Pega Customer Decision Hub overview

Most marketing stacks use a combination of channel-based decisioning solutions, that do not work out-of-the-box together and cannot keep pace with today's customers. The design of these marketing stacks intends to push products rather than solve problems. Building real relationships with today's customers means engaging them one-to-one, anticipating their needs, and delivering relevant experiences across channels.

Customer Decision Hub is the central decision engine of your marketing stack, constantly analyzing the context of the customer and recommending the most relevant, next best action to take, all in real time. Here is how it works.

You first identify the outcomes that you want to achieve, such as increasing sales, reducing churn, or preventing service issues. These outcomes are called business issues. A business issue is the purpose behind the actions that you offer to customers. The business issues contain business groups to organize actions into categories.

Next, you create actions, such as upsell or cross-sell offers, retention bundles, and nurture messages that Customer Decision Hub uses to engage your customers. You create treatments, variations of these actions, to tailor that engagement to multiple channels. Each action and treatment automatically receive a predictive model, so our AI can determine exactly what each customer needs.

With Customer Decision Hub, the next-best-action customer journey takes a transformational approach by using real-time AI to prioritize across all potential journeys and actions to deliver more relevant customer experiences.

Customer Decision Hub helps marketers leverage thousands of pieces of historical data and identify the actions and journeys that lead to positive engagement. Because Customer Decision Hub takes advantage of real-time machine learning, all the predictions are up to date, which ensures that customers receive personalized offers at each stage.

You define a journey once across all business objectives, channels, and lines of business. Then, you add the different stages and assign the corresponding actions to each one. As customers move through their journeys, the AI learns continuously and automatically to identify which actions work best at each stage and pivots between selling, serving, and retaining in real time as the needs of customers change.

Then, you define specific channel and action limits and limit overexposure to a specific action or group of actions. With outbound and inbound action limits, you restrict the number of actions that the system presents to customers in a given period of time.

Next, you set rules of engagement so that Customer Decision Hub knows what customers are eligible for, when certain actions make sense, and what to prioritize in different situations. Engagement policies are a set of business rules and practices that the organization uses to determine which customers qualify for which next best actions. These policies allow you to specify the conditions under which an action or group of actions a customer is eligible for.

You balance customer relevance with business priorities by using arbitration. Arbitration is how Customer Decision Hub prioritizes the remaining list of eligible, applicable, and suitable actions from each group. On the Arbitration tab of Next-Best-Action Designer, you can define the AI controls that the system uses to rank the next best action for each customer.

Finally, you activate your next best actions in the intended delivery channels, which creates a "brain" that powers your entire engagement program.

As you use the Next-Best-Action Designer user interface to define strategy criteria, the system uses these criteria to create the next-best-action strategy framework. This framework leverages best practices to generate next-best-action decision strategies at the enterprise level. These decision strategies are a combination of the business rules and AI models that form the core of Customer Decision Hub, which determines the personalized set of next best actions for each customer. There are several extension points in the framework. An extension point is an empty rule or activity that is intended to be overridden to meet the specific needs of the application. 

In most cases, you do not need to configure the strategy directly. However, Customer Decision Hub includes extension points if you need to add your own business logic to the framework. 

With Customer Decision Hub, you also have all the tools you need to test the AI, simulate different strategies, and find the right mix to optimize performance across your key performance indicators (KPIs). With Scenario Planner, you can compare different configurations, to see which one best impacts your business. With Value Finder, you can also identify underserved customers through simulation tests that allow you to investigate how an introduction of a new engagement policy might affect actions that are offered across a segment of customers.

Each time a customer engages with an offer, the channel calls Customer Decision Hub for a new next best action. Because Customer Decision Hub updates itself every time you receive a new piece of data, you constantly trigger new offers and messages as you learn more about each customer.

So, whether customers browse the web, read an email or mobile message, talk with a CSR, or see a digital ad, that experience is all about them every time. Pega Customer Decision Hub helps you embrace empathy at scale across your entire enterprise, helps customers get what they need, and helps you generate hundreds of millions in incremental value every year.