Last Updated Nov 18 2019

Google Analytics users

There are two types of people who visit your website: those who have never been there before, and those who have. In Google Analytics, this is usually the difference between new and returning visitors—and it’s a useful data point when you want to understand who is coming to your website. But there’s a caveat: the data from GA is not 100% reliable and will not really tell you everything you need. Let’s take a look.

What are users in Google Analytics?

In general, users are visitors who have initiated one session with your website or app within a specified period of time. When you sign in to your GA account, the very first metric on the home is the number of users, which varies depending on the timeframe you choose (today, yesterday, last 7 days, etc.):  


What are new vs. returning users?

New users are users who have never been to your website, according to Google’s tracking snippet; returning users have visited your site before.

When someone views your website, Google’s tracking snippet looks for a tracking cookie on their device:

  • If the cookie is not present, Google creates one and considers this a ‘new’ user
  • If the cookie is present, Google considers this a ‘returning’ user and starts a new session  

Important note: we used italics in the sentence “have never been to your website, according to Google’s tracking snippet” because there are plenty of cases where people have been to your site before but Google’s tracking snippet doesn’t detect it and calls them ‘new’ anyway. If you’re interested in a bit of technical explanation, the box below is for you.

How Google Analytics counts users—and why the numbers are not 100% reliable

Google Analytics distinguishes users who engage with your website by setting a cookie that keeps track of the domain, the number and time of previous visits, traffic source, and the start and end of a session. To determine if a user is new or returning, Google Analytics creates a randomly generated string for a Client ID field stored within a user's browser cookie:




Using this string, GA can match and label any additional sessions coming from the same browser on the same device as a session by a returning user—but in any other scenario, Google has no way to to do the same:

  • If a visitor accesses your site from multiple devices (for example, a laptop first and a smartphone later), GA will count visits from each device as coming from a different user
  • If a visitor has multiple browsers on the same device and uses them interchangeably, GA will assign a separate client ID to each 
  • If a visitor regularly deletes or blocks cookies, they will be counted as new every time they come back to your site after cookie deletion
  • Visitors who use Incognito or Private Browsing Mode on their browsers will always appear as new users, as the browser won’t save cookies and/or site data



To sum up: when it comes to users, your GA data will always be somewhat skewed because of different devices, browsers, and privacy settings and options. 

In other words, when you read that you had ‘10,000’ users last month, you’re probably imagining 10,000 different people—but in reality you should imagine 10,000 different Client IDs instead, knowing that some of them may belong to the same person.  

How to look at users in GA

There are several reports in GA that analyze user metrics and behavior on your website, and we picked two of the most common ones:

Audience overview report

The Audience Overview report gives a high-level view of the number of users and new users who reached your site during a specific timeframe.


In this top-level overview you can also see:

  • The number of sessions per user (sessions are the periods of time a user is actively engaged with your website)
  • The number of pageviews (instances when a page on your website is loaded or reloaded in a browser)
  • The number of pages per session 
  • The average session duration
  • The bounce rate (a measure of single-page sessions where a user lands on your site and leaves without interacting further) 
  • A pie chart of your new vs returning visitors

2. New vs returning visitor report

Under the Audience > Behavior section, people who visit your website are categorized under the dimension of User Type into:

  • New (first-time) user
  • Returning user

In this report, the words ‘user’ and ‘visitor’ are used as synonyms, but there is a slight technical difference. The sum of new + returning visitors (11,081 + 3,149) is not the same as the total number of users (12,995) → that’s because a single user may visit your site several times during the reporting period, which makes them both a new visitor (on their first visit) and a returning one (on any following visit).

You can use the new vs. returning report to see details about each user type; specifically, if you’re a business that’s selling online, you can start investigating the difference in behavior when it comes to the number of transactions and revenue:


What GA can’t tell you about users

Once you start looking at new vs. returning users, you may start spotting differences in behavior:


Here, for example,

  • New visitors spend less time on the site than returning ones
  • Returning visitors have a higher conversion rate than new ones
  • New visitors bounce away from the website more often than returning ones

The logical next question is: why is this happening?

...and that’s where you start running into potential trouble. Finding an answer to this question in Google Analytics is hard, because GA is excellent at reporting what is happening but falls short with the why side of the equation. In this case, GA can’t tell you why new visitors are behaving in a certain way and returning ones exhibit a different behavior, and if you want to find out you have to do some more investigating of your own.

Survey new and returning users to get the missing context

Asking visitors a few simple questions while they’re on your site is the logical next step to start understanding what they want from you and why they are staying longer/spending more/coming back, or not.

How to do it: set up an on-site survey and target the specific URLs you want to start your investigation from.


Keep the survey short (max. 3 questions) not to take too much of your visitors’ time, and tweak the questions slightly depending on the pages you want to collect data on:

  • Homepage, main landing pages: 
    1. Is this your first time on our website? (yes/no)
    2. What are you looking for today?
    3. What’s ONE thing that would make this page more useful to you? 
  • Product pages: 
    1. Have you been on this page before? (yes/no) 
    2. What information about [product] are you looking for? 

Note: it’s much easier for a visitor to reply to question 1 (it’s a straightforward yes/no question), but it takes more effort to answer open-ended questions 2 or 3. Let the poll run until you have at least 20-30 answers to questions 2 and 3, which gives you enough qualitative feedback to dig through.

  • Start by differentiating answers that come from people who answered YES vs. NO to the initial question: keep them in two columns if you’re using a spreadsheet (or even a piece of paper), because you’ll want to read their answers in context
  • Continue by digging through the qualitative feedback to see if anything stands out for each group. For example: do new visitors have specific needs when it comes to ‘the ONE thing that would make the page more useful’? Do you see people repeating the same point over and over again?
  • You can later use this knowledge to add the information that is missing, restructure the page, and make it more appealing and functional  

🔥Pro tip: when you don’t have any context, any information is better than none, so your goal here is not to get a really in-depth plan of action or the answer to all your questions: you’re aiming for a few clues and hints about what is happening on your website.

Once you have developed this knowledge, you’re ready to build upon it by running more research and investigation. Here is a handy 3-step framework that can help you identify the drivers that bring people (new and returning) to your site, the barriers that stop them from converting, and the hooks that ultimately convince them to do so.

Start learning about your users today

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