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Analyzing the impact of applying engagement policies

2 Tasks

20 mins

Visible to: All users
Beginner Pega Customer Decision Hub '24.1 English
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Scenario

U+ Bank is currently cross-selling on the web by presenting various credit cards to its customers. The business wants to present more personalized offers to its customers. To achieve this outcome, in the last quarter, the business applies various Eligibility, Applicability, and Suitability conditions on Actions.

The bank wants to analyze the results of these changes to see the impact of applying the applicability and suitability conditions. They also want to identify underserved customers.

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

Role User name Password
Next-Best-Action Designer DecisioningArchitect rules

Your assignment consists of the following tasks:

Task 1: Analyze the impact of applying applicability and suitability conditions

Analyze the impact of applying engagement policies by exploring Impact Analyzer results and answer the following questions:

  1. What is the value lift and engagement lift that results from applying applicability and suitability conditions for the Credit Cards group in the last quarter?
  2. What is the average value per impression after you apply all engagement policies versus applying only eligibility conditions for the Credit Cards group in the last quarter?

Task 2: Analyze the current customer engagements using Value Finder

Create and run the Value Finder simulation for the Grow issue and Credit Card group. Use the SampledCustomers_Inbound data set as the audience.

Then, inspect the result of the simulation by answering the following questions:

  1. How many customers received relevant actions, and how many received low-propensity actions?
  2. Which Applicability rules cause issues because customers receive no actions? Can you make applicability conditions less restrictive?

 

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 Analyze the impact of applying applicability and suitability conditions

  1. On the exercise system landing page, click Pega InfinityTM  to open Customer Decision Hub:
  2. Log in as a Decisioning Architect:
    1. In the User name field, enter DecisioningArchitect.
    2. In the Password field, enter rules.
  3. In the navigation pane of Customer Decision Hub, click Discovery > Impact Analyzer to open Impact Analyzer.
  4. Question: What is the value lift and engagement lift generated by applying applicability and suitability conditions for the Credit Cards group in the last quarter?
    1. In the Timeframe list, select Last quarter, and then click Apply:
      Last quarter
    2. In the How is Next-Best-Action performing against applying only eligibility criteria? experiment widget, click View more:
      View more experiment step
    3. In the All issues section, click Grow:
      Experiment - Issues selection
    4. In the group list, click Credit Cards:
      Experiment - Group selection
    5. Check the percentage values for the Value Lift and Engagement Lift:
      Detailed Value and engagement lifts for a issuegroup values
      Note: The values of the value lift and engagement lift percentage might vary depending on the instance you are using.
  1. Question: What is the average value generated per impression after you apply all engagement policies versus applying only eligibility conditions for the Credit Cards group in the last quarter?
    1. In the How is Next-Best-Action performing against applying only eligibility criteria? experiment widget, click Lift details:
      Lift details step
    2. In the Lift details window, check the average value generated per impression for Next-Best-Action and for Eligibility criteria only (with arbitration):
      Lift details details
      Note: In this case, the Value per impression is higher for Eligibility criteria only (with arbitration), which might suggest that the engagement policies are too strict. The results might vary depending on the instance that you are using.

2 Analyze the current customer engagements using Value Finder

  1. In the How is Next-Best-Action performing against applying only eligibility criteria? experiment widget, click Go to Value Finder:
    Transition from IA to VF
  2. On the Value Finder landing page, click Create to create a new simulation:
    VF Create a simulation
  3. In the Create new Value Finder simulation dialog box, complete the following details:
    1. In the Scope list, select Grow/Creditcards.
    2. In the Channel list, select Web.
    3. In the Audience list, select SampledCustomers_Inbound.
    4. In the Name field, click the Edit icon, enter Credit Cards Test, and then click Submit.
  4. Click Submit to run the simulation.
    Note: In the current environment, the simulation run can take between 3 and 5 minutes. Wait until you see that the simulation status is completed.
  1. Click Refresh to display the simulation.
  2. When the simulation run is complete, click on the Credit Card Test simulation.
    Simulation ready
  3. Question: How many customers received relevant actions, and how many received low-propensity actions?
    1. In the Customer engagement after arbitration pie chart, check the number of customers in the given categories:
      Chart 1
      Note: In this case, the number of customers who received relevant actions is 334, and the number of customers who received low-propensity actions is 3. However, the results may vary depending on the instance you are using.
  1. Question: Which Applicability rules cause issues due to which customers receive no actions? Can you make applicability conditions less restrictive?
    1. Open the No actions after applicability category:
      no actions after applicability
    2. Click Start simulation to begin a detailed simulation:
      Customer categories - start simulation
      Note: In the current environment, the simulation run can take between 2 and 3 minutes. Wait until you see that the simulation status is completed.
    3. When the simulation run is complete, click View:
      view simulation
    4. In the Analysis of engagement policies tab, click Grow/Creditcards:
      Note: The Customers not passing column shows how many customers do not pass the engagement policies stage.
    5. In the Where are these customers not passing applicability policies section, click Group policies:
      engagement policies 97 customers
    6. In the Group policies section, expand the Customer Actions section to see the details about the engagement policies:
      last screen - results
      Note: In this case, 83 customers do not pass the applicability condition, which checks that the customer should not have any credit cards. Can you make applicability conditions less restrictive? Ultimately, this determination is a business decision. If the business thinks that customers can receive certain cards offers in combination with other offers, then this global group-level condition can be less restrictive.

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


Available in the following mission:

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