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Using sampled production data to test the performance of proposition filters

Updated on September 15, 2022

You can use sampled production data to improve the performance of your proposition filters by testing them against simulated audiences. In this way, you can check how many potential actions are filtered out by each component of the filter, and discover if a particular filter criterion is too broad or too narrow for your requirements.

Pega Customer Decision Hub
  1. In your Business Operations environment, in the navigation pane of Dev Studio, click Records.
  2. Expand the Decision category, and then click Proposition Filter.
  3. In the Proposition Filter tab, open or create an instance of the Proposition Filter rule:
    • To open an existing instance of the Proposition Filter rule, in the Instance name column, select one of the available rules, for example, EligibleSalesOffers.
    • To create an instance of the Proposition Filter rule, click Create.
  4. In the tab of the selected Proposition Filter rule, click ActionsAudience simulation.
  5. In the Audience simulation section, select or create a simulation with which you want to test the proposition filter:
    • To use an existing simulation, select it in the Simulation list.
    • To create a new simulation, click Create simulation, and then select the audience to use for the simulation. If the proposition filter criteria include a When condition, or a strategy that requires parameters, select the Strategy rule that the simulation uses to evaluate the condition. Confirm your choice by clicking Run.
    For example:
    Sample audience simulation results
  6. In the Show population that passed as list, select whether the results should be displayed as a percentage of the starting population, or as a count of audience members.
  7. After the simulation test finishes, analyze the results to see what part of the audience would receive each action according to the current proposition filter criteria:
    • To view the results for a specific group, select the group in the Group list.
    • To view the results for a specific proposition, in the Proposition section, click the proposition name, and then analyze the details on the right side of the screen.
    For each component of the Proposition Filter rule, the simulation test shows percentage values that indicate the percentage of the selected audience that receives the proposition based on the current criteria. For example, if the result for a criterion that checks if the proposition is active is 100.00%, then no audience members were filtered out by this component.
Result:

You have run a simulation to test how the changes that you made impact your proposition filter. You can now decide whether you want to implement the changes on a live system.

To view the main process outline for this tutorial, see Configuring the system for running simulations of decision strategies.

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