PEGACPDC88V1 Certified Pega Decisioning Consultant 8.8 V1 Questions and Answers

To select the best offer from both groups based on customer behavior, you need to ensure that the propensity is enabled in Arbitration tab. Propensity is a measure of how likely a customer is to accept an offer, based on their past behavior and profile. By enabling propensity in Arbitration tab, you can compare the propensities of different offers across groups and select the one with the highest propensity as the next best action. Verified References:  Pega Academy - Decisioning Consultant - Arbitrating actions

When you create a new trigger in the Next-Best-Action Designer, Pega Customer Decision Hub automatically generates a decision strategy for that trigger and channel. You do not need to create or modify any strategies manually. Verified References:  Pega Academy - Decisioning Consultant - Creating triggers

Suppression rules are used to prevent customers from seeing offers that are not relevant or appropriate for them. For example, if a customer already has a higher value card, they should not see a lower value card offer. Therefore, suppression rules are the most likely condition that prevents Anna from seeing the new Rewards card offer. Verified References: [Pega Decisioning Consultant | Pega Academy]

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

Pega Customer Decision Hub always selects and prioritizes the most relevant and valuable action for each customer at any given moment, regardless of whether the action is part of a journey or not. A journey is a way to group and organize actions that are related to a common business objective or customer need, but it does not override the Next-Best-Action strategy that determines the best action for each customer. Therefore, if a customer receives an offer that is not included in any journey, it means that the offer is more suitable and beneficial for the customer than any other offer in the journey. Verified References:  Pega Decisioning Consultant | Pega Academy

According to the best practice, a single change request should be created in the 1:1 Operations Manager portal, because both changes are related to the engagement policies and propositions that are managed in this portal. The Pega Customer Decision Hub portal is used to design and test the decision strategies, not the engagement policies and propositions. Verified References:  Pega Decisioning Consultant | Pega Academy

The business weight is a parameter that allows you to manually adjust the priority of an offer based on your business objectives and preferences. The business weight is multiplied by the business value and the propensity to calculate the final priority score of an offer. A higher business weight means a higher priority score, making the offer more likely to be selected and presented to the customer. Therefore, if you want to boost an offer, you can increase its business weight. Verified References:  Pega Decisioning Consultant | Pega Academy

The Next-Best-Action strategy is a customer-centric approach that aims to deliver the most relevant and valuable proposition for each customer at any given moment. You can use the Next-Best-Action strategy to address various business issues that involve customer interactions, such as service, retention, and collections. Service is the process of providing assistance and support to customers who have questions or problems. Retention is the process of preventing customers from leaving or switching to competitors. Collections is the process of recovering unpaid debts from customers who are delinquent or defaulting on their obligations. These are all business issues that can benefit from using the Next-Best-Action strategy. Verified References: [Pega Decisioning Consultant | Pega Academy]

The scorecard model determines the customer credit score based on various factors, such as income, expenses, assets, liabilities, etc. The scorecard model has a Results tab where you can define the cutoff values for different segments based on the credit score. To change the threshold value for the USD2000 credit limit from < 175 to < 200, you need to change the cutoff value in the Results tab of the scorecard model. Changing the cutoff value in the scorecard decision component, changing the condition in the strategy, or mapping the score value in the decision strategy will not affect the credit score calculation or segmentation. 

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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.

Paul cannot see the Reward card offer because he rejected other credit card offers twice on the web channel and once in contact center in the past 15 days. This triggers the first contact policy that suppresses a group of credit card offers for 30 days if any credit card offer is rejected three times in any channel in the past 15 days. The Reward card offer is part of the credit card group, so it is suppressed for Paul for 30 days. The second contact policy that suppresses the Reward card offer for 7 days if it is rejected twice in any channel in the last 7 days does not apply because Paul did not reject the Reward card offer twice in any channel in the last 7 days. Verified References: [Certified Pega Decisioning Consultant | Pega Academy] , Suppression policies system Following is the description of the image that was sent with question no:5:

This is a screenshot of a table with four columns and two rows.

The table has a header row with white text on a blue background.

The header row reads “Constraint name”, “Constraint mode”, “Constraint value”, and “Channel”.

The second row has black text on a white background.

The second row reads “Standard card”, “Return any action that does not exceed”, “100”, and “Daily”.

The table has a gray border and a light blue background.