Reviewing AI-generated Personas and brand voice

You used the Pega Customer Engagement Blueprint™ tool to create a strategy for U+ Bank to cross-sell credit cards to existing checking account customers. In this topic, you will review the AI-generated Personas and brand voice.

So far, the Blueprint contains the U+ Bank's engagement context, and uses Grow as the outcome and Email and Web as channels. The AI Agents began generating customer Personas based on these settings. Now it’s time to see what the Agents created.

Perfect! The AI created comprehensive profiles that represent different checking account customer segments who might be interested in credit cards. But should I trust these AI-generated Personas, or do I need traditional market research? Let me ask the Blueprint Agent about this.

I will ask, Do I need additional marketing research?

That is an extensive reply! It boils down to the advice that targeted marketing research is needed to further optimize the Customer Engagement Blueprint.

Now let me check the Brand page to see what the AI extracted about U+ Bank's brand.

The AI identified brand voice characteristics from the U+ Bank website. For example: Value-Led, Plainspoken, Relationship-Aware and Measured Confidence. You can also configure your visual identity in the blueprint.

The sample email shows how these characteristics are applied. The subject line and the message use a confident and informative tone.

With these elements in place, the AI has created a solid foundation: customer personas representing different segments, brand voice characteristics ensuring consistent messaging, and you can configure the visual identity to maintain U+ Bank's look and feel. Based on our input, the agents create a set of customer experiences to support our use case.

In another video, you will see how the Pega Next-Best-Action process uses these Personas and brand characteristics to determine the right offer for each customer through a seven-stage filtering process.