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Pega NLP Essentials

Pega Process AI Essentials

Preparation for 1:1 Customer Engagement Implementation

PW24 Enhancing Customer Engagement with Pega Customer Decision Hub

  • Mission

    PW24 Enhancing Customer Engagement with Pega Customer Decision Hub

    5 Challenges

    1 Std. 30 Min.

    Pega Customer Decision Hub '24.1 Visible to: All users
  • Hands-on Training: Enhancing Customer Engagement with Pega Customer Decision Hub™ 

      Discover how Pega Customer Decision Hub™ solves business problems...

    Adaptive analytics overview

    • Modul

      Adaptive analytics overview

      4 Themen

      35 Min.

      Visible to: All users
    • Pega Adaptive Decision Manager (ADM) is a component that allows you to build self-learning adaptive models that continuously improve predictions. ADM...

    Adaptive models

    Applying NLP for Case classification

    • Modul

      Applying NLP for Case classification

      1 Thema

      10 Min.

      Pega Platform '24.1 Visible to: All users
    • Pega Process AI™ utilizes Natural Language Processing to automatically categorize and route claims based on customer descriptions, eliminating delays...

    Building the customer analytical data model

    • Modul

      Building the customer analytical data model

      9 Themen

      1 Std. 55 Min.

      Visible to: All users
    • Data lies at the heart of one-to-one customer engagement. Utilize industry-specific data models for customer-centric decisioning, based on best...

    Building the Customer Insights Cache

    • Modul

      Building the Customer Insights Cache

      9 Themen

      1 Std. 45 Min.

      Visible to: All users
    • Data lies at the heart of one-to-one customer engagement. Utilize industry-specific data models for customer-centric decisioning, based on best...

    Creating parameterized predictors

    • Modul

      Creating parameterized predictors

      1 Thema

      15 Min.

      Pega Customer Decision Hub 8.6 Visible to: All users
    • Learn how to improve the predictive power of your adaptive models by creating parameterized predictors. Input fields that are not directly available...

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