Target data targeting-data

Create queries creating-queries

Select data selecting-data

A Query activity lets you select basic data to build the target population. For more on this, refer to Creating a query.

You can also use the following activities to query and refine data from the database: Incremental query, Read list.

It is possible to collect additional data to be forwarded and processed throughout the workflow’s life cycle. For more on this, refer to Adding data and Editing additional data.

Edit additional data editing-additional-data

Once additional data has been added, you can edit it or use it to refine the target defined in the query activity.

The Edit additional data… link lets you view the added data and modify it or add to it.

To add data to the previously defined output columns, select it in the list of available fields. To create a new output column, click the Add icon, then select the field and click Edit expression.

Define a calculation mode for the field to be added, such as an aggregate for example.

The Add a sub-item option lets you attach computed data to the collection. This lets you select the additional data from the collection or define aggregate calculations on collection elements.

The sub-elements will be represented in the sub-tree of the collection they are mapped to.

Collections are shown in the Collections sub-tab. You can filter the collected elements by clicking the Detail icon of the selected collection. The filter wizard lets you select the collected data and specify the filtering conditions to be applied to the data in the collection.

Refine the target using additional data refining-the-target-using-additional-data

The additional data collected can enable you to refine data filtering in the database. To do this, click the Refine the target using additional data… link: this lets you over-filter on the added data.

Homogenize data homogenizing-data

In Union or Intersection type activities, you can choose to keep only shared additional data to keep the data consistent. In this case, the temporary output worktable of this activity will contain only the additional data found in all inbound sets.

Reconciliation with additional data reconciliation-with-additional-data

During the data reconciliation phases (Union, Intersection, etc. activities), you can select the columns to be used for data reconciliation from the additional columns. To do this, configure a reconciliation on a selection of columns and specify the main set. Then select the columns in the lower column of the window, as shown in the following example:

Create subsets creating-subsets

The Split activity lets you create subsets on criteria defined via extraction queries. For each subset, when you edit a filter condition on the population, you will then access the standard query activity which lets you define the target segmentation conditions.

You can split a target into several subsets using only additional data as filtering conditions, or in addition to target data. You can also use external data if you have purchased the Federated Data Access option.

For more on this, refer to Creating subsets using the Split activity.

Segment data segmenting-data

Combine several targets (Union) combining-several-targets--union-

The union activity lets you combine the result of several activities within one transition. Sets do not necessarily have to be homogeneous.

The following data reconciliation options are available:

Extract joint data (Intersection) extracting-joint-data--intersection-

The intersection lets you recover only the lines shared by the populations of inbound transitions. This activity shall be configured like the union activity.

Furthermore, it is possible to keep only a selection of columns, or only the columns shared by the inbound population.

The intersection activity is detailed in the Intersection section.

Exclude a population (Exclusion) excluding-a-population--exclusion-

The exclusion activity lets you exclude the elements of a target from a different target population. The output targeting dimension of this activity will be that of the main set.

When necessary, it is possible to manipulate inbound tables. Indeed, to exclude a target from another dimension, this target has to be returned to the same targeting dimension as the main target. To do this click the Add button and specify the dimension change conditions.

Data reconciliation is carried out either via an identifier, changing axis, or a join. An example is available in Using data from a list: Read list.

Create subsets using the Split activity creating-subsets-using-the-split-activity

The Split activity is a standard activity which lets you create as many sets as necessary via one or several filtering dimensions, as well as generating either one output transition per subset or a unique transition.

The additional data conveyed by the inbound transition can be used in the filtering criteria.

To configure it, you first need to select criteria:

Then, we need to add new subsets:

Once subsets have been created, by default the split activity shows as many output transitions as there are subsets:

You can group all these subsets into a single output transition. In this case, the link to the respective subsets will be visible in the segment code, for example. To do this, select the Generate all subsets in the same table option.

For example, you can place a single delivery activity and personalize the delivery content based on the segment code of each recipient set:

Subsets can also be created using the Cells activity. For more on this, refer to the Cells section.

Use targeted data using-targeted-data

Once the data has been identified and prepared, it can be used in the following contexts:

Data Management data-management

In Adobe Campaign, the Data Management combines a set of activities for solving complex targeting issues by offering more efficient and flexible tools. This lets you implement consistent management of all communications with a contact using information related to their contracts, subscriptions, reactivity to deliveries, etc. Data Management lets you track the data life cycle during segmentation operations, in particular:

In order to implement these operations, Adobe Campaign offers:

Enrich and modify data enriching-and-modifying-data

In addition to the targeting dimension, the filtering dimension lets you specify the nature of the collected data. Refer to Targeting and filtering dimensions.

The identified and collected data can be enriched, aggregated and manipulated to optimize target construction. To do this, in addition to the data manipulation activities detailed in the Segmenting data section, use the following: