PEGAPCDC87V1 Exam Dumps - Pegasystems Pega Decisioning Consultant Questions and Answers

In the always-on outbound customer engagement paradigm, leveraging AI and continuous decisioning is crucial:

AI-Driven Decisioning:

Step 1: Configure the primary schedule to run daily, allowing the AI engine to continuously evaluate and select the best action for each customer.

Step 2: The AI considers engagement policies, customer behavior, and contextual data to determine the most relevant action.

Benefits of Always-On Engagement:

Continuous evaluation of customer interactions ensures that the actions presented are timely and contextually relevant.

It allows for dynamic adjustment of offers based on real-time data and customer responses.

Implementation Steps:

Step 1: In Next-Best-Action Designer, set up a primary schedule to run daily.

Step 2: Define engagement policies and configure AI models to select actions based on customer interactions and preferences.

Step 3: Allow the AI to decide whether to resend the original offer or present a new offer based on the customer’s response or lack thereof.

Example:

If the customer ignores the first email, the AI might decide to send a reminder email or a different offer based on updated engagement data and policy rules.

References:

Pega-Customer-Decision-Hub-User-Guide-85.pdf: "Configuring a recurring schedule for Next-Best-Action" section.

Pega documentation on "Using AI in decisioning".

To update the cashback offer to be presented through a new channel (SMS) and to update the suitability condition, you need to perform two main tasks: adding a new treatment and editing the engagement policy.

Add a New Treatment:

Step 1: Navigate to the "Actions" section in the Pega Customer Decision Hub.

Step 2: Locate the existing cashback offer action.

Step 3: Add a new treatment specifically for the SMS channel. This involves creating a new SMS treatment that defines the message content, format, and any other relevant details.

Step 4: Ensure the new treatment is linked to the cashback offer action.

Edit the Engagement Policy:

Step 1: In the Pega Customer Decision Hub, go to the "Engagement Policies" section.

Step 2: Locate the engagement policy associated with the cashback offer.

Step 3: Update the suitability condition by lowering the debt-to-income ratio threshold from 48 to 45. This ensures that the new condition is applied when evaluating customer eligibility for the cashback offer.

Step 4: Save and publish the updated engagement policy to ensure it takes effect.

Verify the Changes:

Step 1: Test the new SMS treatment by sending test messages to a seed list to verify the content and formatting.

Step 2: Ensure that the updated engagement policy correctly filters customers based on the new debt-to-income ratio threshold.

References:

Pega-Customer-Decision-Hub-User-Guide-85.pdf: "Defining treatments for actions" and "Configuring engagement policies" sections.

Pega documentation on "Creating and managing actions" and "Editing engagement policies".

To ensure that Silver credit cards are not offered to customers under 27 years of age and that Platinum cards are offered only to customers who had a positive balance in the last year, you need to configure "Engagement policies" in the Next-Best-Action Designer. Engagement policies allow you to set criteria such as eligibility, applicability, and suitability for actions. For this scenario, you would set the eligibility criteria to ensure the age and balance conditions are met before the offers are presented.

 Introduction to Prioritize Component:

The Prioritize component in Pega Decisioning is used to order actions based on specific criteria.

This component evaluates the importance or priority of different actions to determine which should be executed first.

 Understanding Propensity:

Propensity is a prediction of the likelihood that a customer will respond positively to a particular action.

It is a key factor in decision-making processes as it reflects the customer's predicted behavior based on past interactions and other data.

 Role of Propensity in Prioritize Component:

The primary function of the Prioritize component is to rank actions.

This ranking is typically based on the propensity value, which is calculated using predictive models.

The action with the highest propensity is considered the top action because it has the highest predicted likelihood of a positive customer response.

 Verification from Pega Documentation:

According to Pega's guidelines on creating and understanding decision strategies, propensity is a standard and recommended metric for prioritizing actions within the Prioritize component.

To present offers from both groups and arbitrate across the two groups to select the best offer based on customer behavior, you need to map a real-time container to the Top-level or Issue-level in the Next-Best-Action Designer. This mapping allows the system to evaluate and arbitrate offers from different groups based on the defined criteria and customer behavior, ensuring the most relevant offers are presented.

 Volume Constraint Application: Given the volume constraints of a maximum of 100 daily for the StandardCard action, and 75 daily for both Email and SMS channels, the total actions delivered would be limited to the smallest constraint applicable to each channel.

 Calculation:

The StandardCard constraint allows 100 actions per day.

The Email constraint allows 75 actions per day.

The SMS constraint allows 75 actions per day.

Therefore, the total actions delivered = 100 (since the StandardCard action is constrained to 100 but both email and SMS actions can only reach 75 each).

To automatically pause actions that are shown too often for a specific time period, you need to define suppression rules in Pega Customer Decision Hub. Suppression rules allow you to put an action on hold after a specific number of outcomes, such as views or clicks, have been recorded over a defined period. This helps prevent overexposure and ensures a better customer experience by limiting how frequently the same action is shown to a customer.

To ensure that there is no gender bias when presenting mobile data packages for students, you should configure the ethical bias policy to allow a 1 Rate Ratio. This setting ensures that the system will show a warning if there is any deviation from an equal distribution between genders, thereby preventing any gender-based discrimination in offer presentation.

To implement the required changes for the mortgage offers, you should create two separate change requests in the 1:1 Operations Manager portal. This ensures each change is tracked and managed individually.

Update Suitability Condition for Fifteen-Year Fixed-Rate Mortgage Offer:

Step 1: Log into the 1:1 Operations Manager Portal.

Step 2: Create a change request for updating the suitability condition of the Fifteen-Year Fixed-Rate Mortgage offer.

Step 3: Specify the details of the change, including the new suitability condition (Credit Score > 450).

Step 4: Submit the change request for approval and implementation.

Introduce a New Offer - Twenty-Year Fixed-Rate Mortgage:

Step 1: In the 1:1 Operations Manager Portal, create a new change request for introducing the Twenty-Year Fixed-Rate Mortgage offer.

Step 2: Define the new offer, including its eligibility, applicability, and suitability conditions (Credit Score > 600).

Step 3: Configure the necessary treatments and engagement policies for the new offer.

Step 4: Submit this change request for approval and implementation.

Best Practices:

Creating separate change requests ensures that each modification is properly documented and approved, reducing the risk of errors and making it easier to track changes.

This approach also allows for independent testing and validation of each change before it goes live.

References:

Pega-Customer-Decision-Hub-User-Guide-85.pdf: "Managing business-as-usual changes with Pega 1:1 Operations Manager" section.

Pega documentation on "Creating change requests in 1:1 Operations Manager".

By following these steps, U+ Bank can effectively manage the changes to their mortgage offers, ensuring that both the updated suitability condition and the new offer are correctly implemented.