Skip to main content

Mission

AI for 1:1 Customer Engagement

Archived

10 Modules

19 Challenges

12 hrs 35 mins

Visible to: All users Applies to: Pega Customer Decision Hub '23

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
  • To receive updates to this mission follow us on twitter
Beginner
English

Available in the following mission:

Data Scientist v6
This content is now archived and is no longer updated. Progress is not calculated. Pega Cloud instances are disabled, and badges are no longer awarded. Click here to continue your progress in the latest version.

Customer Decision Hub overview

  • Module

    Customer Decision Hub overview

    Archived

    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

    Archived

    2 Topics

    30 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

    Archived

    3 Topics

    40 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

    Archived

    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...

Monitoring adaptive models

  • Module

    Monitoring adaptive models

    Archived

    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

    Archived

    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

    Archived

    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

    Archived

    6 Topics

    1 hr

  • Predicting customer churn is one of many business use cases that involve predictive models. Pega Customer Decision Hub™ provides predictions that use...

Creating a churn prediction using a scorecard

  • Challenge

    Creating a churn prediction using a scorecard

    3 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...

Building models with Pega machine learning

  • Challenge

    Building models with Pega machine learning

    6 Tasks

    15 mins

  • U+ Bank implements Customer Decision Hub™ to determine which credit card offer to show a customer on the bank's website. To reduce the number of...

Importing predictive models

  • Challenge

    Importing predictive models

    Archived

    1 Task

    10 mins

  • U+ Bank implements Pega Decision Management but already uses predictive models that an external bureau created. You are asked to make an existing H2O...

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...

MLOps

  • Module

    MLOps

    Archived

    3 Topics

    30 mins

  • In the ever-evolving world of data-driven decisions, organizations aim to refine predictive models for optimal outcomes. This involves challenging...

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...

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...

Creating and understanding decision strategies

  • Module

    Creating and understanding decision strategies

    Archived

    4 Topics

    1 hr 10 mins

  • Next-Best-Action Designer provides a guided and intuitive UI to bootstrap your application development with proven best practices that generate the...

Creating a decision strategy

  • Challenge

    Creating a decision strategy

    3 Tasks

    25 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 a decision strategy

  • Challenge

    Testing a decision strategy

    3 Tasks

    25 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

    Archived

    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 behavioral data as predictors

  • Challenge

    Using behavioral data as predictors

    4 Tasks

    10 mins

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

Using offline model scores as predictors

  • Challenge

    Using offline model scores as predictors

    3 Tasks

    15 mins

  • U+ Bank uses Pega Customer Decision Hub™ for engagement with its customers. Externally, the data scientist team produces many product group scores for...

Using online model scores as predictors

  • Challenge

    Using online model scores as predictors

    Archived

    4 Tasks

    15 mins

  • U+ Bank is implementing cross-selling of its products on the web by using Pega Customer Decision Hub™. The U+ Bank data science team develops...

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

    Archived

    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

    Archived

    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

We'd prefer it if you saw us at our best.

Pega Academy has detected you are using a browser which may prevent you from experiencing the site as intended. To improve your experience, please update your browser.

Close Deprecation Notice