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Pega Decisioning Consultant

This course is for business users who are responsible for developing Next-Best-Action decision strategies.

Gain greater understanding of the key features, capabilities and benefits of the Pega Customer Decision Hub in this course. Learn how components such as Proposition Management, Predictive Analytics and Interaction History are used to create, simulate and analyze real-time Next-Best-Action decision strategies. Get hands-on experience building strategies for real-time interactions as well as simulating and analyzing their results using Visual Business Director.

Prerequisites

  • None

What you'll learn

By the end of this course, you will be able to successfully:

  • Understand the basic components and capabilities of Pega Customer Decision Hub.
  • Understand how Next-Best-Action improves the customer experience.
  • Create a predictive model and use it in the Next Best Action strategy.
  • Explain how adaptive modeling works and configure adaptive models.
  • Prioritize propositions based on marketing weight, customer intent and predicted customer.
  • Run alternative strategies and compare the results using Visual Business Director.

Course Outline

  1. Course introduction

    • Before You Begin
  2. Introducing decisioning concepts

    • Introducing decisioning concepts
  3. Optimizing the customer value in the call-center

    • Optimizing the Customer Value in the Call-center
    • Practicing What You Learned
  4. The importance of propositions

    • Tell me how to define propositions in my organization
    • Show me how to manage propositions
    • Challenge me creating new propositions
  5. Decision strategy canvas

    • Tell me what is a strategy canvas
    • Guide me importing proposition to the strategy canvas
  6. Calculating dynamic prices

    • Tell me how to personalize propositions with dynamic pricing
    • Guide me using Property-Set component
  7. Selecting the most profitable proposition

    • Tell me how to select the most profitable proposition
    • Challenge me using the Prioritize component
    • Show me how to rank propositions using Prioritize component
  8. Predicting customer behavior

    • Introduction to data analytics
    • Tell me how to predict customer needs
    • Challenge me adding an Adaptive Model component
    • Show me how to use adaptive decisioning
    • Tell me how to retain customers using predictive analytics
    • Challenge me selecting a proposition based on prediction
    • Show me how to retain customers using predictive analytics
  9. Selecting the target audience

    • Tell me how to select the target audience
    • Challenge me adding a Filter component
    • Show me how to select the target audience using a Filter
  10. Arbitrating between propositions

    • Tell me how to do reactive retention
    • Challenge me adding a Switch component to a strategy
    • Show me how to do reactive retention using a Switch
  11. Learning from historical interactions

    • Tell me how to learn from historical interactions
    • Challenge me adding Interaction History component
    • Show me how to configure interaction history component
  12. Defining proposition eligibility rules

    • Tell me what is product eligibility
    • Show me how to define proposition eligibility criteria
    • Challenge me creating and using a When rule
    • Show me how to extend a Proposition Filter rule
  13. Using aggregated data to select the best offer

    • Tell me how to aggregate data to determine the best offer
    • Challenge me how to aggregate historical interactions
    • Show me how to reconnect with a customer
  14. Designing decision strategies for real-life scenarios

    • Practicing What You Learned
  15. Testing strategies en masse with simulations

    • Testing strategies en masse with simulations
    • Practicing What You Learned
  16. Decision strategy execution

    • Decision strategy execution
    • Practicing What You Learned
  17. Balancing business objectives with customer needs

    • Balancing Business Objectives with Customer Needs
    • Practicing What You Learned
  18. Assessing the impact of a new product offer

    • Assessing the impact of a new product offer
    • Practicing What You Learned
  19. Avoiding redundant product offerings

    • Avoiding redundant product offerings
    • Practicing What You Learned
  20. Retaining your customers with predictive analytics

    • Retaining your Customers with Predictive Analytics
    • Practicing What You Learned
  21. Avoiding loan default with predictive analytics

    • Avoiding Loan Default with Predictive Analytics
    • Practicing What You Learned
  22. Third party predictive models

    • Third Party Predictive Models
    • Practicing What You Learned
  23. Predicting customer behavior using real-time data

    • Predicting Customer Behavior Using Real-time Data
    • Practicing What You Learned
  24. Detecting dropped calls

    • Detecting Dropped Calls
    • Practicing What You Learned
  25. Course Summary

    • Before You Leave

Choose Your Format

Need help choosing the best format? Learn More.

  • Skill Level

    Intermediate

  • Duration

    5 days

  • Platform Version

    7.4

  • Skill Level

    Intermediate

  • Duration

    5 days

  • Platform Version

    7.4

  • Skill Level

    Intermediate

  • Duration

    5 days

  • Platform Version

    7.4

Have you completed this course?

Recommended next step:

Pega Decisioning Consultant Practice Exam
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