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Leveraging a churn prediction

2 Tasks

25 mins

 Visible to: All users
Beginner Pega Customer Decision Hub 8.7 English
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Scenario

U+ Bank uses AI to determine which credit card offers to show to customers on its website. The bank wants to reduce the number of clients that leave the bank by using a prediction to calculate the churn risk. The predictive model that drives the prediction is based on the historical data of the bank's customer base. The bank wants to show the potential churners a retention offer instead of a credit card offer.

As a decisioning architect, your task is to create an engagement strategy that makes use of the churn prediction. Next, you configure the Next-Best-Action Designer to decide between a credit card offer and a retention offer based on the outcome of the churn prediction.

Use the following credentials to log in to the exercise system:

Role User name Password
Decisioning architect DecisioningArchitect rules

Your assignment consists of the following tasks:

Task 1: Edit the RetentionStrategy to implement the new applicability rule

As a decisioning architect, modify the skeleton RetentionStrategy to accommodate the following applicability rule: a retention offer is applicable for customers who are at high risk of churn. The strategy should have a component (named, for example, High Churn Risk), which outputs the incoming strategy results if the customer is a high churn risk. Otherwise, the component should not output results.

Note: Use the PredictChurnPropensity prediction to determine if a customer is likely to churn.

Task 2: Configure the Next-Best-Action Designer

Configure the engagement policies with the newly created engagement strategy as group-level applicability rules. Ensure that the following rules are implemented:

  1. Retention offers are applicable for customers who are at high risk of churn.
  2. Sales offers are inapplicable for customers who are at high risk of churn.
    Note: Retention offers are under the Retain business issue, in the Negotiation group. Sales offers are under the Grow business issue, in the Credit cards group.

Task 3: Confirm your work

On the U+ Bank website, verify that Troy, a customer who is predicted to churn soon, is presented with a retention offer. Verify that Barbara, a customer who is expected to remain loyal for now, receives a credit card offer.

 

You must initiate your own Pega instance to complete this Challenge.

Initialization may take up to 5 minutes so please be patient.

Challenge Walkthrough

Detailed Tasks

1 Edit the RetentionStrategy to implement the applicability rule

  1. On the exercise system landing page, click Pega CRM suite to log in to Prediction Studio.
  2. Log in as a decisioning architect with user name DecisioningArchitect and password rules.
  3. In the navigation pane on the left, click Intelligence > Strategies.
  4. Search for and double-click RetentionStrategy to open the canvas.
  5. In the upper-right corner, click Check out for editing.
  6. Right-click the canvas, and then select Enable external input.
  7. Right-click the canvas, and then add a Prediction component.
  8. Right-click the Prediction component, and then select Properties.
  9. In the Prediction field, select the PredictChurnPropensity prediction; the Name field is auto-populated.
    Prediction properties
  10. Click Submit.
  11. From the Arbitration category, add a Filter component.
  12. Right-click the Filter component, and then select Properties.
    1. In the Name field, enter High Churn Risk.
    2. In the Filter condition field, enter PredictChurnPropensity.pxSegment=="Churn". Do not copy-paste, as some punctuation marks are not correctly recognized.
      Filter properties
    3. Click Submit.
  13. From the Enrichment category, add a Set property component.
  14. Connect the Set property component to the Prediction component.
    Note: The Set Property component provides the required input data for the prediction and can be used to set parameterized fields.
  1. Connect the External Input to the Filter component, and the Filter component to the Results. The strategy should resemble the following image.
    Retention strategy
  2. In the upper-right corner, save the strategy configuration.
  3. On the right, click the arrow to open the Test run panel.
  4. In the Setting section, enter or select the following information:
    1. Data transform: Barbara
    2. For external inputs use strategy: RetentionOffers
  5. Click Save & Run.
  6. Ensure that the Results component does not contain a retention offer.
  7. On the canvas, click the Prediction and confirm that the segment for Barbara is Loyal.
    Barbara
  8. Repeat steps 16 and17 for Troy, and confirm that the segment for Troy is Churn.
    Troy
  9. Ensure that the Results component contains a retention offer for Troy.
  10. Check in the decision strategy with appropriate check-in comments.

2 Configure the Next-Best-Action Designer

  1. In the navigation pane on the left, click Next-Best-Action > Designer.
  2. Click the Engagement policy tab.
  3. In the Business structure section, click the Negotiation group in the Retain issue.
  4. Click Edit.
  5. Expand the Customer actions section.
  6. In the Applicability section of the engagement policy, click the Add icon to add an applicability condition.
    1. In the first list, ensure that Customer is selected.
    2. In the second list, in the Strategy section, select RetentionStrategy.
      Note: If the new strategy is not displayed, log out of Pega Customer Decision Hub, and then log back in.
    3. In the third list, ensure that has results for is selected.
    4. In the final list, select the High Churn Risk strategy component.
      Applicabiliy Retention
  1. Save the configuration of the Negatiation group.
  2. In the Business structure section, select the Grow > Credits cards issue and group.
  3. Click Edit.
  4. Expand the Customer actions section.
  5. In the Applicability section of the engagement policy, click the Add icon to add a new applicability condition.
    Add icon
    1. In the first list, ensure that Customer is selected.
    2. In the second list, in the Strategy section, select RetentionStrategy.
    3. In the third list, select doesn't have results for.
    4. In the final list, select the High Churn Risk strategy component.
      Applicabiliy Sales
  6. Save the configuration of the Credit cards group.
  7. In Next-Best-Action Designer, click Channels to configure the website integration.
    Channels button
  8. Click Edit.
  9. In the Triggers area, in the Real-time containers section, in the Business structure level column of the TopOffers real-time container, select All issues / All groups.
    Trigger
  10. Save the Channels configuration.

Confirm your work

  1. On the exercise system landing page, click U+ Bank to open the website.
    U Bank
  2. On the main page of the website, in the upper-right corner, click Log in to log in as a customer.
  3. Log in as Troy, who has a high churn risk, and verify that a retention offer is displayed.
    ExtraMiles tile
    Note: Allow some time for the offer to display. Subsequent offers are displayed immediately.
  1. In the upper right, click on the profile icon and log out.
  2. On the U+ Bank website, log in as Barbara, who is expected to remain loyal, and verify that a credit card offer is displayed.
    Credit card tile

This Challenge is to practice what you learned in the following Modules:

Available in the following missions:

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