, a next-best-action designer should modify the decision strategy in Customer Decision Hub, because the decision strategy is part of the next-best-action framework that defines how to select and prioritize propositions for each customer. The 1:1 Operations Manager portal is used to manage the engagement policies and propositions, not the decision strategies. Verified References: Pega Decisioning Consultant | Pega Academy

The score calculation is independent of the strategy and no change is required. When you use a scorecard component in a decision strategy, you only need to specify the name of the scorecard rule and the output property that will store the score value. The scorecard rule itself defines how the score is calculated based on the input properties and factors. Therefore, if you update the scorecard rule to include a new property in the calculation, you do not need to make any changes in the decision strategy for the updated scorecard to take effect. Verified References: [Pega Academy - Decisioning Consultant - Using scorecards]

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]

CUST-05 receives the Diamond card offer because it is the only action that does not exceed the volume constraint for the email channel. The Silver card offer has already reached its limit of 2 emails per day, so it is not eligible for CUST-05. The volume constraint mode Return any action that does not exceed means that any action that meets the eligibility and suitability criteria and does not violate the volume constraint will be returned, even if there are other actions with higher priority or propensity. Verified References: Certified Pega Decisioning Consultant | Pega Academy, Volume constraints

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]

To output the most profitable shoe, you need to add a Prioritize component in the blank space. A Prioritize component allows you to rank actions based on one or more properties. In this case, you can rank the shoes based on the Profit property and select the highest ranked shoe as the output. Verified References: Pega Academy - Decisioning Consultant - Prioritizing actions