You can create an Interaction History summary data set that is based on your input criteria. For example, you can create a summary of all Interaction History records for a customer that shows all accepted offers within the last 30 days. You can use Interaction History summaries to filter out irrelevant offers (for example, do not display this advertisement to a specific customer if that customer has already viewed it within this month).
- In the navigation pane of Prediction Studio, click .
- Click New.
In the New data
set window, specify the following parameters:
- Name – The name of the new data set, for example, Recently Accepted Offers.
- Apply to – The
application class of the data set, for example,
Important: The applicable class must be derived from the Data-pxStrategyResult class of your application.
- Click Create.
- On the Aggregates tab, in the Aggregate section, click Add aggregate.
- In the Output column specify the aggregate name, for example, .RecentlyAcceptedOffer.
- In the Function column, select a mathematical function to use to extract the data, for example, Last, to extract the most recent records.
- In the From Interaction History, select an Interaction History property to use to group your data, for example, pyGroup.
To limit the data that the summary data set aggregates, in the
section, perform the following actions:
- Click Add condition.
- Specify the condition logic by specifying the following properties, starting from
the left-most field:
- The condition name, for example, A.
- The property by which to filter the Interaction History data, for example, .pyOutcome.
- The logical operator, for example, =.
- The property value to filter out, for example, "Accept".
- In the Where field, type a condition logic that you want to apply to filter data, for example A, A AND B, A NOT B, and so on.
- Click Save.
- To test the summary data set, in the header of Prediction Studio click Run test.