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For global multi-brand organizations, the ability to view aggregated customer profiles across separate BlueConic tenants provides a valuable 360º view of all your businesses.

Watch the video: Introducing the BlueConic Aggregated Data Manager

Overview of the BlueConic Aggregated Data Manager

The BlueConic Aggregated Data Manager (ADM) is designed for organizations with multiple businesses, regions, or brands running BlueConic on multiple tenants who want to have a single view of all customers across brand or regional tenants. This centralized dataset enables you to surface insights and perform modeling across tenants, while ownership over activation of that data can remain with individual businesses, regions, or brands. For example, each brand can manage customer segments and connections to their specific systems for their use cases, but a centralized analytics team can calculate a CLV score across all brands for an individual customer.

The Aggregated Data Manager is a super-tenant that contains aggregated customer profiles that show customer data when a company is using multiple BlueConic tenants to allow for a single view of all profiles across tenants.

The Aggregated Data Manager is updated and aggregated on a recurring schedule. You can then run connections and AI Workbench notebooks against this data for activation and analysis. ADM profiles can be used with standard BlueConic connections, insights, dashboards, and AI notebook plugins.

ADM Example

In the example shown here, a multi-brand company has three separate BlueConic tenants. A customer's matching sub-profiles in Brands 1 and 2 are rolled up into a single aggregated profile in the ADM super-tenant, using standard profile merging rules. This illustration shows an uncombined profile in Brand 3 that is not added to the aggregated profile in the ADM. It remains available in its brand's sub-tenant. All profiles from sub-tenants remain available on their separate tenants and are also available to the ADM (for cross-brand analysis in AI Workbench notebooks, for example).

Benefits of running the Aggregated Data Manager

1. It creates a single view of your customer across brands, while maintaining regional hosting and data separation in each region or brand's unique tenants.
2. You can develop analytics and reporting across regions or brands (e.g. product category-level cohort analyses, longitudinal spending trends, etc.).
3. With the ability to create models and execute scores across regions or brands, you can push individual profile scores back to the individual sub-tenants.

Aggregating profiles across brands

BlueConic uses profile properties that are unique identifiers for aggregating profile data in the ADM. The process of aggregating profiles uses the profile property's specified merge strategy. For example, if a profile property uses the “keep both” values merge strategy, the aggregated profile keeps both values in the aggregated profile. Profile properties that use the “most recently updated value“ rule retain only the most recent value in the aggregated profile. ADM profile properties are separate from the properties on the sub-tenants.

How are profiles from sub-tenants combined by ADM?

The ADM examines and matches profiles across sub-tenants in BlueConic and uses standard profile merging rules for identity resolution, in order to create aggregated profiles. In the following example, the profile properties email and customerId are unique identifiers used in the ADM for aggregating profile data. 

In this example, the ADM aggregates three sub-profiles by matching and merging profiles in this way:

1. Profile1 is matched with profile3 because they contain the same email.
2. Profile2 is matched with profile3 because they contain the same customerId.
3. As a result, all three profiles are combined into a single, aggregated profile for the parent brand on the ADM. (The individual profiles continue to exist on their brand's sub-tenants.)

Tips to keep in mind when aggregating profile data:

• Be aware that profile properties marked as unique identifiers are used differently on sub-tenants and the ADM.
• Create unique identifiers judiciously and start with one or just a few properties.
• Make sure unique identifier properties represent unique values.
• Be aware that unique identifier properties are combined as OR for aggregation. In the example above all 3 profiles are aggregated while 2 profiles only have a value for a single unique identifier property.

Special ADM profile properties

ADM profiles automatically contain special profile properties that contain aggregation information. By default, these profile property are not defined. These can be created manually or by installing the profile_composition plugin.

• sub_profile_ids: Aggregation profiles use this profile property, which contains the profile ids of the sub-tenant profiles.
• sub_tenant_id: For both sub-tenant profiles and aggregated profiles, this property contains the id of the sub tenant where the profile(s) originated. Note: This property is only filled when specified in the tenant configuration of the sub-tenant by BlueConic during ADM setup.
• sub_tenant_name: for sub and aggregation profiles this contains the name of the sub tenant from where the profile(s) originated. Note: This property is only filled when specified in the tenant configuration of the subtenant by BlueConic during ADM setup.

Example ADM profile property

Here you can see the profile property settings of the profile property that tracks data on profiles combined to create aggregated profiles.

Viewing aggregated profiles

To view aggregated profiles in the ADM, you can extend the standard BlueConic Profile tab using the profile composition plugin, which shows the sub-profiles that make up the aggregated profiles. Contact your BlueConic Customer Success Manager to install the profile composition plugin. https://plugins.blueconic.net/profile_composition/index.xml

Access to the Aggregated Data Manager feature

Contact your BlueConic Customer Success Manager to learn more about the ADM and to learn how you can use it to aggregate your customer data across brands.