Creating an interaction history summary data set
Simplify decision strategies by creating data set records for interaction history summaries. These data sets aggregate interaction history to limit and refine the data that strategies process.
Use interaction history summaries to filter customer data and integrate multiple arbitration and aggregation components into a single import component. For example, you can create a data set that groups all offers that a customer accepted within the last 30 days and use that data set in your strategy to avoid creating duplicate offers.
- In the header of Dev Studio, click .
- Click Create.
- In the Data Set Record Configuration section, define the data
set:
- In the Label field, enter the data set label.The identifier is automatically created based on the data set label.
- Optional: To change the automatically created identifier, click Edit, enter an identifier name, and then click OK.
- In the Type list, select Summaries.
- In the Label field, enter the data set label.
- In the Context section, specify the ruleset, applicable Strategy Result class, and ruleset version of the data set.
- Click Create and open.
- In the Data source list, select one of the following
types:
- Data set
- Data flow
- Choose the data source from the list, depending on the data type that you selected in the previous step.
- In the Group by section, select the properties by which you want to group the data.
- In the Aggregates section, add aggregates, and then specify when
conditions for the aggregates, if applicable:
- Click Add aggregate.
- In the Name field, enter the existing property (for the aggregate output).
- In the Function field, specify the aggregate function.
- In the Time window list, specify the time span for which you
want to aggregate data:
- Select All time option, to aggregate data from the entire interaction history.
- Select Last, and then specify the time window, to aggregate data from a specific time period.
- Optional: To add when conditions for the aggregates, in the Condition section, click an empty field, and then specify the when condition.
- Optional: To specify the aggregation start time, in the Start aggregating as
of section:
- Click The first record in the source radio button to start aggregating from the first record.
- Click A defined date radio button to start aggregating from a date that you specify.
- Optional: To further limit the data that the data set aggregates, in the Conditions section, define the filter conditions.
- Click Save.
- Optional: To save processing time, turn on preaggregation for the new data set:
- In the header of Dev Studio, click .
- Next to the data set for which you want to turn on preaggregation, click . Preaggregated data sets save processing time because they include the latest interactions. Data sets that are not preaggregated do not include the latest interactions and therefore they query the database.
- Applying sample scripts for archiving and purging
The interaction history tables contain transactional data which may grow fast. By using the sample scripts, the users can archive the data in the archiving database and delete (purge) the records from the source database. The scripts allow you to move the FACT table records, merge the Dimension records, and delete the records from the FACT table. Before you use any of the scripts, back up the source and target interaction history tables and create indexes on the columns. Indexes improve performance when you read data from the archived tables.
- Interaction History methods
You can use a rule-based API to associate known customer IDs with IDs that are generated by external interactions through different channels and devices or to separate them.
- Accessing interaction results
Ensure that you stay up to date with recent interaction results by filtering and analyzing the interaction history records.
- Extending Interaction History
Learn about the underlying configuration of Interaction History and how to extend it to match your business objectives.
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