Adobe Experience Platform Segmentation Service provides a user interface and RESTful API that allows you to create audiences through segment definitions or other sources from your Real-Time Customer Profile data. These audiences are centrally configured and maintained on Platform, and are readily accessible by any Adobe solution.
This document provides an overview of Segmentation Service and the role it plays in Adobe Experience Platform.
You should understand the following key terms used throughout this document:
Segmentation is the process of defining specific attributes or behaviors shared by a subset of profiles from your profile store to distinguish a marketable group of people from your customer base. For example, in an email campaign called “Did you forget to buy your sneakers?”, you may want an audience of all users who searched for running shoes within the last 30 days, but who did not complete a purchase.
Once an audience has been conceptually defined, it is built in Experience Platform. Typically, audiences are built by the marketer or audience specialist although some organizations prefer they be created by their marketing department, in collaboration with their data analysts. Upon reviewing the data being sent to Platform, the data analyst can create the audience in two ways - either by creating a segment definition by selecting which fields and values will be used to build the rules or conditions of the audience, or by composing an audience using the Audience Composition.
Audiences can be created in two different ways on Adobe Experience Platform - either directly composed as audiences or through Platform-derived segment definitions.
When directly composing an audience on Platform, you can use Audience Composition. To learn how to use Audience Composition to create an audience, please read the Audience Composition guide for more information.
Whether created using the API or using the Segment Builder, segment definitions are ultimately defined using Profile Query Language (PQL). This is where the conceptual segment definition gets described in the language built to retrieve profiles meeting the criteria. For more information, see the PQL overview.
To learn how to create and use segments in the Segment Builder (the UI implementation of Segmentation Service), see the Segment Builder guide.
For information on building segment definitions using the API, see the tutorial on creating segment definitions using the API.
In the event a schema is extended, all future uploads must update newly added fields accordingly. For more information on customizing Experience Data Model (XDM), visit the Schema Editor tutorial.
Additionally, if an Experience Event expiration value is enabled on the dataset, this could affect the membership of the created segment definition. Please read the guide on Experience Event expirations for more information on how this feature can affect segmentation.
Platform currently supports three methods of evaluating audiences: streaming segmentation, batch segmentation, and edge segmentation.
Streaming segmentation is an ongoing data selection process that updates your audiences in response to user activity. Once an audience has been built and saved, the segment definition is applied against incoming data to Real-Time Customer Profile. Additions and removals to the audience are processed regularly, ensuring your target audience remains relevant.
To learn more about streaming segmentation, please read the streaming segmentation documentation.
As an alternative to an ongoing data selection process, batch segmentation moves all profile data at once through segment definitions to produce corresponding audiences. Once created, the resulting audience is saved and stored so that you can export it for use.
Batch audiences are automatically evaluated every 24 hours. If you want to evaluate a batch audience on demand, you can use a segment job. To learn more about segment jobs, please read the segment jobs documentation.
Edge segmentation is the ability to evaluate segments in Platform instantaneously on the Edge Network, enabling same-page and next-page personalization use cases.
To learn how to access an exported audience, see the segment definition evaluation tutorial.
Segment definition metadata facilitates indexing in the event any of your audiences are to be reused and/or combined.
Composing a segment definition (through either the API or Segment Builder) requires that you to define a name and merge policy.
When creating a new segment definition, you are required to provide a name. The segment definition name is used to identify a particular segment definition among the collection built by Segmentation Service. Segment definition names should therefore be descriptive, concise, and unique.
When planning a segment definition, remember that segment definitions can be referenced from, and combined with, any other segment definition. When selecting a name, consider the possibility that your segment definition may contain reusable portions.
Merge policies are rules used by Profile to determine how data will be prioritized and combined into a unified view under certain conditions.
If a merge policy is not defined, the default Platform merge policy is used. If you would rather use a merge policy specific to your organization, you can create your own and mark it as your organization’s default.
More information about merge policies can be found in the merge policies guide.
Estimation of audience sizes is based on the organization’s default profile merge policy.
In addition to name and merge policy, Segment Builder offers you an additional description metadata field where you can summarize your segment definition’s purpose.
Segment definitions can be configured to continually generate an audience on an ongoing basis by combining streaming data ingestion with any of the following advanced segmentation features:
These advanced features are discussed in more detail in the following sections.
A standard user journey is sequential in nature. Adobe Experience Platform allows you to define an ordered series of audiences to reflect this journey therefore capturing sequences of events as they occur. You can arrange events into their desired order by using the visual event timeline in the Segment Builder.
An example of a customer journey that would require sequential segmentation would be product view > product add > checkout > No purchase.
Dynamic segmentation solves the scalability problems marketers traditionally face when building audiences for marketing campaigns.
Unlike static segmentation which requires you to explicitly and repeatedly capture every possible use case, dynamic segmentation uses variables to build the rule logic and dynamically express relationships.
To illustrate the value of this advanced segmentation feature, consider a data architect collaborating with a marketer to identify customers who made purchases outside their home state.
Static segmentation requires you to define individual segments with a unique home state attribute, before filtering for purchase events that do not equal the home state. An explicit segment definition of this type would read “I’m looking for people from Utah where the state of their purchase is not Utah”. Creating an audience using this method requires you to define one segment definition for every US state, for a total of 50 segments.
As a result of the different segment definition combinations that inevitably arise as you scale, the manual process required for static segmentation becomes more time consuming, reducing your overall efficiency.
By assigning a variable to the purchase state attribute, your dynamic segment definition simplifies to “find me a purchase where the state of that purchase is not equal to the customer’s home state”. Doing so allows you to then consolidate 50 static segments into a single dynamic segment definition.
With the advanced multi-entity segmentation feature, you can extend Real-Time Customer Profile data with additional data based on products, stores, or other non-person, also known as “dimension” entities. As a result, Segmentation Service can access additional fields during segment definition as if they were native to the Profile data store. Multi-entity segmentation provides flexibility when identifying audiences based on data relevant to your unique business needs. For more information, including use cases and workflows, refer to the multi-entity segmentation guide.
Segmentation Service supports a variety of primitive and complex data types. Detailed information, including a list of supported data types can be found in the supported data types guide.
Segmentation Service provides a consolidated workflow to build audiences from Real-Time Customer Profile data.
For more information on using the Segmentation Service UI, please read the Segmentation Service UI overview.
To learn how to compose audiences in the UI, please read the Audience Composition guide. To learn how to define segments definitions in the UI, see the Segment Builder guide. For information on building segment definitions using the API, see the tutorial on creating segment definitions using the API.