As a B2B marketer myself, I personally understand the frustrations of going into your analytics dashboard and seeing that “direct traffic” makes up a substantial portion -- it may even be the primary channel source -- of your visits and leads. But if you’re like many marketers, direct traffic now probably makes you feel like this: ¯\_(ツ)_/¯ You see it as unfortunate that you get a lot of direct traffic, but you’re resigned to the fact that it seems like there’s not a whole lot you can do about it.
However, direct traffic is actively detrimental to your marketing, and you should want to decrease your direct traffic as much as you can. We’ll discuss a few ways you can do just that.
Decreasing Direct Traffic
But first, we must understand why direct traffic is a bad thing. Let’s start at the root of the direct traffic problem. Direct traffic is typically defined by marketing analytics as any time a visitor manually enters your URL. But in reality, just about every marketing analytics product considers any visitor who doesn’t have a referral source as direct. A common behavior that gets classified as direct is traffic from untagged (or improperly tagged) social posts/ads and untagged emails. Rather than having its own filter, it becomes the catch-all bucket for traffic that doesn’t qualify for any of the other filters.
Essentially, direct traffic is a lack of attribution, not a channel in itself. If a visitor can’t be attributed to a specific channel, it goes into the direct bucket.
The more direct traffic you have, the less useful data you have to work with.
The tangible problem for marketers that the lack of attribution creates is that direct traffic data is not actionable. Because it’s not really a channel like the rest of your marketing mix, the only levers you can manipulate on direct traffic is to yell out your URL even louder or try to convince people to bookmark your page. Both of those options sound pretty terrible. The more direct traffic you have, the less useful data you have to work with.
(Note: real direct traffic isn’t bad. For example, friends and partners of the company likely visit directly. It just means people know you well enough to know or be able to figure out your URL.)
If you keep up with the B2C marketing analytics world, you would have heard that the rise of mobile apps has driven a big increase in direct traffic -- it’s what they call “dark” traffic. Because mobile apps communicate with the mobile web slightly differently -- they don’t pass a referral source -- web analytics can’t attribute the visit to a channel source. And so you end up with a lot of direct traffic.
For most B2B companies, however, dark mobile traffic is not as big of a problem. So what can B2B marketers do about it? How can you clean up your direct traffic channel?
Fortunately, there’s a few things B2B marketers can do to decrease their oversized direct traffic and correctly assign visitors and leads to their true channel sources.
Essentially, direct traffic is a lack of attribution.
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View-Through Conversion Attribution
The first thing you can do is look at what is called view-through conversions. Digital ad technology is rapidly maturing, and we’re now at the point where it’s possible to tell whether a person viewed an ad (typically a banner display ad) and then went to the site later, without ever clicking on the ad. The ad may have introduced first awareness, name recognition, or just reminded the viewer to look into the product or company. When they later type in the URL directly, that visit will show up as direct, unless their analytics has view-through conversion attribution capabilities.
With view-through conversion, you’re able to understand the context behind the direct visit (e.g. they saw an ad) and can make smarter decisions because of it.
Anonymous First-Touch Attribution
When a visitor goes to a B2B website, the goal of the website typically is to get the visitor to fill out a form because that turns the visitor into a lead. That form fill enters them into the marketing automation system and allows marketers to start sending lead nurturing content -- a key part of the B2B marketing process.
However, because marketing automation focuses on lead creation and lead nurturing, it has one big gap that results in a large amount of direct traffic. When visitors come to the B2B website, they’re anonymous until they fill out a form. So if a visitor comes to the website through search, leaves without filling out a form, and then comes back at a later date by manually typing in the URL and fills out a form, that conversion will be counted as direct traffic. It’s like the first visit (via search) never happened.
The solution? Anonymous first-touch attribution. On today’s internet, you’re never truly anonymous. Just about every site places a tracking cookie on every visitor and gives them a cookie ID that persists from session to session, so that they don’t get a new ID every visit. Going back to the previous scenario, advanced attribution connects the cookie ID from the first anonymous session with the cookie ID from the session where the visitor filled out a form. This communicates that it is the same person who made both visits, and that the real first touch wasn’t direct. Rather it was from search, which is more accurate and a lot more meaningful.
Additionally, you could see how marketers would want to apply these two concepts to similar situations. For example, if someone visits the website from a non-direct channel (social, for example), leaves, and then ten minutes later re-enters the site directly and fills out a form.
A smart attribution model would credit that lead creation to Social, rather than Direct. How long that time window is, is hard to say because every industry and every company has a slightly different customer journey and experiences different customer behavior.
Looking At The Data
To see how big of a problem direct traffic is causing, and to see how much impact view-through conversions and anonymous first-touch tracking has, we looked at the data for our own website. Here’s the percentage of our leads that are labeled as “direct” (from the months of July-September 2015), according to Hubspot and Bizible.
Hubspot: 9.3% direct
Bizible: 5.2% direct
(Also, according to Hubspot and Google Analytics, direct traffic is the source for 45-55% of our web visits.)
Because Bizible’s marketing attribution is able to track and connect both anonymous first-touch visits and view-through conversions, we are able to decrease our meaningless direct traffic channel by nearly 50%. To be clear, this doesn’t mean we lost traffic -- rather, we were able to correctly attribute nearly 50% of what would have been direct traffic into their real channel sources.
Cedexis discovered that 60% of leads that Marketo was saying were direct traffic were actually coming from some other referral source.
That’s a great improvement, but we’re confident that the delta (~50% improvement) is actually on the low side for the typical B2B company. Because we do very little to no brand advertising, view-through conversions has a smaller impact for us than for the average company. For companies that invest in brand advertising, we’d expect the percentage of leads from the direct channel to drop even more significantly.
For example, after using Bizible, Cedexis discovered that 60% of leads that Marketo was saying were direct traffic were actually coming from some other referral source. And it’s had a big impact. “With this data,” says Rob Malnati, VP of Marketing, “we have been able to streamline our campaign attribution reporting and make better investment.”
When you’re not investing much time and money on your marketing channels, it’s possible to get by using just the free or included analytics tools. But as you increase your spend and add different channels to your marketing mix, it is increasingly important to be able to dig into the data and know that the data you’re basing your budget allocation on is accurate.
Now that we have better signals to more accurately categorize and attribute our traffic, I rarely think about direct traffic anymore. It’s no longer dominating our channel source data and clouding our analysis.
It’s a good feeling.