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).
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In the navigation pane of Prediction Studio, click .
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Click New.
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In the New data
set window, specify the following parameters:
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Click
Create.
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On the
Aggregates
tab, in the
Aggregate
section, click
Add aggregate.
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In the
Output
column specify the aggregate name, for
example,
.RecentlyAcceptedOffer.
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In the
Function
column, select a mathematical function to use to
extract the data, for example,
Last, to extract the most recent
records.
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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:
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Click
Add condition.
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Specify the condition logic by specifying the following properties, starting from
the left-most field:
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The condition name, for example,
A.
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The property by which to filter the Interaction History data, for example,
.pyOutcome.
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The logical operator, for example,
=.
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The property value to filter out, for example,
"Accept".
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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.
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Click Save.
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To test the summary data set, in the header of
Prediction Studio
click
Run test.