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Delayed learning of adaptive models

Updated on July 5, 2022

Delayed learning is a way of updating adaptive models by providing input about customer decisions to the Adaptive Decision Manager (ADM) server. ADM collects data about customer behavior that can be used to predict the next best action for customers.

Adaptive models are scoring models built in a Pega Platform application that can capture and analyze customer responses in real time. Adaptive models identify the most suitable proposition for a customer or determine the proposition that the customer is most likely to accept.

Overview of delayed learning

You can use delayed learning of adaptive models in outbound campaigns where the response from a customer is not immediate. Delayed learning is a two-step process for which you need instances of the Data Flow rule and the Strategy rule. First, you need to collect and store data for later response capture. Next, you need to capture responses for previous decisions. The process is governed by instances of the Data Flow rule. Instances of the Strategy rule are required to set the correct values for adaptive models and the outcomes.

For a better understanding of this concept, the following rule instances serve as an example:

  • DecisionFlow data flow
  • ResponseFlow data flow
  • MakeDecision strategy
  • Response strategy

Data storing for later response capture

As a Decision Architect, you configure the delayed learning options in the Strategy shape of a data flow. In this example, the DecisionFlow data flow references the MakeDecision strategy.

DecisionFlow data flow
The data flow consists of three shapes: Bank Payments data set, Make Decision strategy, and Phones abstract shape.

The strategy uses adaptive models to collect data for a particular offer on a specific channel and direction. To store data for later response capture, the strategy must operate in the Make decision and store data for later response capture mode.

Properties of the Strategy shape in the DecisionFlow data flow
The strategy shape references the Make Decision strategy and is set to store data for later response capture.

During the execution of this Strategy shape, all the field names that are marked as predictors in the ADM models are collected and stored in the pxDecisionResults data set by means of the pxDelayedLearningFlow data flow. Along with predictor information, this data set stores Interaction ID and Subject ID to uniquely identify all the records. Apart from this, the pxDelayedLearningFlow data flow captures a snapshot of the Make Decision strategy results and stores them in the Event Store data set.

Note: Storing results in the Event Store data set is necessary to capture responses for previous decisions without providing an Interaction ID.
pxDelayedLearningFlow data flow
Two paths go from the decision result shape: through event summary to event store and to decision result data set.

To save the snapshot of the MakeDecision strategy results, the Convertshape of the pxDelayedLearningFlow data flow provides mapping between the properties in the strategy result class and the Event Store properties.

Properties in the Convert shape of the pxDelayedLearningFlow data flow
For example, the Subject ID in the decision results is mapped to the Customer ID in the event summary.

When the MakeDecision strategy is configured in such a way, the adaptive model's learning process can begin.

Response capture for previous decision

When you decide to use adaptive models to select offers based on the adaptive model output in subsequent outbound campaigns, you need to use a data flow. In this example, the ResponseFlow data flow that references Response strategy.

ResponseFlow data flow
The flow goes from Bank Payments through Response Strategy and branches into Interaction History and Adaptive Analytics.

The Response strategy must operate in the Capture response for previous decision mode.

Properties of the Strategy shape in the DecisionFlow data flow
The strategy shape references the Response strategy and is set to capture response for previous decision.

During the execution of this Strategy shape, the retrieval of previous decision results depends on the following options:

Identified by interaction ID
When you select this option and provide an Interaction ID, the Subject ID and Interaction ID fields that are mapped in the strategy inputs, are used to uniquely identify particular records in the pxDecisionResults data set. Data from the pxDecisionResults data set is embedded in the strategy results and sent to the Adaptive Analytics data set to update ADM models.
In the past
When you select this option and specify a time period, the Event Store data set is queried with the Subject ID of the customer to retrieve a snapshot of data from the specified time period, for example:
PropertyValue
pxCustomerID4
pxGroupID4
pxEventID-5375906222368414386
pxEventTypeData-Decision-Results
pxDescriptionOffered : /loan/home loan/Interest 8%
pxCaptureTime2016129%082839 GMT
Then, the Event ID from the snapshot and the Subject ID of the customer are used to uniquely identify particular records in the pxDecisionResults data set. Data from the pxDecisionResults data set is embedded in the strategy results and sent to the Adaptive Analytics data set to update ADM models.

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