Meaningful Metrics: New vs Returning Visitors in Google Analytics

“I want to increase the number of returning visitors.” Now you need a report to track your progress. This article will help you navigate Google Analytics to find the right data, and to produce a meaningful report using Analytics Edge.

Why Do We Care About New or Returning Visitors?

Numerous studies have shown that websites tend to have more new visitors and fewer returning visitors. But the returning visitors tend to have higher engagement — they bounce less, view more pages per session, and have higher session durations. They also tend to have higher conversion rates and higher sales…much higher. This makes us want more returning visitors.

But every website needs both new and returning visitors — you need to feed the funnel with new users so you can turn them into returning users. Some marketing initiatives encourage new visits (like advertising and search engine optimization), and some encourage return visits (like posting to social media or an email newsletter). It is important to know how they all come together to make the numbers grow.

How Does Google Analytics Measure New/Returning Visitors

Google Analytics uses the dimension User Type to differentiate between a New Visitor and a Returning Visitor. They show this dimension in the standard report AUDIENCE > Behavior > New vs Returning along with a number of metrics. The metrics displayed vary depending on whether you have Enable Users Metrics (Property Settings) or Enable Ecommerce (View Settings) options on.

Google says you can use this report to measure the gravitational pull of your site, and the extent to which you’re encouraging first-time users to return. You can also see the economic impact of new vs. returning users.

During a User’s very first visit to your website, the User Type dimension will be set to New Visitor. After that, all future visits will be tagged as Returning Visitor. The report shows the basic counts, the engagement, and the conversions for each User Type. You can easily see whether Returning Visitors engage and convert more on your site by comparing the numbers.


Sources of Confusion: Users, Sessions, and Visitors

In some reports you will see % New Sessions or New Users metrics. Combine those with the Users and Sessions metrics for New Visitors and Returning Visitors, and things can get confusing. Sessions and Users and Visitors are different things:

  • a new User (person) would be classified as a New Visitor (type of user), count as a User and a New User, with a Session (visit). By itself, that would count as 100% New Sessions.
  • a returning User (person) would be classified as a Returning Visitor (type of user), and be counted as a User with a Session. By itself, that would count as 0% New Sessions.
  • a single User (person) can have multiple Sessions (visits) in the reporting period. If they are a new User to your site, their first Session would be as a New Visitor, but their returning Sessions would be classified as a Returning Visitor. So a single User can be BOTH a New Visitor and a Returning Visitor in the same report.
  • a single User can be a New Visitor only once (on their first visit), but they can have multiple return Sessions in the same reporting period. Since %New Sessions is a ratio of (new Sessions)/(new+returning Sessions), it drops if there are more returning visits from that User.
  • a User that visited before the reporting period would be seen only as a Returning Visitor. Their New User count (first-ever visit) happened before the reporting period started, so they would not appear as a New Visitor at all.

For example, if a single User has their first, second and third visit during the reporting period, they would appear as:

Total Users: Note that the total number of Users is NOT a mathematical sum of New Visitors+Returning Visitors. 1 (New) + 1 (Returning) = 2, but the total number of Users is 1 because it was the same person — the total Users metric is an entirely different query that removes any duplication.

% New Sessions is not a good indicator of the number of new or returning users. In the example, the % New Sessions is 33% even though all the sessions came from the same user. Only the first session was new; the others were returning. Lots of returning sessions by the same users causes the percentage to drop.

Google Analytics does not have a dedicated metric for Returning Users like they do with New Users. If you want to see how many returning Users you have, you would need to look at the Users metric where the User Type is Returning Visitor (cell B3 in the image above).

Further reading: Misunderstood Metrics: New vs Returning Visitors


Meaningful Metrics: New and Returning Visitors

Caveat: because of the way Google Analytics works, a user will be identified as a New User if they use different devices or have enabled privacy settings. This means you do not know if a “New User” is actually new. However you can be very confident that a Returning Visitor is really is returning. Changing new user counts could mean a number of different things, but if returning user counts go up then you know you got more returning users.

Key Performance Indicators are metrics you can watch over time that will indicate improvement, or a lack of it. The most common key performance indicators for New vs Returning Visitors are:

  • % New Sessions – this is a classic, readily available, but poor metric to monitor. By itself, it tells you almost nothing; an increase could be good (more new users) or bad (drop in returning sessions).
  • New Users – readily available, and commonly used to evaluate the effectiveness of traffic generation efforts. It gets more meaningful when combined with a channel or source, such as new users from organic search.
  • Returning Sessions – filtered query required (Sessions metric where User Type is Returning Visitor). A good measure of visitor loyalty and site appeal, but affected by changes in the number of sessions per returning user.
  • Returning Users – filtered query required (Users metric where User Type is Returning Visitor). Often overlooked because most people don’t realize it can be obtained. The ultimate visitor loyalty measure.

Segmentation is used to look deeper into the metrics — to understand why they are what they are. Any of the previous measures can be combined with other dimensions, such as date, source or demographics (like device). While this is referred to as “segmentation”, it usually does not involve the use of a “segment” in Google Analytics — just add another dimension to your query, or add a filter to get just one value. Some segmentation examples:

  • by Date (Week/Month) – see if various marketing initiatives have been successful, or what impact website changes have had.
  • by Channel or Source/Medium – see which channels are delivering new users to the site, and how returning users find their way back.
  • by Referring URLs – what are your best references? Are some more effective for conversion?
  • by Device Category (Mobile Device) – rough estimate of the usability of the mobile version of the site.
  • by Landing Page – what anchor or reference pages bring people back again and again? Which pages bring in the most new visitors?
  • by Language/Country – does your site appeal more to specific locations or languages?


Meaningful Reports: Widgets

Because of the variety of metrics available, and how they interact with the User Type dimension, you can combine them in different ways in order to show different behaviors.

A common way to present Key Performance Indicators (KPI) is with dashboard widgets. Widgets are usually self-contained block that shows the current KPI value along with a trend or previous value to provide context. It is important that you do not simply present a number without that context.

Learn more: Building a Dashboard Widget in Excel

Returning Users Widget

The Analytics Edge query required to get the data is:

  • dimension: Month of Year
  • metric: Users
  • filter: User Type > Exact Match > Returning Visitor
  • dates: duration 13 months; end of Last Month
  • option: Minimize sampling

As described above, getting the number of returning users out of Google Analytics requires a special query because there is no “Returning Users” metric available. This query pulls the Users metric, filtered for a User Type of Returning Visitor.

This query delivers 13 individual months of User numbers. You would write this query to a data worksheet, and use cell references from the actual widget to the data worksheet (see the article for details). The result includes the current and previous month values as well as a year-ago value so you can calculate month-to-month and year-to-year changes. It also includes all of the months in between so you can build a chart showing the trend.

Note that the Minimize sampling option is turned on to reduce the risk of sampling for larger websites.


Meaningful Reports: Tables and Charts

Segmented data is usually presented in tables or charts. Your selection depends on the content and purpose of your report. Trends are usually presented as line charts, and segmented groupings are typically presented in tables or bar charts. When building your report in Excel, you need to work within the rigid row-and-column grid of the spreadsheet.

If the report is for your use only, I recommend that you keep things simple and write your query results to separate worksheets. That way, future changes will not impact other queries.

Learn more: Building a Marketing Dashboard in Excel

Analytics Edge provides a number of free sample reports with various presentation approaches, but you should pick an approach that is right for your reporting situation and content.

Returning Users by Channel

The Analytics Edge query required to get the data is:

  • dimension: Default Channel Grouping
  • metric: Users
  • filter: User Type > Exact Match > Returning Visitor
  • dates: preset Last Calendar Month
  • sort: desc Users

As described above, getting the number of returning users out of Google Analytics requires a special query because there is no “Returning Users” metric available. This query pulls the Users metric, filtered for a User Type of Returning Visitor.

When looking at the Default Channel Grouping or other segmentation, it is often preferred to sort the results by the number of Users in descending order. This puts the most significant items at the top of the list.

Returning Users by Channel Trend

The Analytics Edge query required to get the data is:

  • dimension: Month of Year,Default Channel Grouping
  • metric: Users
  • filter: User Type > Exact Match > Returning Visitor
  • dates: duration 12 months, end of Last Month
  • option: Minimize sampling
  • Standard or Core Add-in: Pivot by Month of Year, sort by last column descending

This report builds on the previous one, adding the Month of Year dimension, but it requires a Pivot operation. The Analytics Edge Standard Add-in and Core Add-in offer Pivot and Sort functions; if you are using the Basic Add-in, you will need to link your query results to an Excel Pivot Table.


Meaningful Analysis

When viewing the standard reports in Google Analytics, you may be tempted to reference the %New Sessions metric or New Users count because the numbers are readily available. While those metrics may help measure your lead generation activity, they do not tell the whole story.

Returning visitors are typically more engaged, with higher conversion rates and total sales (or goal completions). They are worth monitoring, but Google Analytics doesn’t make it easy to do so. Analytics Edge does.

Use the Analytics Edge queries above to monitor your New and Returning Users, or modify the queries to suit your specific needs. Consider weekly reporting instead of monthly, and try other dimensions for segmentation to better understand visitor behavior on your website.

Questions to consider:

  • what content do returning visitors favor? Can you create similar new content? Add calls-to-action to deepen your relationships?
  • look at landing pages with high bounce rate for new visitors – do they need some work?
  • if there is a drop in new users, consider new or strengthening marketing initiatives.
  • if there is a drop in returning users, review other segmentation to determine if it is a specific group of people or specific content that is being lost.