What is direct traffic in Google Analytics & why is it so high?

Direct traffic is that Google Analytics session (or visit) which starts without a referrer being passed by a user’s web browser.

This is the most accurate definition of direct traffic. All other definitions of direct traffic (like direct traffic is the traffic which comes from bookmarks or traffic from typed URLs etc) are lame, as they do not accurately describe, what direct traffic really is.

Direct traffic is ‘unknown’ traffic

The majority of people assume that 100% of direct traffic is made up of the traffic which directly visits their website (by typing the URL in the browser address bar) or which comes from bookmarks. But this is not often the case.

Whenever Google Analytics is not able to determine the origin of the traffic source, it reports that traffic as direct traffic.

Whenever a referrer is not passed or is dropped because of technical reasons, Google Analytics is not able to determine the origin of the traffic source and report that traffic as direct traffic.

Google should seriously consider renaming ‘direct traffic’ as ‘unknown’ traffic to avoid any confusion regarding the origin of the traffic source.

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Direct traffic is actually a demand

Contrary to popular belief, ‘Direct’ traffic is not really a marketing channel. It is a ‘demand’ which is created as a result of investment in marketing campaigns.

People will not automatically find your website and visit it directly. They find and visit your website in response to some online and/or offline marketing activity. This marketing activity can also include ‘word of mouth’ publicity.

So if majority of your sales and conversions are being attributed to direct traffic, you may get the impression that it is just your brand power which is driving sales and not the marketing campaigns. However this is not the case.

If you are still in doubt then pause all of your marketing campaigns for a week or two and monitor how it impacts the direct traffic to your website. Your direct traffic is likely to go down.

Customers generally do not convert on their very first visit to a website. A return visit is most likely to happen before a conversion or transaction takes place on the website.

One of the most common and easiest ways to return to a website is to type part of the website URL in the browser address bar. The web browser then auto-fills the remaining part of the URL and the user ends up directly visiting your website.

Because of this user behavior, direct traffic can end up being attributed a lot of traffic, sales and other conversions by web analytics tools.

For example, look at the report below:
ga wrong
The majority of marketers looking at this standard ‘All Traffic’ report in Google Analytics for the last three months will draw the following conclusions:

  • Organic traffic is playing a secondary role to direct traffic.
  • The majority of traffic and revenue is coming through direct traffic.
  • We need to speed up content development and link building to increase organic traffic to the website.

But now you know that all unknown traffic is reported as direct traffic by Google Analytics.

So on the surface it looks like 618,199 visits/sessions were direct, but it may actually be only 25,000 sessions which were from direct traffic and the rest were from display ads, email, organic,  social media and applications/campaigns in which the referrers were not passed.

Related Article: You are doing Google Analytics all wrong. Here is why

But this analysis does not end here, because you are still not looking at the complete picture.

Here is the complete picture:

scenario-1.1

Visitors do not always access your website directly and then make a purchase straight away.

They are generally exposed to multiple acquisition/marketing channels (like display ads, social media, paid search, organic search, referral websites, email etc) before they access your website directly and make a purchase.

So if you are unaware of the role played by prior marketing channels, you will credit conversions and e-commerce transactions to the wrong marketing channels, like in the present case to direct traffic.

If you look at the chart above, organic search is playing a key role in driving direct traffic to the website which eventually resulted in conversions and ecommerce transactions.

To get this type of understanding you need to understand and implement attribution modelling.

So the conclusion that organic traffic is playing a secondary role to direct traffic is incorrect.

Examples of Direct Traffic

In the following cases, a referrer is not passed and hence the traffic is reported as direct traffic by Google Analytics:

#1 ‘Type in’ traffic

Sometimes people try to visit your website by typing your brand name followed by .com in the address bar under the assumption that this will be your website address. If they succeed in visiting your website, all such traffic is reported as direct traffic by Google Analytics.

#2 Traffic from bookmarks

Let us suppose a user landed on your web page via Google organic search and then bookmarked the page. After 6 months, the user returned to your web page via the bookmark. His visit could now be reported as a direct visit by GA (as by default the campaign cookie expires after 6 months).

Note: If the user landed on your web page via Google organic search, bookmarked the page, and then later returned to the page, within 6 months via a bookmark, then his visit could have been reported as a visit from organic search and not direct. This is because by default campaign cookie expires after 6 months.

#3 Traffic from apps

The majority of mobile, desktop, and social media applications do not send a referrer. So traffic from such apps is reported as direct traffic by Google Analytics.

#4 Traffic from non-web documents

Non-web documents (Microsoft Word, Excel, PowerPoint, PDF, etc) do not send a referrer. So traffic from such documents is reported as direct traffic by Google Analytics.

#5 Traffic from desktop email clients

Visits that came from a link within a desktop email clients (like Microsoft Outlook) are all reported as direct visits by Google Analytics.

#6 Traffic from instant messenger (IM) and/or online chat rooms

IM visits that came from a link within an instant messenger (like Skype, Google Hangout) and/or online chat rooms are all reported as direct traffic by Google Analytics.

#7 Traffic from incorrectly tagged marketing campaigns

Incorrectly tagged marketing campaigns can cause the referrer data to drop. Google analytics ignores the referrer when it sees a campaign tracking code. For example, if you share a tagged link on Twitter with ‘utm_source=facebook’, then all the Twitter visits will be treated as ‘Facebook visits’ by Google Analytics.

But if you went one step further and used something like ‘utmSource=facebook’ (which is not the correct campaign tracking variable) while tagging the URL then Google Analytics will completely ignore the referrer and report traffic from Twitter as direct traffic.

#8 Traffic from web browsers which do not send referrer data

Sending of the referrer data depends entirely on the web browser and/or the redirect method being used. If a user’s web browser does not pass the referrer data then there is no way to get it. 

Whenever a referrer is not passed or is dropped because of technical reasons, Google Analytics is not able to determine the origin of the traffic source and report that traffic as direct traffic.

Sometimes a user’s browser privacy settings and/or add-ons used (like Firefox No Referrer Add on, ScriptSafe for Chrome) can cause the referrer header to drop and not passed. Private browsing, incognito mode, in private browsing and other similar settings, do not let the browser to pass the referrer data.

Here one thing worth noting is that Privacy settings and add-ons can not stop search engines like Google to send referrer data because they do not send original referrer header in the first place. That is why they are also able to bypass the HTTP secure connection protocol and can pass referrer from HTTPS to HTTP website.

You can also use the same tactic to pass referrer data.

#9 Traffic from redirected URLs which do not send referrer data

Sending of the referrer data depends a lot on the redirect method being used. For example, Internet Explorer 8 loses referrer data when following methods are used a redirect method:

Javascript:location.href and Meta refresh – 0.

Similarly, Internet Explorer loses referrer data when you click on a link that uses ‘windows.open’ JavaScript method or when you click on a link embedded in a flash application.

If you use the following redirect methods then there is no guarantee that all web browsers will send the referrer data:

Javascript:location.href

Javascript:location.replace

windows.open

meta refresh.

Use server-side redirects (301 and 302) instead of Meta and JavaScript redirects, to redirect visitors and search engines, as they allow all major web browsers to pass the referrer data. Give preference to 301 over 302 wherever you can, as 301 redirects have better cross-browser compatibility when it comes to passing the referrer data.

302 redirect often causes the referrer to be dropped. During HTTPs to HTTP redirect and vice versa, the referrer is not passed by default. All such traffic is reported as direct traffic by Google Analytics.

#10 Traffic from IOS ‘open in…’

When you use an option like ‘open in safari’ or ‘open in chrome’ in IOS, the referrer data is not passed. All such traffic is reported as direct traffic by Google Analytics.

#11 Traffic from a link which uses the ‘rel=noreferrer’ attribute

A referrer is not passed in case of visits that came from a link that uses the ‘rel=noreferrer’ attribute. For example:

<a href=”https://www.example.com/about/” rel=”noreferrer”>No referrer for you</a>

#12 Traffic from company’s firewall which does not send referrer data

Sometimes your company’s firewall settings can cause the referrer to drop. All such traffic is reported as direct traffic by Google Analytics.

Note: Sometimes errors in your script can cause the Google Analytics cookies to be reset, thus resulting in a direct visit.

#13 Fake Direct Traffic from Spambots

In the context of Google Analytics, fake traffic is defined as one or more fake hits sent to your GA property.

A ‘hit’ is that user interaction with your website that results in data being sent to your Google Analytics property. A hit can be a ‘pageview’, ‘screenview’, ‘event’, ‘transaction’ etc. A fake hit is the one which is generated by a spambot instead of as a result of a living breathing human beings who interacted with your website. At present, it is possible to fake any GA hit.

What that means, a spammer can send fake direct traffic, fake referral traffic, fake organic traffic, fake traffic from social media, etc. A spammer can fake events, virtual pageviews, screen views, hostname, request URI, keywords and even transaction and item data

In the context of Google Analytics, there are two types of spambots:

  1. Spambots which visit websites
  2. Spambots which do not visit websites

Spambots that crawl your website can visit your website without sending referrer data. All such traffic will be reported as direct traffic by Google Analytics.

Spambots that do not visit your website can send fake hits to your GA property by abusing measurement protocol.

If you see a sudden and massive spike in direct traffic with a bounce rate close to 100% and an avg. session duration close to 0 seconds, then most probably your website has been attacked by a spam bot.

To learn more about, how to reduce or even completely remove spam/fake traffic in Google Analytics, read this article: Guide to removing referrer spam and fake traffic in Google Analytics

Google Analytics can report direct traffic in two ways:

  1. As a traffic source
  2. As a marketing channel.

Direct traffic as a traffic source

In the context of GA, ‘source’ (or ‘traffic source’) is the origin of your website traffic. For example, in the case of ‘(direct) / (none)‘, ‘direct’ is the traffic source.

In the context of GA, ‘medium’ (or ‘traffic medium’) is the category of the traffic source as defined by Google. For example, in the case of ‘(direct) / (none)‘, ‘none’ is the traffic medium.

In order to see Direct traffic reported as a traffic source, navigate to ‘Sources/Medium’ report in GA:

Whenever a referrer is not passed or is dropped because of technical reasons, Google Analytics is not able to determine the traffic source and the traffic is treated as direct traffic by Google. In that case, GA sets the traffic source to ‘direct’ and medium to ‘none’.

Direct traffic as a marketing channel

In the context of Google Analytics, a channel or a marketing channel is a group of several traffic sources with the same medium. For example, ‘Direct’ is a marketing channel that can be made up of any number of traffic sources as long as the medium of the traffic sources is ‘none’.

In other words, a direct marketing channel can be made up of any number of traffic sources as long as the traffic sources are unknown to Google Analytics.

For example, in the case of traffic coming from Microsoft Word document, instant messenger (like Skype) or a mobile app, the referrer is not passed and hence Google Analytics is not able to determine the source of the traffic.

Because of that, all such traffic is treated as direct traffic by Google. 

In order to see direct traffic reported as a marketing channel, navigate to ‘Channels’ report in GA:

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Himanshu Sharma

Digital Marketing Consultant and Founder of Optimizesmart.com

Himanshu helps business owners and marketing professionals in generating more sales and ROI by fixing their website tracking issues, helping them understand their true customers' purchase journey and helping them determine the most effective marketing channels for investment.

He has over 12 years of experience in digital analytics and digital marketing.

He was nominated for the Digital Analytics Association's Awards for Excellence. The Digital Analytics Association is a world-renowned not-for-profit association that helps organisations overcome the challenges of data acquisition and application.

He is the author of four best-selling books on analytics and conversion optimization:

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