Dark search, dark social & everything in between
Certain types of web traffic do not pass referral information on to our analytics programs, making it difficult to properly track these visits. Contributor Maggie Malek recaps a session from SMX West detailing how to handle this "dark" web traffic.
In an advertising world where tracking matters more than ever — where understanding our consumers and knowing exactly how to reach and target them is top of mind — dark search and social can be terrifying to marketers. Getting past this fear and understanding the data behind “dark” is exactly what Marshall Simmonds tackled in his recent SMX West session on “Dark Search, Dark Social & Everything In-Between.”
An industry leader since 1997, Simmonds is no stranger to deciphering search data. During his tenure as Chief Search Strategist for About.com, he was responsible for building the brand into the most successful content network on the internet. When About.com was acquired by The New York Times, Simmonds remained in the position, responsible for search strategy and exposure for NYTimes.com, Boston.com, IHT.com and About.com. Now he spends his days leading the team at Define Media Group, an SEO company that specializes in enterprise search marketing and strategic audience development.
As head of social at MMI Agency, I was definitely excited to see Simmonds speak. Any time I can help my practice prove value to clients, I am all in! The session was really awesome, and I took away some very actionable tactics to launch at my agency.
History of dark search and social
Simmonds first gave a quick overview of the history of the invisible (dark) web, which was recognized as far back as 2001. They knew even then, without the level of sophisticated measuring tools that marketers have today, that some web traffic just wasn’t trackable. Today, dark search and social is defined as any web traffic that can’t be tracked through our analytics programs.
Discovery of dark starts with direct traffic
“Direct traffic” refers to traffic that comes to your site with no referral string. This could be from someone typing your domain name in the URL box or following a bookmark.
In 2013, Simmonds and his team started to see a big spike in direct traffic, and they wanted to find out why. After all, they needed to know where traffic was coming from in order to protect their budgets and to truly understand the consumer journey.
Through their research, they discovered a formula for extrapolating dark search and social traffic from the direct traffic bucket in analytics tools, giving them back the credit for this traffic volume (More on that below).
Most analytics tools will put all no-referrer strings into one giant “direct traffic” bucket. Simmonds segments this traffic that lacks any link in attribution into three categories: dark search, dark social and dark mobile, and separates each segment by traffic source. Here is his breakdown:
|DARK SEARCH||Direct traffic||Apps||Browsers||Image search||Secure search||Misinformation|
|DARK SOCIAL||Direct traffic||Sharing apps||IM||Snapchat, WhatsApp|
|DARK MOBILE||Referral traffic||Apps||Android||iOS|
Let’s talk dark mobile
Mobile search shows no sign of slowing down; according to Simmonds’ data, it’s actually grown 115 percent in the last 18 months.
This growth has led to a rise in “dark mobile,” and here’s why.
Although Safari and the Google app pass on accurate organic referrer data, the Android search app passes referrer data as “direct.” Not good. Also, messaging apps are on the rise; people send links back and forth all of the time, and there is no way to track where people are coming from when they click a link from a messaging app.
So now you know what is considered “dark.” But what’s the big problem with big buckets of direct traffic in your analytics? If you are involved in any search or social campaign, you are losing out on credit because of these dark leaks. Simmonds’ goal is to empower search and social marketers with the data they need to attribute dark social and dark search to their campaigns, proving value.
To do so, he and his team did a study, looking at 149 sites in 78 categories with a total of more than 307 billion page views. After thoroughly analyzing all of the links and the data from this study, Simmonds and his team were able to create a new “dark” formula.
A formula for extracting your dark search and social data
So, how do we get around the direct traffic bucket to figure out where people are really coming from? It starts with human nature. It’s not realistic that people are memorizing and typing in URLs that are either several directories deep or very, very old. If they aren’t doing that, it means they are coming from links that have been shared in untrackable places such as email, social media and messaging apps.
So how do you pull that traffic out?
Step 1: Extract your dark social data
- Pull all of your direct traffic.
- Remove home page and section fronts.
- What’s left is dark social.
Step 2: Extract your dark search data
- Verify links against your social campaign(s).
- Filter for new users.
- What’s left is dark search.
You can use the formulas for dark search and dark social to help you decipher the dark mobile data, too.
There is very much an invisible web. But our search and social tools can’t see it or measure it. As you track measurement on a day-to-day basis, always be thinking about the following:
- Be aware of misinformation!
- You must quantify direct traffic.
- Search and social teams must work together to get good data.
- Google data is obscure.
- So is social data.
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