The Trouble with Users in Universal Analytics

Ameet WadhwaniGoogle Analytics Data, Universal Analytics

In Universal Analytics, reporting on the Users metric can be challenging. One of the most frequent questions we encounter with our Universal Analytics Backup Utility is: "Why doesn't my Users metric align with the UA web reports?"

This post aims to provide a clear understanding of the user metric in Universal Analytics.

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Just like in GA4, the Users metric delivered by the Reporting API is a calculated metric. Like Bounce Rate, Avg Time on Page, or Pageview Per Session, they are non-summable. In other words, you cannot take Users by Date and summarize them to get users by Week, Month, or Year.

Understanding Metrics for Users in Universal Analytics

User Metrics in GA4
MetricDescription
UsersThe total number of users for the requested time period.
New UsersThe number of sessions marked as a user's first sessions.
nDay UsersTotal number of n-day active users for each day in the requested time period.

In UA, a 'User' represents a unique individual who has visited a website during a particular time period. In other words, Users are a calculated metric that is derived from counting the unique number of users (browserIDs) that occurred in the time period. Similar to other calculated metrics, like engagementRate, average session duration, or pageviewsPerSession, you cannot sum on User counts. 

This is where the confusion begins since a User can visit a website over multiple time periods. The user is marked as having visited for each period of time in the query.  

If you ask for Days in the query and the same user visited over multiple Days, you will see them marked once for each day, regardless of how many sessions they had on each of those days. 

What you absolutely 100% cannot do is summarize that table on Users to go from Days to Weeks, Months, or Years.  By doing so, you count repeat users for each day they visited. 

A User who came back twice per week for one month will show up at least 8 times in the table that lists users by Day. Whereas if you change the query to ask for Month and Users, that user will only appear once. This is why user numbers are inflated when you summarize them. 

When you make an API call to retrieve User data for a specific granularity (e.g., daily), the response table will provide user counts for each day. If you try to aggregate this data to a higher level (e.g., weekly, monthly or yearly), you'll face the non-additivity issue and end up with an inflated number.

Implications of including Users in UA Backup Tables

Since the User metric is non-summable, but often displayed alongside other metrics in a table that has a few dimensions, reporting on users by day, week, month, and year requires a strategic approach.

Here's how you can achieve accurate reporting:

Separate Queries for Different Time Granularities

In addition to daily data tables. also include weekly, monthly, and/or yearly tables for each case where you want to see users alongside other dims and metrics. 

For instance:

  • One query for daily users over a specific period.
  • A separate query for weekly users over a period.
  • Another for monthly users, and so on.

By doing this, the UA API will handle the deduplication of users for each specific granularity, ensuring accurate User counts.

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Analytics Canvas now includes a series of 4 default user tables in the standard UA Backup Table Library so that you will always have accurate user counts by period.

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Conclusion

While the inability to summarize the Users metric in UA might seem like a limitation, it's essential to understand that this design choice ensures more accurate and meaningful data. 

At Analytics Canvas, we're always here to help you navigate these complexities and ensure you're extracting valuable insights from your data. If you have more questions or need assistance with your UA backup or your transition to GA4, feel free to reach out to our team!

Next Steps

Whenever you’re ready… here are 3 ways Canvas can help you with your UA backup and GA4 reporting challenges:

  1. Extract data from all your properties using the API or BigQuery without writing code
  2. Profile, analyse, and prepare data for reporting  
  3. Maintain your GA4 data warehouse within Analytics Canvas Online or your own DB

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  • Start an instant 30 day risk-free trial. No credit card or sales call required. 
  • Schedule a demo for you and your team.
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Wondering if Canvas is right for you? Check out the related articles to learn more about our GA4 connectors.