A return to the dark side of social sharing

Dark Social

If you can, cast your mind back to December 2012 and this post on tracking Dark Social in which we explored the idea of a huge chunk of social data being hidden away in the Typed/Bookmarked segment within SiteCatalyst, rather than being allocated to Social Network referrals.

An ongoing challenge for any of us trying to demonstrate the value of social media to our businesses is that it can be very tricky to prove it. While we’re able to track direct conversions, it’s much harder to track those indirect conversions resulting from engagement. It’s not impossible to do, but does require more expensive and sophisticated tools than many businesses are able/willing to invest in without that proof of return, resulting in a chicken and egg situation.

This is one of the major reasons why being able to more accurately see the true level of socially driven traffic coming through to our site it so important. This year we’ve been having another tinker with the Dark Social segment to try and get as truer picture as possible.

Our new and improved segment definition looks like this:

Includes | Visit

  • Referrer Type equals Typed/Bookmarked (we only want to see this referrer as this is where our Dark Social traffic is hiding)

Excludes | Visit

  • Tracking code is not null (we’re looking for anything and everything without a tracking code on it)
  • Referrer Type equals (Add in all the other referrer types listed as we want to make sure the visit can’t be attributed anywhere else)

Excludes | Page View

Below is the January data from one of our UBM Live events (in the first Dark Social post we looked specifically at a media brand, this time we’re looking at an event brand) with data showing the impact that the new and improved Dark Social segment is having on our social results:

Page Views


Unique Visitors

All Visits




Visits from Social Sites segment




Dark Social segment




Social Sites and Dark Social Combined




And if we look at the Referrer Types Report and compare the results with and without the Dark Social segment applied, here’s what we get:

Return to dark social

This is a really important result as it gives us an indication of the impact that the community’s social sharing is having on traffic to our sites. Remember that due to the absence of tracking codes, we know that this isn’t social sharing which has been driven by our brand channels through our existing campaigns. This is our community being social about us off their own backs – that’s where the power of social media really lies and this segment is starting to help us prove it.

(As a follow-up to this post, I’m going to do another looking at the results for an event site compared with a media brand to see what impact the availability of content has on Dark Social sharing)


Photo credit: ‘Dark Matter Map’ by thebadastronomer is licensed under  CC BY-NC 2.0

Tracking ‘Dark Social’ – Uncovering the true value of your social media traffic

Back in July a colleague shared a blog post she’d discovered about how Twitter drives four time as much traffic as you think by Jonathan on awe.sm

The blog explains how referrers are a poor way of attributing traffic from social sharing, in that much of our social traffic actually shows up under ‘Direct’ (Google Analytics) or ‘Typed/Bookmarked’ (SiteCatalyst), rather than under t.co, facebook.com etc or ‘social sites’, as the analytics programme is unable to attribute the original referrer.

This is due to a number of reasons:

  • When a user clicks on a link in any kind of non-browser client (this could be Outlook or some of the mobile/tablet apps you use for social media), no referrer information is provided for that visit (if you didn’t come from a web page then you must have typed it into your browser) – so it’s attributed to ‘Typed/Bookmarked’ and you’ve just lost some of your social traffic. This also applies where people are moving from a secure site (https) to a non-secure one.
  • This means that a lot of social traffic is invisible to our existing analytics programmes and as a result, we’re not getting a true measurement of the value it’s providing us in terms of traffic and conversions. This unattributable social traffic is being called ‘Dark Social’.

So how can we start to get a handle on this situation? Well, a few months after the initial blog post, we stumbled across another one – ‘Dark Social: We have the hole history of the web wrong’ by Alexis C. Madrigal on The Atlantic.

Alexis explores how to take this ‘Typed/Bookmarked’ traffic and filter out the true typed/bookmarked pages, leaving us with the unattributed social media traffic.

I’ve been experimenting with creating a segment within SiteCatalyst which applies to all visits where the referrer equals Typed/Bookmarked, then excluded all other referrer types, all tracking codes, all newsletter URLs and website sections (these are more likely to be typed into the browser or bookmarked).

What we’re left with is unattributed URLs, which don’t have a referrer, and are too long to be reasonably typed in by hand. This is our ‘Dark Social’. So far the results look positive, I need to show the segment around to some more skilled SiteCat experts than I to make sure it’s pulling the right data, but assuming I’m not far off, it’s looking like 25% of our visits and unique visitors could be attributed to Dark Social – a massive increase on what we’re reporting today.

Have you had any successes with tracking Dark Social?