Why you have far less unique visitors than your web analytics tool tells you

Web analytics tools heavily overstate the number of unique visitors your website has. The degree of error ranges anywhere between a few dozen percent to a few hundred percent. Here we discuss the variety of causes for this erroneous unique visitor count.

Javascript disabled

The smallest issue for distorting unique visitor count is visitors who have Javascript disabled. For many years the percentage of users who have Javascript disabled has evolved around 2%. Often these are visitors who use Firefox NoScript add-on. When users who have Javascript disabled visit your site none of their activity will be measured. This can be compensated somewhat by adding a tag to your normal analytics tag.

In the Google Analytics example below this will register a hit via the Measurement Protocol even when Javascript is disabled. This will enable you to register a pageview but most of the other information that a tag would register won’t be captured.



The use of ad-blockers, particularly by younger users, significantly increased in recent years. In many European countries ad-block usage is above 20%. Many of these ad-blockers have the ability to block web analytics trackers. Some ad-blockers block analytics tracking by default, others make it very easy to enable it.


Image source: https://www.quantable.com/analytics/how-many-users-block-google-analytics/


The margin of error this creates varies according to your user base. One experiment established that Google Analytics script was blocked in 11% of cases.

In-private browsing

Nearly one out of five internet users use in-private browsing. With regards to analytics tracking this means only temporary session cookies and no permanent cookies to identify unique visitors will be placed. When visitors come back to your site they will be considered a new visitor thus inflating your unique visitor count. However, their session information and hits will be registered correctly.

The above applies to nearly all browsers, except Firefox. In-private browsing in Firefox means the NoScript add-on will block any form of Javascript tracking. As such no measurement will be made at all.

Cookie deletion

It is hard to find statistics on cookie deletion behaviour. Yet when I ask in the many analytics courses that I teach whether participants delete cookies I find that without exception several of them do at varying frequencies (anywhere between 6 weeks to several months). If I were to stick a number on it I’d probably pick 20%. Visitors who delete cookies obviously heavily distort your unique visitor count since they will be counted as a new visitor every time they come back to your site after having deleted their cookies.

Multi-device & multi-browser usagemulti-device-usage

Users who use more than one device to visit your site will have a tracking cookie on each
device and will therefore be counted as multiple unique visitors. The question is, how
many of your visitors do use multiple devices. The only way to prove this is by making visitors login to your site every time they visit. You will then be able to record a unique user id instead of a cookie id.

In the example on the right taken from a site where users are always logged in we see that about 30% uses more than one device to visit the site. If no unique user id would have been captured this would mean the unique visitor count would be inflated by 30%. On your site the same thing happens although maybe to a lesser degree (the example was taken from a site to which visitors return very frequently).

When users use different browsers on the same device to visit your site the same principle applies. They will have a cookie in each browser will leads to inflation of the unique visitor count.

In conclusionuser-id-vs-cookie-id-3

There are different reasons why the unique visitor count of your analytics tools is overstated. Some issues cause that unique visitors are underreported (javascript disabled, ad-blocking), other issues will inflate the unique visitor count on your site (in-private
browsing, cookie deletion, multi-device usage, multi-browser usage).

Clearly inflation is far more likely to happen than under-reporting. Yet, it is virtually impossible to quote a generic inflation factor.

In the example on the right from a site where users a always logged in we confronted the number of unique user id’s with the number of unique cookies in Google Analytics. The result: 93.681 unique user id’s matched to 312.577 users or unique cookies.

The real number of unique visitors was overstated by more than a factor 3 ! With some visitors equaling as many as dozens to hundreds of unique cookies !!

So…be warned…unique visitor does not equal unique human being…far from !


  1. Hi Remco,

    About 5 years ago I set up an experiment to measure this – the site was an Australian higher education site that used a login, and I captured the hashed value of the login id as the client ID in a GA User-ID view, and also captured the value in a custom dimension. Comparing the no. of Visitors in the custom dimension between the standard (cookie-based) view and the UserID view over time, I was able to show that after a day, 5% of users had a new cookie, after a week 14%, at 30 days 41%, and at 90 days 69%.

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