Leveraging Pega GenAI Automated Insights

This video shows you how to use Automated insights to make the change request creation process more efficient and effective.

Automated insights combine the power and features of Pega Value Finder analysis with Pega GenAI, to detect underperforming Next-Best-Actions and provide actionable recommendations for improving actions and treatments. The suggestions are available in 1:1 Operations Manager, in the Automated Insights section.

U+Bank has several active credit card offers. Based on a Value Finder analysis, the treatments associated with the actions do not bring the maximum business value. The bank aims to increase the accept rate of existing actions.

On the Automated insights tab, you can explore the recommended solutions to enhance actions and boost business value.

Expand the single recommendation to view its description and details. In the Recommended content configuration section, you can review the recommended treatment settings and check how many variants of the treatments are preconfigured. Click Preview treatment suggestions to see the two options. You will be able to select one of these options at a later stage.

In this case, a particular audience exhibits a low response rate for the Rewards card. Presenting this offer to the Superior Credit Elite customer type would likely result in a higher accept rate.

Selecting Proceed to a plan stage initiates the process of updating the action with the recommended treatment. The newly created change request includes Pega GenAI-generated suggestions, providing the opportunity to modify or reject them based on business needs.

In the Define channels and treatments stage, you can observe two treatment recommendations for the action. U+ Bank aims to maximize the interest in the action, so proceed with both recommended options.

Each recommendation provides two variants of predefined treatments with Pega GenAI-generated images. Additionally, you can also observe the initial Rewards card tile treatment. Remove the variants that are less appealing, then set the Placement type to Tile and continue.

After you successfully create the change request as a Business User, log in as a Team Lead and prioritize the change request.

The next step is to complete the action build task. Log in as an NBA Specialist and check if you see the Design web treatment tasks for each of the newly created treatments.

Assign the Design web treatment tasks to yourself and complete them one by one.

As an NBA Specialist, you can also regenerate Pega GenAI-generated treatment images if they don't meet the business requirements. Pega GenAI-generated images can be used as an inspiration. However, the final decision about the content rests with the operations team.

From this point, the NBA Specialist, the Team Lead and the Revision Manger can finish the process until the new changes are deployed to production.

You have reached the end of this video. What did it show you?

• What Automated Insights are in 1:1 Operations Manager.
• How to use Automated Insights recommendations to make the Change Request creation process more effective and efficient.