Skip to main content

This content has been archived and is no longer being updated.

Links may not function; however, this content may be relevant to outdated versions of the product.

Exploring key decision management features with DMSample

Suggest edit
Updated on April 5, 2022

Gain hands-on experience of the decision management functionality through DMSample – a reference application that walks you through real-life decision use cases, by providing preconfigured artifacts and simulated input data.

Before you begin: Configure the DMSample application:
  1. Switch your application to DMSample.

    For more information, see Switching between applications in Dev Studio.

  2. Generate the data that you need to fully explore DMSample use cases by creating and running the Initialize Application case.

    For more information, see Initializing DMSample data.

  3. Generate reports that help you verify that DMSample predictive models accurately predict customer behavior.

    For more information, see Initializing predictive model monitoring.

  1. Learn about end-to-end scenarios and real-life decision management use cases in DMSample:
    1. In the header of Dev Studio, click DMSampleOverview.
    2. To learn more about a feature, click the corresponding tile.
  2. Explore core DM features and best practices:
    • Learn how to arrange advertisements, products, offer bundles, or services in a proposition data model by exploring examples for cross-selling, retention, and sales.
    • Delve into sample decision strategies to discover the best practices for selecting the most relevant propositions for customers.
    • Learn how to run strategies through the input-process-output pattern of data flows to issue decisions, capture responses, and generate work assignments.
    • Explore predictive models for determining churn likelihood, assessing credit risk, and predicting call context. Use machine learning to proactively react to patterns in customer behavior, based on previous interactions.
    • Find out how to increase the relevance of next-best-action strategies through adaptive analytics. Adaptive models in DMSample can dynamically calculate the likelihood of a positive response to tablet and phone propositions, and determine which message is the most relevant to a customer in a given context.
    • Explore Customer Movie to gain insight into various aspects of customer behavior, detect meaningful patterns, and enhance offline and online interactions.
    • Learn about using event strategies to maintain the quality of service. An end-to-end scenario demonstrates how to react to dropped customer calls in real time.
  3. Enable the option to extend DMSample with new rules and new rule versions by adding an unlocked ruleset version.
    For more information, see Creating rulesets.
  1. Initializing DMSample data
  2. Initializing predictive model monitoring
Did you find this content helpful? YesNo

Have a question? Get answers now.

Visit the Support Center to ask questions, engage in discussions, share ideas, and help others.

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

Pega.com is not optimized for Internet Explorer. For the optimal experience, please use:

Close Deprecation Notice
Contact us