Google Analytics Walkthrough
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Google Analytics Walkthrough

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Currently supported:
Reporting API - Version 3
Management API - Version 4

This provides a general description of Google Analytics and its capabilities.

Pull data from Google Analytics in Rivery

The data extracted from the Google Analytics connector uses a configuration of metrics and dimensions.

The data is organized into views (profiles), properties and accounts. Views are related to Properties, and Properties are related to accounts.

Rivery allows you to pull data from multiple views by selecting specific views or selecting any property/properties or account/accounts, as data of related views are extracted.

  1. Choose the report type - The are two report types available:
    Standard and Cohort. The following instructions are relevant for both the Standard and Cohort reports. Additional instructions for the Cohort report can be found at the end.

    Google Analytics Walkthrough-report_type

  • Select the Google analytics connection or create a new connection according to the instructions above.
    Click on “Test connection” in order to make sure the connection is valid.
  • Select from which viewto pull the data.
    • Leave the inputs of accounts, properties and views empty in order to pull data for all available views in the given Google analytics connection.
    • Click on any of the accounts, properties and views inputs in order to get lists of all available accounts, properties and views. Once the lists are populated you can search for the required values.
    • Any selection of an account will filter the values in the lower levels (properties and views) to contain only items that belong to the selected account.
  1. Time period
    Google Analytics Walkthrough-image3

    1. Select the type of time period of the report. It can be a custom date range (as described in the picture above) or a defined time period shown in the pop-up list (for example Yesterday, last week etc.)
  • 1.Select the start date and end date.

  • 2.Leave the end date empty in order to pull data until the moment the river runs.

  • 3.After each run of the river, the start date will be updated automatically with the end date, and the end date will be updated with the empty value. This enables the next run to pull data from the end of the previous run.

     4.Select the time zone offset. It will be relevant only if the end date is empty in order to find the moment of the river’s run according to the time zone.

    5.Days back - use that input in order to tell Rivery to pull data from a given number of days back before the given start date.

Instructions if selecting any other value:

  • Select the timezone offset in order to send the correct dates that consider that offset.
  1. Select the dimensions and the metrics of the report

    1.Click on each input in order to see all the available fields
    2.Important: There are only specific combinations of Dimensions and Metrics allowed by Google Analytics. If the selected combination is not allowed, you will receive an error message.

    Google Analytics Walkthrough-image4

    Important note about XX metrics:
    XX metrics are custom metrics defined in Google Analytics
    You need to manually insert the required metrics by clicking on the metrics field and writing the metric in lowercase. Insert each metric by pressing the enter button.

    e.g. goal2completions
    Make sure to only insert metrics that are defined in your Google Analytics account

    Important note about Dimensions:
    In some cases Audience dimensions like "userGender" and "userAgeBracket" can cause significant reduction in the number of entries and total amount of sessions (only rows that contain these dimension(s) will return) due to Google Analytics user privacy policy and limitations.

  2. Segment - Click to get a list of all available segments in the given Google Analytics account. Once you choose at least one segment an additional field, segment, will be available in the mapping which defines the set of each record broken down by segment. E.g., the following table shows each record received for a given segment. In this use case the set of New Users is part of the set of All Users.

    20210710All Users147833313
    20210710New Users1613726
  3. Additional fields - Any selected fields in that list will be added to the results as an additional field. This is useful in case it is necessary to have the details of the account/property/view in each record of the results.

  4. Advanced options -
    Google Analytics Walkthrough-image5

    1. Custom metrics - Click on the inputs to show a list of all available custom metrics of the given Google Analytics connection.

    2. Custom dimensions- Click on the inputs to show a list of all available custom dimensions of the given Google Analytics connection.

      Important: If selecting more than one view, the selected custom dimensions/metrics must be supported by all the selected views, otherwise it will cause an error.

    3. Sort - Decide how to sort the results by any selected dimension.

    4. Filters - Decide how to filter the data. You must follow syntax instructions when filtering data:

      • == Equal
      • != Does not equal
      • > Greater than
      • < Less than
      • >= Greater than or equal to
      • <= Less than or equal to
      • == Exact match
      • != Does not match
      • =@ Contains substring
      • !@ Does not contain a substring
      • =~ Contains a match for the regular expression
      • !~ Does not match a regular expression

The following section is for the specific setting for the cohort report.

1. Chose the Cohort report type. the Cohort Size.
The size can be day, week or month, and will automatically add the cohortNthDay, cohortNthWeek, or cohortNthMonth respectfully to the dimension list.
3.Select the time period from the predefined options
4.The cohort report can handle multiple segments up to 4

Google Analytics Walkthrough-cohort_options


When you want to analyze your metrics, note that some metrics are unique and cannot be combined between different dimensions without knowing what it will do.
If you see in Google Analytics' UI a range of time interval, e.g., 31 days back, to get the exact same values for users and other unique fields, you will have to set the exact same parameters in your river with the exception to not select "date" dimension, because it will split your data by daily intervals. And select time chunk size to don't split.


For example getting the number of users from each dimension may result in overshooting the number of real users that viewed your website. You can learn more about it in the link below:

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