[GA4] Google Analytics account structure

This business has one website and one Google Ads account. The business does not need to separate data according to region or line of business.

Google Analytics Standard account structure

• Account: One account. Data is owned by a single legal entity.
• Property: One property for the website
• Data streams: One data stream. If the business also has an app, a separate data stream for the app.

Principles applied

This organization has one website and one Google Ads account.

Business requirements

The account structure needs to address the following requirements:

• Students review course offerings, register for courses, and perform and manage course work online.
• The marketing team needs to be able to create audiences for remarketing and prospecting.
• Analysts want to understand cross-device usage and whether there's a need for a mobile site or app.

Google Analytics Standard account structure

• Account: One account. Data is owned by a single legal entity.
• Property: One property for each logical user base (institutional site).
• Data streams: One data stream for the institutional website.

Principles applied

This umbrella corporation has multiple geographic regions and each region is its own business entity. Each region has its own website, marketing team, and Google Ads account. The umbrella corporation also has an app (available for iOS and Android).

Business requirements

The account structure needs to address the following requirements:

• The umbrella corporation needs to have a global view of data from all business entities.
• There is no need for each business entity to have legal ownership of its data.
• Each business entity wants to understand how the user journey moves across the website and app.
• Each business entity needs to compartmentalize its data.
• The marketing team for each business entity uses the Google Ads - Analytics link to create and share audiences, and uses the audiences for bidding in Google Ads.

Google Analytics Standard account structure

• Account: One account. Data is owned by a single legal entity.
• Property: One property for a single logical user base
• Data streams: One data stream for the website. One data stream for each version of the app.

Google Analytics 360 account structure

• Account: One account. Data is owned by a single legal entity.
• Property: One property for a single logical user base
• Subproperties: One subproperty for each business entity that has a need to compartmentalize data
• Data streams: One data stream for the website. One data stream for each version of the app.

Principles applied

This business has one global brand website and a separate marketing site for each game title. It sells multiple game titles in the Play Store and App Store.

Business requirements

The account structure needs to address the following requirements:

• Collect first-party data from websites and apps to create audiences and inform media buying.
• A separate environment for development, staging, and production of each game.

Google Analytics Standard account structure

• Account: One account. Data is owned by a single legal entity.
• Property: One property for each logical user base (global-brand site; each game title's marketing site and app).
• Data streams: One data stream for the global-brand website. One data stream for each marketing site, and one for each corresponding version of the app.

Google Analytics 360 account structure

• Account: One account. Data is owned by a single legal entity.
• Property: One property for each logical user base (global-brand site; each game title's marketing site and app).
• Roll-up property: One roll-up property pulling together data from all separate source properties for a holistic view
• Data streams: One data stream for the global-brand website. One data stream for each marketing site, and one for each corresponding version of the app.

Principles applied

This business has one corporate website to provide information to clients and to generate leads that require offline interaction to finalize contracts (e.g., phone, mail, point-of-sale). Each subsidiary has its own website, a separate marketing team, and its own Google Ads account.

One subsidiary (auto) also has an app.

Business requirements

The account structure need to address the following requirements:

• Data is owned by a single business entity in one location.
• Data from the corporate site needs to be available for analysis to improve lead generation and content optimization.
• Each subsidiary needs to compartmentalize its data in order for the related marketing team to create audiences, and track conversions associated with a single Google Ads account.

Google Analytics Standard account structure

• Account: One account. Data is owned by a single legal entity.
• Property: One property for each logical user base (corporate site; each subsidiary's site and app).
• Data streams: One data stream for the corporate website. One data stream for each subsidiary site, and one for each corresponding version of the app.

Google Analytics 360 account structure

• Account: One account. Data is owned by a single legal entity.
• Property: One property for all sites and apps (corporate site; each subsidiary's site and app).
• Subproperties: One subproperty for each for each logical user base (corporate site; each subsidiary's site and app).
• Data streams: One data stream for the corporate website. One data stream for each subsidiary site, and one for each corresponding version of the app.

Principles applied

This company has multiple brands, each with a desktop website, a mobile site, and an app. Each brand has its own marketing team and advertising accounts.

Business requirements

The account structure needs to address the following requirements:

• Data needs to be analyzed by country.
• Each marketing team needs to build its own audiences and attribute key events to its linked advertising accounts.

Google Analytics Standard account structure

• Account: One account. Data is owned by a single legal entity.
• Property: One property for each logical user base (corporate site; each brand's site and app).
• Data streams: One data stream for the corporate website. One data stream for each brand site, and one for each corresponding version of the app.

Google Analytics 360 account structure

• Account: One account. Data is owned by a single legal entity.
• Property: One property for each logical user base (corporate site; each brand's site and app).
• Roll-up property: One roll-up property to view all entity and geographical data sets together.
• Data streams: One data stream for the corporate website. One data stream for each brand site, and one for each corresponding version of the app.

Principles applied

• Concepts and definitions
• Best practices
• Data streams
• Search Console integration
• Customize what reports are visible
• Data hygiene
  • Exclude internal IP traffic
  • Remove unwanted referrals
  • Set up cross-domain measurement
• Data transformations
• User permissions and user roles
• 360-specific features: subproperties and roll-up properties
  • Subproperties
    • Data governance
    • User governance
  • Roll-up properties
  • Cost considerations
• Examples with subproperties and roll-up properties
  • Enterprise company with several complementary lines of business
  • Parent company with several brands
  • Global enterprise with regions and subregions
• Linking: Google Ads, SA360, and DV360
  • Google Ads
  • Search Ads 360
  • Display and Video 360

Subproperties are a new kind of Google Analytics 4 property available to Google Analytics 360 accounts. They allow you to create a subset of the data that’s in a source property. Subproperties replace the need for views. For example, you can create a subproperty that has a subset of the data that’s in your source property, and provide certain users with access to just that subproperty. In addition, subproperties provide capabilities around data hygiene, data governance, user governance, and feature governance that significantly increase the benefit of using GA4 for larger businesses and enterprises.

You can create a subproperty from any source property, but cannot create a subproperty from a roll-up property. Subproperties have a one-to-one relationship with a source property.

Data governance

One of the biggest use cases for subproperties is data governance - controlling what data is included or excluded from a property. Subproperties allow you to filter data in or out in order to create the set of data needed for a specific audience or use case. This allows for better organization of your data to make it more easily accessible to certain audiences.

Separating data sets allows for each group to access their information more quickly and easily, even if they could have achieved the same thing with a little more filtering in the source property. Subproperties allow you to achieve this with import and export filters from a source property to a subproperty for these types of use cases.

Data can be filtered into a subproperty using any event or custom dimension collected in the source property.

User governance

Another use case for subproperties is for user governance needs. An example of this would be if you have strict company policies stating that one region (for example, North America) can see a certain subset of data related to their region, but another region (for example, South America) should not have any access to the data. Using subproperties, you can restrict data for each region within its own property so that there is no access outside of the appropriate region.

This line of thinking similarly applies to lines of business that need to keep their data separate for their own operating needs, or separate data between the marketing site and the in-product experience, if your company has reasons that one team should not see the data of another team.

If you do not need to restrict access to data, but instead just need to point a certain subset of users to certain data sets, report customization and report collections may be a better solution. For example, you could create a collection of reports specifically tailored to the marketing team so they can more easily navigate to the data relevant to them. These features help to organize data in an easy-to-access format for specific audiences and come at no additional cost.

A roll-up property contains data from two or more properties. A roll-up property can include data from ordinary properties and subproperties, but not other roll-up properties. They enable a broader view of a business across products, brands, or regions by bringing together data from multiple properties within the same account. Roll-up properties in GA4 support similar use cases.

Roll-up properties function in much the same way as any other property. Each roll-up property has its own quota for custom dimensions, custom metrics, user properties, and more. All settings are controlled from within the roll-up property (roll-up properties do not inherit settings from their source properties), and are specific to the needs of the roll-up property and roll-up user base.

Each event that is sent to a subproperty or a roll-up property is processed again, which incurs an additional cost to the 360 account. Each additional event hit is charged at half the rate of the initial event hit. In other words, each subproperty or roll-up property hit costs 0.5 of an event hit.

To help you get a better understanding of how your setup may impact your billing, you can use a new feature called “Bill Preview”, available to Google Analytics Certified Partners to help their customers get a better understanding of potential GA4 360 costs.

• Enterprise company B: 1 account
  • Product line D (home insurance): 1 property
  • Product line E (car insurance): same property as D
  • Product line F (life insurance): same property as D & E

In this case, the enterprise company has 1 account with 1 source property. While there are different lines of business which may need to analyze data separately, the products are complementary and there is often a need to analyze multiple products together, so they have decided to send all product data into the same source property. The specific product teams, however, need to be able to analyze their data separately. Due to high volumes of traffic in the overall property, they have elected to create subproperties for each line of business.

• Parent company: 1 account
  • Brand X (automotive): 1 property
  • Brand Y (household goods): 1 property
  • Brand Z (consumer electronics): 1 property

In this case, the parent company has 1 account with 3 source properties, one for each brand. Each individual brand operates separately and needs to analyze their data separately, so they each have their own source property. The parent company, however, would like to see all of their brands rolled up into a single property so that they can have a good understanding of total users, total revenue, and more. In this case, the parent company will create a roll-up property with all 3 brand properties as sources for the roll-up. This will give them the holistic view they need, while allowing the brands to remain independent from one another.

Let’s elaborate on this example. This parent company has a loyalty rewards program that extends across all of their individual brands. When a user participates in this loyalty program, they have a unique rewards ID that we can associate with the user as a user property and/or as a parameter on every event.

The rewards team works at the parent company level, and needs to see data for loyalty program participants across all brands together in the same property. We can achieve this by using a combination of subproperties and roll-up properties so that the rewards team has their own data set to work with. Each source property would produce a subproperty with data just for rewards participants, and then all three subproperties would be pushed into a roll-up property for rewards data.

In this case, the global enterprise account has 3 regional roll-up subproperties with 2 source subproperties each.

In Google Analytics 4 properties, there are a few enhancements to Ads linking, however, the premise remains the same. You can link your Google Ads account to your Google Analytics 4 property in order to share audiences and site stats to Google Ads and benefit from Google Ads reporting data in your GA4 property. Linking to an Ads account is at the Google Analytics property level. You can link a source property, a subproperty, or a roll-up property.

In GA4 properties, you share an individual audience with all linked accounts. With this, sharing becomes much easier, but you must share all audiences or none, so keep that in mind as you develop your Google Analytics 4 audiences.

When you link your GA4 property and Google Ads account, you are able to see site stats in Google Ads. This feature exports behavioral engagement data from Google Analytics directly into the Google Ads user interface. While you can set up a link to any property type, we recommend that you only link to either the source property or the subproperty (but not both): this avoids the double counting that would occur if you linked to both a source property and a subproperty.

Audiences can be shared from any GA4 property (i.e. ordinary property, subproperty, or roll-up property) to Google Ads, but keep in mind that an audience from a subproperty or a roll-up will have different data than the source (ordinary) property, due to filtering or multiple data sets. This is important to note when using audience targeting in Google Ads.

Similarly, key events are dependent on the linked property type. You don’t want to import the same key event type from a source property, a subproperty, and a roll-up property, so the best practice recommendation is to link the source GA property to Google Ads and export your key events only from the source. An exception to this may be if you have regional-specific Ads accounts, which you may need to link at the subproperty level instead.

At its initial launch, the SA360 integration will support data inheritance from the source property to a subproperty or a roll-up property. This means that if the link is established on the source property, the subproperty or roll-up property will receive data from SA360, but the subproperty or roll-up cannot control or set up the link itself.

In Google Analytics 4 properties, you will share an individual audience with all linked accounts. With this, sharing becomes much easier, but you must share all audiences or none. Keep this in mind as you develop your Google Analytics 4 audiences.

At its initial launch, the DV360 integration supports data inheritance from the source property to a subproperty or a roll-up property. This means that if the link is established on the source property, the subproperty or roll-up property will receive data from DV360, but the subproperty or roll-up cannot control or setup the link itself.

In Google Analytics 4 properties, you share an individual audience with all linked accounts. With this, sharing becomes much easier, but you must share all audiences or none. Keep this in mind as you develop your Google Analytics 4 audiences.