Leveraging GenAI to understand configuration results in Customer Profile Viewer

2 Tasks

15 mins

Visible to: All users

Beginner

Pega Customer Decision Hub '23

English

Scenario

U+ Bank is currently cross-selling on the web. The business operations team is looking to enhance their understanding of test configuration results in the Customer Profile Viewer using the AI Insight feature.
The business aims to gain insights into the usage of engagement policies, as well as the reasons why customers may not be receiving a specific action, and optimize their strategies to provide more effective experiences for their customers.

Use the following credentials to log in to the exercise system:

Role	User name	Password
Decisioning Architect	DecisioningArchitect	rules

Your assignment consists of the following tasks:

Task 1: Examine Troy's profile in Customer Profile Viewer

Examine Troy's profile in the Customer Profile Viewer to check the actions that he qualifies for in an Inbound Web channel.

Task 2: Understand how engagement policies filter some actions

With the help of AI Insights, understand how engagement policies filtered some actions for Troy.

Challenge Walkthrough

Detailed Tasks

1 Examine Troy's profile in Customer Profile Viewer

Log in as a Decisioning Architect, with username DecisioningArchitect using password rules.
In the header of Pega Customer Decision Hub, click Reports > Customer Profile Viewer to open Customer Profile Viewer.
In the Customer Profile Viewer, complete the details to access the customer profile:
1. In the Type list, select Customer name.
2. In the Customer Name field, enter or select Troy Murphy.
Click View to see Troy's profile.
In the profile of Troy, click the Next best actions tab to check the propensity.
On the Next best actions tab, complete the following details:
1. In the Channel context list, select Web Inbound.
2. Select the Show all decision results radio button.
3. Click Make decision to see the decision table.
  Note: If the AI insights are slow to display, click Make Decision again.

2 Understand how engagement policies filter some actions

After you view the next-best-action decisions for Troy, you can use the AI Insight feature, which uses Pega GenAI™ to better explain the results that are displayed in the table. The AI Insight provides the summary for the tested configuration. In this example, you receive a clear explanation that there are four candidate offers for Troy. However, only 2 actions passed, and 2 actions were filtered out due to the Suitability conditions.

Click on the Polaris icon in the results column of the Rewards Plus Card to view an explanation of the action results.

In the Action results explanation window, you will learn that the Rewards Plus Card is filtered out due to a suitability condition. It also provides you with the probable approach to make this offer pass and be delivered to customers.