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Mission

AI for 1:1 Customer Engagement

9 Modules

15 Challenges

11 hrs 25 mins

Visible to: All users
Beginner Pega Customer Decision Hub '24.2 English

Familiarize yourself with the one-to-one customer engagement paradigm and discover how Pega omni-channel AI delivers the right action during every customer interaction. Learn how to optimize the adaptive models that drive Pega Customer Decision Hub™ predictions. Learn how to use predictive models to improve the decisions that Customer Decision Hub makes and how to update predictions with the MLOps process.

  • Explore the CDH role based learning paths here download pdf
  • Access the offline mission content here student guide

Available in the following mission:

Data Scientist v8

Customer Decision Hub overview

  • Module

    Customer Decision Hub overview

    5 Topics

    55 mins

  • Familiarize yourself with the one-to-one customer engagement paradigm and discover how Pega’s omnichannel AI delivers the right action during every...

Exploring decisions in Customer Decision Hub

  • Challenge

    Exploring decisions in Customer Decision Hub

    4 Tasks

    10 mins

  • U+ Bank uses Pega Customer Decision Hub™ to decide which one of four credit card offers to show in a web banner when a customer logs in to the U+ Bank...

Customer Decision Hub predictions

  • Module

    Customer Decision Hub predictions

    3 Topics

    35 mins

  • Discover the Pega Customer Decision Hub™ predictions in the Prediction Studio portal, a comprehensive workspace for Data Scientists who manage...

Exploring Prediction Studio

  • Challenge

    Exploring Prediction Studio

    2 Tasks

    10 mins

  • U+ Bank implements Pega Customer Decision Hub™ to optimize customer interactions on their web channel by showing a personalized web banner when...

Adaptive models

  • Module

    Adaptive models

    4 Topics

    50 mins

  • Online, adaptive models are crucial to next-best-action decision strategies in Pega Customer Decision Hub™. Adaptive Decision Manager is a key...

Adding predictors to an adaptive model

  • Challenge

    Adding predictors to an adaptive model

    6 Tasks

    10 mins

  • U+ Bank is implementing cross-selling of their credit cards on the web by using Pega Customer Decision Hub™. The implementation team has set up the...

Shadowing an adaptive model

  • Challenge

    Shadowing an adaptive model

    4 Tasks

    10 mins

  • U+ Bank uses Pega Customer Decision Hub™ to personalize the credit card offers that a customer receives on the U+ Bank website. A prediction...

Monitoring adaptive models

  • Module

    Monitoring adaptive models

    3 Topics

    40 mins

  • It is a regular data scientist task to inspect the health of the out-of-the-box Pega Customer Decision Hub™ predictions and the adaptive models that...

Monitoring adaptive models

  • Challenge

    Monitoring adaptive models

    3 Tasks

    10 mins

  • The models for the U+Bank implementation of cross-selling on the web of their credit cards have been learning for some time. Your task in this...

Exporting adaptive model data

  • Module

    Exporting adaptive model data

    3 Topics

    35 mins

  • The reporting datamart of Pega Adaptive Decision Manager (ADM) is an open data model. As a result, data scientists that work on Pega Customer Decision...

Exporting historical data

  • Challenge

    Exporting historical data

    2 Tasks

    15 mins

  • U+ Bank has implemented Pega Customer Decision Hub™ to display a personalized credit card offer to eligible customers on their website. As a data...

Exporting adaptive model data for external analysis

  • Challenge

    Exporting adaptive model data for external analysis

    3 Tasks

    25 mins

  • U+ Bank implements cross-selling of their credit cards on the web by using Pega Customer Decision Hub™. Self-learning, adaptive models drive the...

Creating predictions

  • Module

    Creating predictions

    5 Topics

    45 mins

  • Predicting customer churn is a crucial challenge, as losing customers can significantly impact profitability. To address this requirement, you can use...

Creating a churn prediction using a scorecard

  • Challenge

    Creating a churn prediction using a scorecard

    2 Tasks

    20 mins

  • U+ Bank wants to predict and avoid potential customer churn before it happens. When customers leave a bank, the result is costly in terms of lost...

Creating a churn prediction using an ML model

  • Challenge

    Creating a churn prediction using an ML model

    2 Tasks

    15 mins

  • U+ Bank implements Pega Customer Decision Hub™ to personalize the credit card offer a customer is presented on their website. If a customer is...

Challenging a Predictive Model

  • Challenge

    Challenging a Predictive Model

    3 Tasks

    10 mins

  • U+ Bank uses Pega Customer Decision Hub™ to personalize the credit card offers that a customer receives on the U+ Bank website. The bank makes a...

Decision Strategies Overview

  • Module

    Decision Strategies Overview

    2 Topics

    45 mins

  • Decision strategies optimize business processes by using data-driven, real-time arbitration to select the best actions for specific contexts. This...

Building a Decision Strategy

  • Challenge

    Building a Decision Strategy

    3 Tasks

    40 mins

  • As a Decisioning Architect, you are tasked with designing a basic decision strategy that outputs a Label Action with the lowest printing cost. A set...

Testing decision strategies

  • Challenge

    Testing decision strategies

    4 Tasks

    30 mins

  • A decision strategy that produces the next-best-label Action is set up in the application. The purpose of the decision strategy is to select the label...

Defining prediction patterns

  • Module

    Defining prediction patterns

    2 Topics

    20 mins

  • Learn how to improve the predictive power of your adaptive models by configuring additional potential predictors in Pega Customer Decision Hub™. For...

Using parameterized predictors

  • Challenge

    Using parameterized predictors

    4 Tasks

    30 mins

  • U+ Bank is cross-selling their credit cards on the web by using Pega Customer Decision Hub™. All available customer data, including financial...

Leveraging a churn prediction

  • Challenge

    Leveraging a churn prediction

    3 Tasks

    25 mins

  • U+ Bank implements Customer Decision Hub™ to determine which credit card offers to show to customers on its website. As part of the implementation...

Model governance

  • Module

    Model governance

    4 Topics

    50 mins

  • AI has the potential to deliver significant benefits, but improper controls can result in regulatory issues, public relations problems, and liability...

Detecting unwanted bias in engagement policy conditions

  • Challenge

    Detecting unwanted bias in engagement policy conditions

    6 Tasks

    15 mins

  • U+ Bank is currently cross-selling on the web by showing various credit cards to its customers.

    The bank wants to run an ethical bias simulation in...

mission badge: AI for 1:1 Customer Engagement

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