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.
- Optional: To limit the data that the summary data set aggregates, in the
Filter 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.