Address your customers' needs better by predicting customer behavior with predictions. For example, you can determine the probability of a customer accepting an offer or the likelihood of a customer discontinuing a subscription (churn).
The most common predictions are built into Pega Customer Decision Hub as part of the Next-Best-Action Designer strategy framework, for example, Predict Action Propensity and Predict Treatment Propensity. Predictions are strategies driven by adaptive and predictive models. Predictions are used in decision strategies to predict outcomes based on customer characteristics and historical customer behavior, such as offer acceptance or web banner clicks.
To extend your next-best-action strategy framework, you can create your own predictions. Prediction Studio provides a range of prediction templates with preconfigured outcomes for customer engagement. For more information, see Creating predictions for customer engagement.
Replacing a model in a prediction is possible at any time in the prediction's life cycle, through Machine Learning Operations (MLOps). As a data scientist, you can add and approve the new model in a non-production environment, and start a deployment process to migrate the new model to production.