The new features were unveiled by Nick Mihailovski, Pete Frisella and Andrew Wales in a session titled Optimize Web and Mobile Apps, Across Devices, Using Google Analytics.
You can watch the whole presentation here, and I recommend you do: it’s forty minutes well-spent, and covers some additional stuff that isn’t covered in this post. (It’s embedded at the foot of this post).
What is covered in this post is, in my opinion, the most significant part of the session as far as digital marketing is concerned. Let’s get stuck in.
Cross Device Measurement with Client ID
Cross-Device Measurement is related to one of the main ways we think Universal Analytics will change the way businesses look at their data. It’s all about how Universal Analytics gives us a better understanding of how visitors use multiple devices to access our content.
To illustrate this with some screenshots from the presentation, take a look at how “regular” Google Analytics will track three visits from three devices as three Unique Visitors, even if it’s the same person using all three:
You can see the problem: each visit on each device initiaties a Client ID (cid) which tells Google Analytics who that visitor is. With three visits from three devices, we’ve got three Client IDs which, as far as Google Analytics is concerned, is the same as three Unique Visitors.
Clearly, this isn’t optimal!
Luckily, Universal Analytics gives us a way of understanding when three visits is one person, or three people:
With Universal Analytics, we get a new parameter – uid, or User ID. This lets us tell Google Analytics that it’s the same person using mobile, tablet and laptop.
We’re no longer seeing this as three Unique Visitors, but as one Unique Visitor — so the distortion has been removed.
By itself, this is a huge change. We all know, from our own behaviour as well as that of our customers, that people are using more devices and switching from one to another with increasing frequency.
From a digital analytics perspective, having a tool that can’t tell the difference between three people and one person visiting three times is completely insufficient, and if your tools aren’t up to the job your analysis won’t be, either.
See, this is why we all need Universal Analytics!
To continue with the example, let’s say that someone accesses our website on a tablet, and then they switch to their laptop computer to complete a purchase.
With User ID, we know that only one person was behind us, but we’re still not quite getting the complete picture.
Here’s another slide from the session showing how it might look:
On the face of it, we’ve got one tablet visitor with $0.00 revenue, and one desktop visitor with $3.99 revenue. That makes tablet traffic look pretty suboptimal, and you might decide to ditch tablet users and focus on desktop users instead.
Once again, a suboptimal tool isn’t going to get you anywhere in life, let alone in actionable data analytics. So, how can Universal Analytics help us?
In a word: Cross Device Measurement. Okay, that’s three words but once you see what it does, you’ll forget my inability to count. Here’s how Cross Device Measurement would give us a more accurate view of the same situation:
Bam. Universal Analytics is giving us a picture of multiple-devices and how they’re used by our audience to collectively contribute to our overall conversion volume and our revenue.
If you’re thinking that this looks and feels a lot like Assisted Conversions, you’re exactly right. Just as the idea of Multi-Channel Funnels gave us an understanding of how certain marketing channels co-conspire to drive conversion, Cross Device Measurement tells us how our users hop from device to device, and tell us where we should be paying most attention.
But wait. It gets better.
Take a look at this:
Universal Analytics is going to give us device-based conversion paths! Again, analogous to cross-channel conversion paths, this is really going to blast open our understanding of how users are interacting with our content. (Apologies for the fuzzy image by the way, it’s the best I was able to get.)
The session then homed-in on a couple of angles as to how this can give us insight.
First up, we might discover that a certain type of screen-to-screen behaviour tends to elicit a lot of conversions:
In this example, users that switch from desktop to tablet spend a lot more on-site than users that complete the reverse journey, or that stay on desktop all the way through. After patting ourselves on the back for having such a great tablet-optimised site, we might decide to put something on the homepage to tell desktop users to try us on their tablets.
Which, to take a step back for a second, is pure digital analytics. Observe a behaviour, look for ways to encourage it. Perfect!
Secondly, how about this:
It’s reminiscent of Assisted Conversions again, and it tells us some pretty important information. On the face of it, with only $0.99 in revenue we might decide that mobile isn’t a terribly important platform for us.
However, when we bring in transaction data from other platforms, we can see that the user that accessed our content on a mobile phone made purchases totalling $17.98 on other devices. So while smartphones might not be great as a final touchpoint, we’re getting an understanding of the importance of the supporting role they play in the process.
And if that’s not made you dizzy, think about where this could go. We already use Multi-Channel Conversions in our reporting, when we have Cross-Device Conversions to play with too, the insight is going to increase exponentially.
We’ll probably see ways of being able to splice the two sets of data here and there; so we might see that a certain campaign played a pivotal role in early-stage awareness for users on smartphones, but that a completely different campaign did the same on tablets.
As I said before: bam. There’s no timeline as to when we can expect this to be available publicly, but still: bam!
Turning mobile on its head
Digital marketing continues to become more and more data driven and with additional features being made widely available – in a free product, let’s not forget – the quality and depth of that data is always increasing.
So, are you as excited about this new feature as I am? How do you envisage this new dimension of reporting being useful to your organisation?