Table of contents
Why is it important and what is it for?
Direct traffic is any visit to a website made by a user without having clicked on any link that appears in the results of a search engine, in the content of another website, social network or advertisement. That is, it is the web traffic that comes from typing in the browser search the address of the website directly.
But... Why is it important and what is the purpose of this type of traffic?
The truth is that direct traffic provides us with a lot of qualitative and quantitative information about our website and business.
First of all, it is an indicator of how popular our brand is among users or how easy it is to remember our domain name.
On the other hand, a high percentage of direct traffic can mean that many visitors have us in their minds as their first choice when visiting our website, application or online store compared to the competition.
What is part of Direct Traffic according to Google Analytics:
Generally, within direct traffic, other types of web traffic are also considered because it is not always possible to determine their origin by web analytics tools such as google analytics.
Direct Traffic Examples
- a visitor knows the URL and enters it directly into the address bar of his browser
- the user accesses the website through a link saved in the bookmarks or favorites in his browser
- the visitor arrives through a link sent by a third party; email, Whatsapp or messaging service such as slack, etc...
- the visit is produced from a link coming from a pdf document, word, PowerPoint, docs txt
- and traffic from mobile applications.
But there are many cases that can distort the correct measurement of this web traffic.
Elements that distort your measurement
Some studies claim that 60% of direct traffic is actually organic traffic.
Without going into the details of these studies, it is true that many times within this direct traffic are imputed views that have nothing to do with it.
To avoid this deviation in the data of your project you should know these factors that may be distorting the magnitude of the volume of this type of visit.
Let’s investigate the most common causes of direct traffic to find the answer:
Views of internal employees:
Employees often visit the website of the company they work for. If you don’t have the IP filtered in your web analytics tool they will end up counting as part of the direct traffic. As a rule of thumb, filter out all the IPs of the company’s employees.
Intranet or customer portal
Often one of the main culprits of distorting direct traffic figures are having an intranet or customer portal integrated with your website. In this case, it is not advisable to filter out this traffic completely, but to set up different views within Google Analytics to see the data without this traffic.
Traffic from links in emails
It is quite common for Outlook email clicks, or mobile device app clicks to not pass referral information. You can usually identify if an email has caused a spike in direct traffic by analyzing the traffic around the time a particular email was sent but it can be impossible to track when we are talking about hundreds of employees sending emails every day.
Clicks on mobile applications or desktop programs:
Programs such as Skype, Slack, asana, or news apps often do not pass referral information and therefore result in direct traffic. The best way to capture and analyze this is to understand where your website links are commonly used or where they are digitally placed, including apps.
In conclusion:
Although this direct traffic is traditionally attributed to visitors who manually enter the website URL or click on a bookmarked link, the reality is much more complex.
Measuring and analyzing direct traffic can be a challenge for any digital marketing and analytics team. Determining the reality behind these visits requires a good understanding of our business, the sections of our website, inventory of apps and software applications, as well as a deep understanding of web analytics tools.
If this component of the traffic is not well measured, we can get a very biased interpretation of the data.