Adobe Experience Platform enables you to drive coordinated, consistent, and relevant experiences for your customers no matter where or when they interact with your brand. With Real-Time Customer Profile, you can see a holistic view of each individual customer by combining data from multiple channels, including online, offline, CRM, and third party. Profile allows you to consolidate your customer data into a unified view offering an actionable, timestamped account of every customer interaction. This overview will help you understand the role and use of Real-Time Customer Profile in Experience Platform.
The relationship between Real-Time Customer Profile and other services within Experience Platform is highlighted in the following diagram:
Real-Time Customer Profile merges data from various enterprise systems and then provides access to that data in the form of customer profiles with related time series events. This feature enables marketers to drive coordinated, consistent and relevant experiences with their audiences across multiple channels. The following sections highlight some of the core concepts that you must understand in order to effectively build and maintain profiles within Platform.
A Real-Time Customer Profile is composed of a main entity, called the primary entity, and various supporting entities. In the context of Experience Platform, the primary entity is typically a profile entity, which is composed of traits, behaviors, and segment memberships of an individual person. Other entities allow the segmentation engine to utilize data outside of the primary entity of the profile, and include the following:
Since dimensional and B2B entities only exist outside the primary entity, these are only used for batch segmentation.
Dimensional and B2B entities are linked to the primary entity through schema relationships. Refer to the following documentation for more information:
Although Real-Time Customer Profile processes ingested data and uses Adobe Experience Platform Identity Service to merge related data through identity mapping, it maintains its own data in the Profile data store. The Profile store is separate from catalog data in the data lake and Identity Service data in the identity graph.
The Profile store uses a Microsoft Azure Cosmos DB infrastructure and the Platform Data Lake uses Microsoft Azure Data Lake storage.
Experience Platform provides a series of guardrails to help you avoid creating Experience Data Model (XDM) schemas which Real-Time Customer Profile cannot support. This includes soft limits that will result in performance degradation, as well has hard limits that will result in errors and system breakages. For more information, including a list of guidelines and example use cases, please read the Profile guardrails documentation.
The Experience Platform UI provides a dashboard through which you can view important information about your Real-Time Customer Profile data, as captured during a daily snapshot. To learn how to access and work with the Profile dashboard in the UI, and detailed information regarding the metrics displayed in the dashboard, refer to the Profile dashboard UI guide.
Each individual customer profile is composed of multiple profile fragments that have been merged to form a single view of that customer. For example, if a customer interacts with your brand across several channels, your organization will have multiple profile fragments related to that single customer appearing in multiple datasets. When these fragments are ingested into Platform, they are merged together in order to create a single profile for that customer.
In other words, profile fragments represent a unique primary identity and the corresponding record or event data for that ID within a given dataset.
When the data from multiple datasets conflicts (for example one fragment lists the customer as “single” while the other lists the customer as “married”) the merge policy determines which information to prioritize and include in the profile for the individual. Therefore, the total number of profile fragments within Platform is likely to always be higher than the total number of merged profiles, as each profile is typically composed of multiple fragments from multiple datasets.
A profile is a representation of a subject, an organization or an individual, composed of many attributes (also known as record data). For example, the profile of a product may include a SKU and description, whereas the profile of a person contains information like first name, last name, and email address. Using Experience Platform, you can customize profiles to use specific data relevant to your business. The standard Experience Data Model (XDM) class, XDM Individual Profile, is the preferred class upon which to build a schema when describing customer record data, and supplies the data integral to many interactions between Platform services. For more information on working with schemas in Experience Platform, please begin by reading the XDM System overview.
Time series data provides a snapshot of the system at the time an action was taken either directly or indirectly by a subject, as well as data detailing the event itself. Represented by the standard schema class XDM ExperienceEvent, time series data can describe events such as items being added to a cart, links being clicked, and videos viewed. Time series data can be used to base segmentation rules on, and events can be accessed individually in the context of a profile.
Every business wants to communicate with their customers in a way that feels personal. However, one of the challenges of delivering relevant digital experiences to customers is understanding how to tie their disconnected data together, which is often spread across different digital channels such as tablets, mobile phones and laptops. Identity Service allows you to piece together the complete picture of your customer by linking identities from multiple channels and creating an identity graph for each customer. Visit the Identity Service overview for more information.
When bringing data fragments together from multiple sources and combining them in order to see a complete view of each of your individual customers, merge policies are the rules that Platform uses to determine how data will be prioritized and what data will be used to create the customer profile.
When there is conflicting data from multiple datasets, the merge policy determines how that data should be treated and which value should be used. Through RESTful APIs or the user interface, you can create new merge policies, manage existing policies, and set a default merge policy for your organization.
To learn more about merge policies and their role within Experience Platform, please begin by reading the merge policies overview.
One of the key features of Real-Time Customer Profile is the ability to unify multi-channel data. When Real-Time Customer Profile is used to access an entity, it can supply you with a merged view of all profile fragments for that entity across datasets, referred to as the “union view” and made possible through what is known as a union schema.
To learn more about union schemas, including how to access union schemas in the UI, visit the union schema UI guide.
Adobe Experience Platform Segmentation Service produces the audiences needed to power experiences for your individual customers. When an audience segment is created, the ID of that segment is added to the list of segment memberships for all qualifying profiles. Segment rules are built and applied to Real-Time Customer Profile data using RESTful APIs and the Segment Builder user interface. To learn more about segmentation, please begin by reading the Segmentation Service overview.
Real-time input is made possible through a process called streaming ingestion. As profile and time series data is ingested, Real-Time Customer Profile automatically decides to include or exclude that data from segments through an ongoing process called streaming segmentation, before merging it with existing data and updating the union view. As a result, you can instantaneously perform computations and make decisions to deliver enhanced, individualized experiences to customers as they interact with your brand. While being ingested, the data also undergoes validation to ensure it being ingested properly and conforming to the schema upon which the dataset is based. For more information about what validation is done during ingestion, please begin by reading the data ingestion quality overview.
In order to drive coordinated, consistent, and personalized experiences for your customers across multiple channels in real time, the right data needs to be readily available and continuously updated as changes happen. Adobe Experience Platform enables this real-time access to data through the use of what are known as edges. An edge is a geographically placed server that stores data and makes it readily accessible to applications. For example, Adobe applications such as Adobe Target and Adobe Campaign use edges in order to provide personalized customer experiences in real time. Data is routed to an edge by a projection, with a projection destination defining the edge to which data will be sent, and a projection configuration defining the specific information that will be made available on the edge. To learn more and begin working with projections using the Real-Time Customer Profile API, refer to the edge projection endpoints guide.
Platform can be configured to send record and time-series data to Profile, supporting real-time streaming ingestion and batch ingestion. For more information, see the tutorial outlining how to add data to Real-Time Customer Profile.
Data collected through Adobe solutions, including Analytics Cloud, Marketing Cloud, and Advertising Cloud, flows into Experience Platform and is ingested into Profile.
Observability Insights allows you to expose key metrics in Adobe Experience Platform. In addition to Experience Platform usage statistics and performance indicators for various Platform functionalities, there are specific profile-related metrics that allow you to gain insight into incoming request rates, successful ingestion rates, ingested record sizes, and more. To learn more, begin by reading the Observability Insights API overview, and for a complete list of Real-Time Customer Profile metrics, see the documentation on available metrics.
Occasionally it may be necessary to update data in your organization’s Profile Store. For example, you may need to correct records or change an attribute value. This can be done through batch ingestion and requires a Profile-enabled dataset configured with an upsert tag. For more information on how to configure a dataset for attribute updates, please refer to the tutorial for enabling a dataset for Profile and upsert.
Data Governance is a series of strategies and technologies used to manage customer data and ensure compliance with regulations, restrictions, and policies applicable to data use.
As it relates to accessing data, data governance plays a key role within Experience Platform at various levels:
Data Governance is managed at several points. These include deciding what data is ingested into Platform and what data is accessible after ingestion for a given marketing action. For more information, begin by reading the data governance overview.
Experience Platform enables your customers to send opt-out requests related to the usage and storage of their data within Real-Time Customer Profile. For more information on how opt-out requests are handled, please see the documentation on honoring opt-out requests.
To learn more about working with Real-Time Customer Profile data using the Experience Platform UI or the Profile API, please begin by reading the Profile UI guide or API developer guide, respectively.