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Developing and managing models

Suggest edit Updated on March 11, 2021

Configure and manage AI capabilities of Pega Platform to predict customer behavior and perform text analysis. Enhance the relevance of decisions by using adaptive models that are self-learning. Incorporate predictive analytics into every process and every interaction with your customers. Analyze texts from various sources, such as e-mail, chat channels, social media, and so on.

  • Adaptive analytics

    Adaptive Decision Manager (ADM) uses self-learning models to predict customer behavior. Adaptive models are used in decision strategies to increase the relevance of decisions.

  • Predictive analytics

    Predictive analytics predict customer behavior, such as the propensity of a customer to take up an offer or to cancel a subscription (churn), or the probability of a customer defaulting on a personal loan. Create predictive models in Prediction Studio by applying its machine learning capabilities or importing PMML models that were built in third-party tools.

  • Managing data

    Create and manage data sets, Interaction History summaries, and other resources. Make sure that you identify the data that correlates to your business use case and that is aligned with the use problem that you want to solve.

  • Model management

    On the Model Management landing page, you can manage adaptive models that were run and predictive models with responses. You can view the performance of individual models and the number of their responses, or perform various maintenance activities, such as clearing, deleting, and updating models.

  • Viewing Prediction Studio notifications

    Gain an insight into the performance of your adaptive and predictive models by accessing notifications in Prediction Studio. By viewing detailed monitoring data for your models, you can update their configuration to improve the predictions that you use to adjust your client-facing strategies.

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