- Hey everyone, I'm Matt Camuso here with Alyssa Danilow, and we're diving into something that's transforming how brands engage with their customers. That's adaptive analytics with Pega Customer Digital Hub. Now, if you're thinking, "Here we go again, another data AI buzzword." Please stick with us, because what we're talking about today is fundamentally different from what most companies are doing right now. - That's right, Matt. And here's why it matters. Most organizations today that are using innovative forms of AI are focused on things like content generation and information gathering. Think prompt focus chatbots and AI rappers. And when it comes to decision management, most brands are still stuck using rigid business rules and maybe some predictive models created by data scientists. This approach is manual and static, and it's looking at historical data to forecast what might happen next.
But here's the problem. Your customers aren't historical, and they aren't static. They're right here, right now, making decisions in real time. - Exactly. So say you're a data science leader at a bank, you've got hundreds of models that you need to build, deploy, test, maintain manually. It's exhausting, it's time-consuming. And by the time you've deployed that model, customer data behavior is already shifted. You're always playing catch up. And that's where adaptive modeling changes everything.
So instead of relying solely on what happened in the past, adaptive models learn from every single interaction as it happens. Every click, purchase, every response feeds the system, and makes it smarter, automatically and in real time. So I think a real life example would help nail this home. Alyssa, walk us through how this actually works. - Absolutely. Imagine you're a marketer at a communication service provider, and you need to launch a new device plan. You've got variations, one with a monthly fee, another with an annual payment, another for family plans. Traditionally, you set up A/B tests, and that could take months to get statistically significant results. But with adaptive modeling in Pega Customer Decision Hub, the system starts learning the minute you make those offers available.
The systems observes how each customer responds. So let's say customer A clicks on the monthly option. The machine learning model discovers that this type of customer might prefer that structure. By the time customer B comes along, the system's already adjusted its predictions based on that first interaction. Not only that, you could also have your system analyze external field predictors and import them into Customer Decision Hub, so your models have started working even before the get-go. Now this is still in the works and coming very soon, so let's keep that a secret between us. But yes, the adaptive models are continuously learning and optimizing with every single customer interaction. - Cool. And here's what I love.
We have rich capabilities like champion challenger, shadowing, and other machine learning operations to help you introduce new predictors, and build models confidently. Now, for our marketers out there, what sort of things do we have in terms of adaptive models for segments and audiences? - Yeah, that's a great question. Our adaptive analytics are capable of producing hundreds, even thousands of automatic segments. Essentially, you know which customers have high or low propensity per model, group, issue, and product. And can describe these populations based on model futures and the most active, that drive the most significant lift. Therefore, you're creating segments out of shared or common attributes your adaptive models pick up on. - Love it. So here's the bottom line.
If you're still relying purely on business rules and manual model deployment, you're gonna fall behind. Customer expectations are rising, competition is intense, and adaptive modeling, it gives you the agility to keep pace, to keep scale and get ahead. Reach out on Pega Community to learn more, or check out pega.com.
