Google Analytics Organization and Naming Recommendations

Posted: October 24, 2017 at 1:34 pm, Last Updated: October 24, 2017 at 1:40 pm

The Google Analytics framework is organized into three hierarchical levels: Accounts, Properties, and Views.
There is often confusion about what these different levels of organization represent, and therefore how they should be labelled.

Here are our official recommendations for organizing and naming Google Analytics accounts, properties, and views:

Accounts

Google Analytics Accounts are intended to represent a business or organizational unit, which often – but not always – includes multiple websites. Account are just containers to organize the various websites within the company or organizational unit; they don’t have any important settings other than just their name. Therefore, the account should (ususally) not be named for a specific, individual website, but for the business or organizational unit which is responsible for the website(s) within it.

Naming Accounts

Name the account for the actual Mason school/college or top-level organizational unit which is responsible for a group of websites.

Examples

  • Mason College of Science
  • Mason Office of the Provost
  • Mason Division of Enrollment Management

There is a limit of 50 properties per account, so if your unit or department has more than 50 websites, you may need multiple accounts. In that case, add a number on the end to create a second account for your unit (example: Mason College of Humanities and Social Sciences 01).

Properties

A property in Google Analytics usually represents a single website. (Properties can include multiple websites’ data, for example in the case of ‘roll-up’ properties in which you want to aggregate analytics data.) As such, the property should be named for the specific website in question. To avoid ambiguity, I recommend using the domain name of the website as the name of the analytics property.

Naming Properties

Name the property with the domain name of the website in question. (Leave out the “http://” or “https://”.)

Examples

  • www2.gmu.edu
  • cvpa.gmu.edu
  • provost.gmu.edu

Views

A view is the actual “bucket” of data containing the analytics data for the website in question. By default, when you first implement Google Analytics, it will automatically create a single view called “All Web Site Data”.

So why is there another level of organization under the property level? Because you may want to have multiple views containing different subsets of data for an individual website. For example, you may want one view including only US traffic and another view including only international traffic. Or, if your department relies heavily on social media, you may choose to have a separate view that only includes traffic from Facebook. Splitting your data into multiple views can be very helpful for identifying trends and differences in behavior between segments of your audience.

In fact, even if you don’t need to split your data in this way, you should always have at least the following three different views in each property:

  • An unfiltered view, to store the completely unmodified, raw data, as a backup to any other modified views that you create.
  • A test view, to test new settings or configuration changes before making them ‘official’.
  • An official, or production view, as your official source of analytics data, set up just the way you want. (As mentioned above, you may actually maintain multiple production views depending on how you would like to split your data.

Naming Views

  • Prefix the view name with a label indicating which type of view it is:
    • For a raw (unfiltered) view, prefix the view name with “[RAW]”.
    • For a test view, prefix the view name with “[TEST]”.
    • For a production view, prefix the name with “[PROD]”.
  • Include the website domain name in the view name, to make it clear what website the view relates to. (This is helpful if you manage multiple websites analytics data.)
  • For production views, include a short descriptive name indicating subset of data what it captures, if applicable.
  • Include an effective date in parenthesis at the end. This makes it clear just from looking at the name how far back the data in the view extends.

Examples

  • [PROD] www2.gmu.edu – All Traffic 2.0 (2017-06-25)
  • [RAW] www2.gmu.edu (2017-06-25)
  • [TEST] www2.gmu.edu (2016-12-01)