Countly vs. Google Analytics


We know that the most commonly-used analytics tool is Google Analytics (GA), primarily due to its free option. To help our new users (who may have been using Google Analytics earlier) get a handle on using Countly with greater ease, we’ve compiled some information about the many comparison points that may arise between Countly and GA. To highlight this information accurately, you will find this document divided into Basic Terms and FAQ.

Note: this article has been kept limited to the metrics on the Countly Analytics plugin. 

Basic Terms


On Countly, if a user opens an application or visits a website, it counts as a session until they close it. When Countly detects that the user/visitor has been inactive for more than 20 minutes, it will terminate the session and start a new one when the user/visitor opens the app or visits the website again. 

On Google Analytics, it starts counting as a session from the moment a user arrives on your site or opens your app. If 30 minutes pass without any kind of interaction from the user, the session ends. However, every time this user interacts with an element (like an event, social interaction, or a new page), GA resets the expiration time by adding another 30 minutes from the time of that interaction (as different than Countly, where the 20 minutes is considered as an inactive period). Additionally, a session is considered as having ended if the device on which the user is active crosses the midnight mark, as well as if the user leaves after having arrived via one campaign, and then comes back through a different one.

There is a difference between GA and Countly when it comes to session logic - in particular, the inactivity time settings causes differences between GA and Countly results. If you’d like to compare the results, the best method is to configure inactivity time from the Web SDK. But there will still be minor differences due to activity check logic named “cooldown” of Countly.

For more information, please visit here. For more details on the ‘cooldown’ period, please visit here.

Session on Countly refers to Session on GA.


Total Session:

On Countly, this is the number of times your website is opened. 

Total Session on Countly refers to Total Session on GA.

On Google Analytics, this is the number of total sessions during selected date range.

Tip: If you see a difference in session numbers between Countly and GA, it would probably be due to bots and the session logic on GA (if you have proper installation of Countly). Countly blocks the traffic created by bots more effectively compared to GA. Even so, the difference expected is lower than 5%. 


New Sessions:

On Countly, this is the number of first time visitors. This is basically the amount of visitors for selected period. New visitors open your website only once. If a visitor visits your website again in any other period, it won't be considered a new user or new session. Hence:

  • If user uses another computer/device, it's a new user
  • If user uses another browser, it's a new user
  • If user uses incognito mode, it's a new user
  • If user clears browser/website data/cache, it's a new user

New Sessions = New Users (Visitors) 

New Session on Countly refers to New Visitors on GA.

On Google Analytics, a new session starts after 30 minutes of inactivity, or at midnight — so if a user opens your website, walks away from their computer for 45 minutes, and returns to the page after that, it counts as 2 sessions.

Unique Session on Countly refers to New Session on GA.


Total Visitors:

On Countly, this is the number of unique visitors to your website for the selected period.

Total visitors = New visitors + Returning visitors

Total Visitors on Countly refers to New Visitors + Returning Visitors* on GA.

*no default metric

On Google Analytics, this is the number of users who have initiated at least one session during the date range.

The sum of new + returning visitors is not the same as the total number of users on GA → 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).

New Visitors:

On Countly, this is the number of first time visitors. If, in any other period, the same user opens your app or website again, it won't be a new user.

New Sessions = New Users (Visitors) 

New Visitors on Countly refers to New Visitors on GA.

On Google Analytics, this is the number of first-time users during the selected date range.

New Visitors or New Sessions on Countly refers to New Visitors on GA.


Returning Users/Visitors:

On Countly, this is the number of users that have used your application at least one time before.

Returning user = Unique Sessions - New Sessions 

Returning Users on Countly is the same as Returning Users on GA.

On Google Analytics, this is a user who returns to a site (using the same browser / same computer/device). If someone has visited your website within 1 month and returns from the same device, they are marked as a Returning Visitor in Google Analytics. 


Average Session Period:

On Countly, the average session period tells you how long your users/visitors spent on your app or website and is calculated by the equation given below:

Average Session Period = Total duration / Total Sessions

Average Session Period on Countly refers to Average Session Duration on GA.

On Google Analytics, it measures how much time—on average—visitors spent on your website as a whole. Note that if someone only loaded one page and triggered no events, their session duration is reported as 0, even if they spent time on the site. This means that, by default, Google Analytics’ Time on Page and Session Duration metrics are lower than the true value of how long someone spent on a page or site.

Average session duration = Total session duration / Total Sessions


Average Request Received:

On Countly, this shows the number of write API requests Countly Server receives for each session (including sessions, session extensions, events, etc).

There is no default metric on GA; custom metrics can be used to measure it. 
Avg. Hits Per Session on GA may be the equivalent of Avg. Request Received on Countly.


Time Spent:

On Countly, it shows total time spent on the website for the selected time period.

Time Spent on Countly refers to Session Duration on GA.

On Google Analytics, it measures how long a user spent on your site in total.


Average Time (on Page View breakdown):

On Countly, this is the total time spent on a specific page (not overall website or app) for the selected time period. 

Average Time on Countly refers to Avg. Time On Page on GA.

On Google Analytics, it measures how long—on average—visitors spent on a specific page of your website, similar to Countly.


Average Time Spent:

On Countly, it gives you total duration spent using your application divided by total visitors count.

There is no default metric on GA; custom metrics can be used to measure it.
Total Session Duration Per Visitor on GA may be the equivalent of Avg. Time Spent metric on Countly.


Total Time Spent:

On Countly, it gives you the total duration visitors spent on your website during a selected date range.

Total Time Spent on Countly refers to Total Session duration or 
Total Visit Duration
on GA.

On Google Analytics, it shows how long a user spent on your site in total.


In this section, you will find the responses to some common questions regarding Countly vs. Google Analytics.

Why do I see different user numbers on Countly as compared to Google Analytics?

When you see different user numbers or sessions on Countly and Google Analytics, it might be because of the user/visitor tracking method you are using. By default, Countly and GA generate random value and attach it to device/browser/etc. But Countly allows different tracking strategies, like tracking a user instead of a device, which can be done when a customer provides their own ID value. GA, similarly, might have different custom strategies too. The strategy you use in each can determine the user numbers, and using different strategies could result in data differences.

A critical point here is that, by default, Google Analytics determines unique users using client ID parameter. The Client ID is a unique identifier parameter used in GA for a browser–device pair which is used to report a unique user. On the other hand, in Countly, thanks to the User ID implementation feature, you see unique users across devices, browsers, and multiple sessions. This means that Countly automatically merges data for the authenticated user and so defines user with User ID to unique user profile. The differences in implementation on tracking method can cause a huge difference between data in GA and Countly.
For example, if you use random generated id for GA, but use custom provided ID in Countly, then GA would definitely have more users than Countly, because Countly would be able to identify the same user between different browsers/devices/etc., which is something that GA will not do.

Do storage and cookies tracking methods cause differences?

As a default user tracking method (for unknown users which are not authenticated with login or registration system), Countly uses “device_ID” which is normally (by default) generated on the environment the Countly SDK runs on (e.g. a smartphone, a web browser, or a desktop application). It is used to identify the user who directly interacts with the device. Google Analytics mainly sets first-party cookies which are domain associated cookies and generated to access same-site information relative to the website domain in your address bar to track users/visitors. Users’ cookies are not shared across devices. Different browsers or devices will result in different cookies and therefore different users.
Countly uses local storage while GA uses cookies, which cause differences in many situations such as cross domain (including with 'www' and without 'www'), when clearing app storage, or when using incognito modes and so on. For example, if a visitors clears the cache on the browser, they will be tracked with new cookie and Client ID and treated as a New User. So, you probably see higher numbers on your GA reports.

How can you determine whether users are recorded and how if they open and close a browser very quickly?

Javascript in browser is asynchronous, as in, in most cases there is no control over order of which code is executed. This means that sometimes Google Analytics code gets executed first, while at other times Countly code is executed first. It, of course, also matters from point of positioning in the website too.
But the main point here is that if someone loads a webpage quickly and quits it, without even maybe loading it fully, it is impossible to determine whether Countly or GA reported those users or not; which tracker (if any) did have time to load is mostly out of control.

Do GA and Countly block bots in the same manner?

GA blocks some bots, while Countly blocks others - no one option blocks everything. This is because when bots visit the website, Countly chooses to report or to not report them based on some behavior or identification. This bot blocking process is different in GA and in Countly, which is why there may be a difference in the results.

Does the ad blocker on users' browsers and apps make a difference to the data captured?

Ad blockers on browsers and apps of users would have different affects on GA and Countly data. Visitor uses ad blockers to block data from being sent to our servers (not our decision or depends on our methods). Some ad blockers block Countly while some block GA and others block both. Some, like uBlock, only blocks specific information, for example Sessions in Countly, but allows all other requests. How the same ad blocker behaves with GA can be completely different. Hence, this can affect the data.

How does referral spam affect GA and Countly?

Google Analytics gets spammed a lot by referral spam, which is why many Countly users have noticesd a reduction in users/sessions when they switch to Countly. One of the primary reasons for this is that Countly is less likely to be spammed as most of the bots target GA specifically.

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