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.
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.):
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:
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.
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:
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.
There are several reports in GA that analyze user metrics and behavior on your website, and we picked two of the most common ones:
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:
Under the Audience > Behavior section, people who visit your website are categorized under the dimension of User Type into:
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:
Once you start looking at new vs. returning users, you may start spotting differences in behavior:
Here, for example,
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.
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:
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.
🔥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.