In a recent discussion about website traffic and visits, I found some people would think accessing the same website in a new browser tab or new browser window will be a new visit to the website in the corresponding tab or window. It is surely not the case and a difference in human perception of the digital experience and what is happening technically.
Browser Tabs And Windows
Opening multiple windows for the same application is a common practice in desktop computing back in the 1980s and before the Internet age. The tab came later and started with the web browser and became popular in the mid-2000s. Both windows and tabs are now available in not only web browsers but many other applications and also on mobile devices. They provide some very convenient ways for users to organise their way of work, contextually group information and tasks together, increase productivity and streamline their workflow.
In particular in web browsing, people are accessing and opening multiple windows/tabs for the same website for two primary reasons:
- Continuing the current journey with the current tab and starting new branches of different journeys in other tabs, such as from a search engine to open different result pages into new tabs
- Comparing different contents on some content-rich websites and different products offered, we may be doing a lot of this on any e-commerce website
Another common use for tabs is the introduction of the tab group in many modern browsers, allowing users to remember a whole list of web pages and make them ready when launching the browser next time. However, a difference between the tab group and manually opening a new tab is that not all tabs in the tab group load the corresponding website immediately, usually only loading the page when the user switches to the corresponding tab. However, the use of the tab group is still encouraging users to have multiple tabs opened, whether to the same website or different websites.
Challenges For Website Traffic Analytics
So how is that tabbed browsing behaviour impacting web analytics? The simplest answer is web analytics recognize visitors and visits by using cookies which the same set of cookies are being shared by all tabs and windows of the same browser.
Nowadays, all website traffic trackings are implemented via web beacon, which sends traffic information to analytics tools together with the unique visitor identifier typically stored locally on the browser as a cookie. When the analytics tool receives the traffic information, it stores traffic information and builds up visits, which is usually as defined as continuous website interactions without 30-minute breaks between any two web beacons.
Since all tabs and windows share the same set of cookies, web beacons sent from different tabs and windows also share the same unique visitor identifier, from this the analytics tool will conclude all traffic from multiple tabs and windows is coming from the same visitor and same visit. This creates quite some problems in website traffic analytics.
With tabbed browsing, users can open multiple tabs simultaneously and land on the same website from different sources. This makes it difficult to accurately attribute conversions or actions to a specific referral source. For example, if a user lands on a website through a search engine in one tab but converts on another tab opened from a social media link, it becomes challenging to attribute the conversion accurately. The same applies to onsite attribution on what website behaviours are contributing to the final conversion. For example, if a user searches doe men’s clothing in one tab, and searches for kid’s toys and completes the purchase in another tab, it becomes difficult to attribute the entire purchase journey to a single user.
Tabbed browsing complicates session tracking. A session typically represents a user’s continuous engagement with a website. In tabbed browsing, a user’s activities may span across multiple tabs, making it tricky to define and track individual sessions accurately. Determining when a session starts and ends becomes more challenging, impacting metrics like session duration and engagement.
Each tab in a tabbed browser operates independently and traffic is tracked together, which means analytics tools cannot distinguish user behaviour across different tabs. We may be seeing users navigating from one page to another page which has no reasonable or logical connection.
Browsers often prioritize the active tab, while background tabs may have limited resources allocated to them. As a result, web analytics may not accurately track user interactions, such as page views or events, in background tabs. This can lead to underreporting or incomplete data on user engagement.
There is also a new browser feature getting more common and popular, profile, which allows users to separate personal, work, and different purposes of profiles in the same browser. The profile feature is less problematic for website traffic analytics, as different profiles maintain a different set of cookies and other browser configurations. Traffic to the same website from the same browser but different profiles have different unique visitor identifiers and thus are considered as different visitors. However, if different profile windows are opened and multiple tabs in the same profile window to the same website, the problems described above persist.
So What And How To Handle
Is that a big problem? It depends on the specific context and goals of the website or business relying on web analytics.
If all we care about website traffic analytics are simply some countings, such as visitors, visits, page views, downloads, etc. The challenges associated with tabbed browsing may have minimal impact on their overall analytics insights.
However, for businesses heavily reliant on accurate attribution, session tracking, or user journey analysis, the challenges can pose significant hurdles. In such cases, the problems of tabbed browsing can affect data accuracy, lead to incomplete insights, and impact decision-making processes based on web analytics data.
This is a very challenging problem to resolve.
First, we are unable to certainly know and difficult to observe if a user accessing our website from multiple tabs/windows or not. Each tab is isolated and web browsers do not expose this information for the website to know if it is running in one tab or another. All data collected from all tabs of a website are mixed and interlaced together in the analytics tools which is quite impossible to know they are from different tabs and isolate them.
Also, it is out of the website’s control how users browse the website from one or multiple tabs. Some websites even have a practice to keep opening links to their websites into a new tab.
There are two approaches to “address” the issue instead of resolving it. The design of the website and the design of tracking.
Multiple tab browsing is a behaviour of users trying to address problems when browsing websites. There may be potential issues with information architecture making users find it difficult to get all the necessary information on one single page, it is easier to have multiple tabs with related pages opened instead of navigating fore-and-back repeatedly. Or it is a lack of or incomplete product comparison features for users to compare in one single page but with multiple product pages opened in different windows to compare. Reviewing and improving information architecture and features is not only reducing the issues of tabbed browsing but also an improvement to customer experience and satisfaction.
The design of tracking should accommodate the possibilities of complicated user behaviour, not only on multiple tabs browsing. Shift the focus from session-based analytics to user-centric analytics. Instead of analyzing sessions or individual page views, track and analyze the behaviour and actions of individual users over time. This approach can provide a more holistic view of user engagement and help mitigate the impact of tabbed browsing. Go beyond first/last touch attribution to more advanced attributions, such as linear, time-decay, J-shape, etc.
Supplement web analytics data with user research and surveys to gather qualitative insights. Directly engaging with users through interviews or surveys can help fill gaps in understanding user behaviour that may be impacted by tabbed browsing. It can also help in the improvement of the website and tracking design.
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