How to Identify Dark Traffic on Analytics

A significant portion of your website’s traffic goes unaccounted for. This makes it nearly impossible to properly track your marketing efforts, which eventually skews your strategic decisions based on how a campaign might (or might not) be performing.

In this article I will explore how you can identify ‘dark traffic‘, and what analytic tool techniques you can use to ensure traffic to your site is correctly tracked. Doing so will bring true clarity to your marketing campaign decisions.

What is ‘Dark Traffic’?

Website analytics tools commonly divide total site traffic into search, direct, and other referring websites, depending on the source or medium of where each originated.

It’s common to have somewhere between 10–20% of your site’s traffic from visitors typing in the URL directly (‘direct’ referrals). If this number is too low, you may want to consider your brand awareness. But if that number is too high, you’re wandering into the realm of dark traffic.

Dark traffic arrives at your website from a URL that’s difficult to track, and is typically included under direct traffic in analytics programs, because it lacks a proper referrer string to help identify the original source.

Generally speaking, direct traffic is supposed to be made up of people visiting your website directly. However, direct traffic numbers tend to be over-reported, as many visits from other sources end up getting incorrectly lumped together.

Is Dark Traffic a Big Deal?

So, while your direct numbers are artificially inflated, results from organic search, email, or social media are understated. That’s dark traffic at work.

But what kind of discrepancy are we talking about? As much as 60%, according to an experiment conducted by Groupon.

They wanted to examine the changes in organic search and direct traffic; comparing the results from a specific period to recorded traffic numbers from the same day and time of the previous week.

They started by completely deindexing their site, narrowing in on traffic to their pages relating to a specific location (such as “Restaurants in San Francisco”), which generally don’t receive a ton of direct traffic (because they’re not memorable and would be difficult for users to actually type out).

During this test they also noticed a huge difference based on browser type as well. While desktop-based referrals tend to be among the most reliable, Internet Explorer was still misrepresenting direct traffic by about 75%!

This impressive, yet gutsy, move ultimately revealed substantial misrepresentations of both categories, which has a huge impact on those who attempt to measure, analyze, report, and make decisions based on web analytics data (that’s you).

Why is ‘Dark Traffic’ Important?

Let’s say a friend sends you a Buzzfeed article, like this gem – 23 People Who Had Absolutely No Idea What They Were Doing in 2015 – through email.

The next morning, you fire up your favorite desktop email client after making the morning coffee, see the undeniably catchy title, and click-through to have a good laugh.

That visit will probably be misrepresented as direct traffic on Buzzfeed’s analytics program.

The likelihood of someone actually typing in that URL – http://www.buzzfeed.com/crystalro/people-who-had-no-idea-what-they-were-doing-in-2015 – is extremely low. No sane person would remember that, let alone type it out by hand.

The visit described flies ‘under the radar’, overstating direct numbers while understating the impact email actually had.

Where else does this commonly occur?

• Links inside email and social desktop or web applications.
• Traffic from secure, https-enabled sites to non-secure ones.
• Non-web based files, documents, PDFs, presentations, etc.
• People who’ve used image search.

Bad decisions at a strategic marketing level can happen if you’re seeing misrepresented traffic levels from these sources, with many channels (like search, email and social) not getting the credit they fully deserve.

All the great work you’ve been doing lately on building Twitter engagement might not get the internal support (read: additional time, funding and team members) it deserves if the numbers are being underreported on a consistent basis.

The good news is, you don’t have to continue flying blind. Instead, you can start taking back control and improving how you identify dark traffic.

How Do You Identify Dark Traffic?

It’s impossible to correctly categorize 100% of dark traffic. However with a few simple methods, you can begin figuring out how you it might be affecting you, and how to prevent as much of it as possible going forward.

Step 1: Utilize Google UTM Parameters When Possible

One of the best ways to gain control of dark traffic is to properly tag all links on campaigns or content that you control using Google UTM parameters.

Google UTM codes are simple parameters (or strings) appended to the end of a URL to help define extra information about that specific link. Here are the major categories you can (and should) use:

• Campaign Source (utm_source): Identify a particular search engine, social network or email campaign (e.g. Bing)
• Campaign Medium (utm_medium): Identify the specific medium as either social, email, cpc, etc.
• Campaign Term (utm_term): Typically reserved for paid search or ad campaigns.
• Campaign Content (utm_content): Typically content-based in nature (to help you classify one ad creative against others), or variations of content (for example, A/B conversion testing)
• Campaign Name (utm_campaign): Helps you track results based on your own internal promotion or campaign name, while also helping you relate to a particular keyword or topic as well

Remembering and writing these by hand is clunky until you get used to it, but fortunately there are a variety of tools and builders readily available.

The first is Google’s own official URL builder, which helps you simply add in details for each section, and will output the new tagged URL for you.

Below’s an example of the parameters we used for the campaign to promote WebSite Auditor’s content editor to our newsletter subscribers.

There are also some time-saving third-party tools, like this Chrome Extension, which helps you quickly create a tagged URL on the fly while looking at a particular web page.

If you’re working with a team or creating these in bulk, a worksheet can help you manage and coordinate the chaos.

Step 2: Create a Direct Traffic Segment Report in Google Analytics

The second technique for identifying dark traffic is through creating a new segment in Google Analytics.

The idea is similar to Groupon’s method mentioned earlier, where you’re filtering out traffic to ‘popular’ pages on your site that actually do receive a large amount of direct traffic naturally; for example, the homepage, important product or service pages, and typically main section pages commonly located in your primary navigation.

That way, you’re able to quickly identify all of the direct traffic to the ‘longer’ pages (like the Buzzfeed example earlier) which generally don’t receive a lot of direct traffic naturally (which is therefore probably overstated).

An additional method helps segment out any URLs from subfolders or subdirectories, falling in line with the same logic that difficult or complex URL strings probably aren’t remembered by users and then typed out directly by hand.

If you’re not comfortable manually creating these in Google Analytics, then you can also utilize some pre-built methods, like these examples from Gravity Search Marketing. By simply clicking a link, you’re able to add and customize the new segment to your liking.

Step 3: Look for ‘Dark Social’ Correlations with Existing Campaigns

The third method builds on the previous two, helping you to go in and correlate what you’re seeing with existing marketing campaigns (after ‘real’ direct traffic has been pulled out of your analytics view).

Unfortunately, you can’t do much to past campaigns to help give you insight, but you can start with spikes to see where promotion may have impacted or influenced direct visits.

Adding additional segmentation for new or returning visitors also helps here, depending on your promotional efforts (i.e. new blogger outreach or an email newsletter to your existing customers).

Depending on your company’s tagging consistency with paid search and email, now you can go back and begin cross-referencing the percentage of direct traffic to long URLs which might be the result of untagged social campaigns.

Conclusion

‘Dark traffic’ is already affecting your site, skewing your analytics, and making it tough to figure out how your marketing is (really) doing.

You’ll never be able to fully identify all traffic, but by following the steps above, you’ll have a far greater understanding of where your traffic is coming from, and know how to make better marketing decisions because of it.

Have you spotted ‘dark traffic’ affecting your site, and if so, how have you dealt with it? Let us know in the comments below!

Source:https://www.searchenginejournal.com/definitive-guide-dark-traffic-what-how-identify-it/160496/?ver=160496X3