How to Assign User Permissions within Google Analytics in Order to Connect to Google Data Studio

Within Google Analytics, user permissions govern what users can do and the data that they can access. In this article, we are going to explore the structure of Google Analytics, user permissions and their privileges and how to assign the necessary permissions to enable a user to connect GA to GDS.

This report is a continuation of our previous report, ‘How to: Connect Google Analytics to Google Data Studio.

This report consists of 4 sections:

  1. The Structure of Google Analytics
  2. Google Analytics’ Hierarchy and User Permissions
  3. User Permissions
  4. Assigning User Permissions

Google Analytics allows only the account owner to assign user permissions at 3 different levels. These levels reflect the hierarchical structure of every organisation within Google Analytics. An organisation is the collection of products and users, and every Google Analytics organisation is made up of:

  1. An account – the access point to Google Analytics. There can be multiple accounts within an organisation.
  2. A property – a website, devise or mobile application. An account can contain multiple properties.
  3. A view – an access point for reports and each property can contain multiple views.

Users can be added to Google Analytics at an account, property or view level and this determines their user permissions.

At the account level, the user is assigned the greatest permissions and has access to every property and view in that account.

At the property level, users have access to every view within that property, but that access is limited to one specific property.

At the view level, users only have access to that specific view within the individual property.

There are 4 main user permissions within Google Analytics and therefore 4 levels of access:

  1. Manage Users
  2. Edit Permission
  3. Collaborate Permission
  4. Read & Analyze Permission

1) Manage Users (account level access)

In order to assign a user the ability to manage other users within an organisation, they need to be added at an account level. This permission enables users to add or delete other users, as well as assign permissions.

*This permission does not include privileges that come with ‘edit’ or ‘collaborate’.

2) Edit Permission (account, property or view level access)

A user can be assigned editing permission at any level within the organisation but it is important to note that this user permission entails different privileges at each level. For example, a user with edit permission at an account level can manage account settings, manage filters, create new properties and more.

A user with edit permissions at a property level can import data, create new views, customise tracking and more but they cannot do anything that a user with the same permission at an account level can do.

*This permission includes privileges that come with ‘collaborate’ and ‘read & analyze’ but not ‘manage users’.

3) Collaborate Permission (account, property or view level access)

Users that are assigned this permission have the ability to create, delete and share personal assets as well as collaborate on them.

*This permission includes privileges that come with ‘reading & analyze’ but not ‘edit’ or ‘manager users’.

4) Read & Analyze (account, property or view level access)

This permission is assigned to users that only need to view data. It allows users to create reports, dashboards and customs segments but not edit data in any way.  

*This permission doesn’t include any privileges that come with the other user permissions.

In order to connect Google Analytics with GDS, a user needs to be assigned at least the Read & Analyze permission.

For this example, we are going to add a new user at the view level to assign them the read & analyze permission.

1) The first step is to select the ‘admin’ cog on the bottom left-hand side of the screen in the Google Analytics dashboard.

Next, select ‘user management’ in the View level.

2) Then, click on the ‘+’ sign in the top right-hand corner of the screen and input the new user’s email address.

3) You will then be prompted to select whether or not you would like the new user to be notified via email. Below this, the 4 user permissions will display.

4) Select the check box for ‘read & analyze’.

In order to modify an existing user’s permissions, select the desired user from the list displayed in your user management panel.

Once a user has been assigned the appropriate permissions, they are able to create a new data source. This information has been covered in our previous article – ‘How to: Connect Google Analytics to Google Data Studio.

How to connect Google Sheets to Google Data Studio

In this article, we are going to learn how to connect Google Sheets to Google Data Studio. We will explain how to correctly set up Google Sheets, before going on to explore how GDS imports information into a report.

There are two main scenarios when connecting Google Sheets to GDS may be useful:

  1. When there is no connector available to pull in data directly from your platform.  An example of this might be offline sales.
  2. When only paid connectors are available, for example, Supermetrics which is a paid connector for platforms like Facebook.  Using Google Sheets allows you to export and import data, allowing you to get the data into GDS for free, but it’s a more involved process.

We recommend reviewing the previous articles in our ‘how to’ series to give you a basic understanding of Google Data Studio.

This article consists of 2 sections:

Here are 15 steps to follow in order to create a report with GDS using imported data from Google Sheets.

Preparing Data in Google Sheets

1) It is possible to power a GDS report with a range of different data connectors, one of which is Google sheets – Google’s version of Excel.

2) In order to create a Google Sheet, click on this link and sign into your Google account.

3) Google Sheets is a web-based application which allows users to create and edit data stored in a spreadsheet, which is shared live online.

To ensure that GDS imports the information from Google sheets correctly, it is necessary to display the data in a specific format. Below you will find an example of a Google Sheets table showing results from a merchandise store.

The data in Google Sheets needs to be stored in a table format. In the first row of the table, each column needs to contain a header.

4) In this example, we have used the following headers; date, product type, country the product was sold in, average price, product revenue and tax rate. We are working with 4 main types of data: date, text, currency value, and percentage. It’s necessary to check that each type of data is correctly formatted.

Date example:

  • The date column must be formatted correctly by selecting the ‘format’ drop-down menu and then selecting ‘number’ and then ‘date’. Dates must be in the following format: dd/mm/yyyy.

Text example:

  • All data displayed as text is aligned to the left.

Currency example:

  • Data displayed as currency needs to be formatted correctly by selecting the column, clicking on the ‘format’ drop-down menu and selecting ‘currencies’.

Percentage example:

  • Data displayed as a percentage must also be formatted correctly by following the same steps as above and selecting ‘percentage’.

5) It is important to note that Google Sheets Connector can only connect to one sheet at a time. So, it is necessary to ensure that all the information that needs to be exported to GDS is displayed in a single sheet.

6) GDS cannot import data that is displayed in charts or graphs so it is necessary to ensure that all the information in Google Sheets is presented in a table format.

7) On the table in Google Sheets, a ‘total’ row displaying the sum of each column’s data cannot be included because this will result in double counting. The sum of each column can be added in GDS if it is required.

Connecting Google Sheets to Google Data Studio

8) In order to connect Google Sheets to GDS, it is necessary to create a new data source by selecting the ‘+’ in the bottom right-hand corner of the page in GDS.

The following screen will then appear:

9) Next, select the Google Sheets data connector and authorize the account.

10) Once GDS is able to access the Google Drive folder where the Google Sheet is stored, it can connect to the sheet in one of three ways:

  • Selecting the relevant Google Sheets from a list of saved ones
  • The URL of the spreadsheet
  • Google Drive explorer

11) Select the option that best suits you. It’s important to make sure that the ‘Use first row headers’ checkbox is selected. Finally, click connect.

12)There are two important things to check before connecting the Google Sheet with GDS:

  • Has GDS identified the correct ‘type’ of data for each column in the table on Google Sheets? GDS highlights columns that contain numerical values in blue, and ones that contain texts in green. If GDS doesn’t give you the option to select the data type, this indicates that the data in Google Sheets isn’t in the correct format.
  • Should GDS ‘sum’, ‘average’ or ‘count’ the values in the columns that require these functions?

13) When you select a data visualization from the drop-down menu, you will see from the data tab that the dimensions and metrics are now available to use in your report. Add in a table to confirm that GDS is displaying the correct information with the correct data ‘types’ from Google Sheets.

14) It is possible to build a report by following the same steps outlined in our previous articles. To see a preview of the report, select ‘view’ in the top right-hand corner of the page.

15) Finally, in order to edit any information in the GDS report, amend the Google Sheets accordingly and select the refresh button at the top of the page.

We hope this article was helpful and has assisted you in improving your knowledge in Google data studio. Don’t miss the next article in our ‘how to’ series guide.