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Using historical data to predict customer behavior

Updated on September 10, 2021

Predictive analytics augments enterprise decision-making processes through the use of predictive models. The models use historical data, like the past behavior of your customers and their profiles, to identify patterns, risks, and opportunities. You can build predictive models in Pega Platform™ or use the third-party models that are PMML-compliant.

Predictive analytics is a business intelligence technology that makes it possible for you to differentiate among customers based on their likely future behavior. It can also help you to make decisions about which actions to take with a particular customer or customers. Furthermore, predictive analytics can optimize marketing campaigns and decrease the churn rate among customers.

Build predictive models

Build predictive models in the Analytics Center and export them into Predictive Model rule instances, or upload PMML-compliant models into Predictive Model rule instances. For more information, see:

Configure Predictive Model rules

Manage and configure the settings of your predictive model by using the Predictive Model rule form. For more information, see:


Predicting credit risk and customer churn in a Strategy rule

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