Configuring the Customer Engagement Blueprint settings

Pega Customer Engagement Blueprint™ analyzed the U+ Bank website to extract relevant business and brand information. In this topic, explore how to configure the outcomes and Channels that we want to use.

Earlier, I defined U+ Bank's engagement context by providing its website URL and business objective: cross-selling credit cards to existing checking account customers. The AI agents started analyzing the website. Now let's see what they discovered and configure our Blueprint settings. The analysis is complete and I am now on the Setup page. Let us have a look at what the AI discovered.

Blueprint identified the industry as Banking: that is correct. And for Products and Services, it extracted Checking, Savings, and Credit cards. Excellent. The AI analyzed the U+ Bank website and correctly identified the product catalog. This information will shape the personas and experiences we generate.

Now I need to configure the Blueprint by selecting outcomes and Channels. I can see several options. The goal is to sell credit cards. Let me ask the Blueprint Agent about this.

"Which outcome should I select for cross-selling credit card customers?"

Interesting. The agent explains that I could use either Grow or Acquire. Grow focuses on expanding the customer relationship by offering additional products. Acquire focuses on getting customers to adopt a new product. Because the bank wants to expand existing relationships with checking account customers, Grow  makes more sense for this use case.

Alright, I'll select "Grow  as the outcome.

Good. Now I see a new section: What channels will you be communicating on? I have many options, but for cross-selling credit cards, Email and Web make the most sense. They are digital channels that support personalized, scalable outreach to existing customers. I’ll select both, and then click OK to confirm my selections.

Great! The Channels are now confirmed as Email and Web. I can see that there are optional features available, Customer Journeys and Data Model, but I’ll proceed to the next step to see what the AI generates based on the configuration.

Excellent! Based on the "Grow" outcome and the U+ Bank website analysis, the AI is now generating customer personas that represent different segments of checking account customers who might be interested in credit cards.