Google is taking Google Analytics (GA) in a new direction, focusing on making analytics more relevant to marketers – the people making decisions about budgets – than to just analysts and webmasters. GA took as its starting point the questions that marketers have been asking of their data for years. Additionally they are making the technology simpler to install and debug. 

The big thing is a new tracking method: user-centric, multi-sessional, multi-device tracking. When I talked about this at Google recently, I used Viv, our client services team leader at Periscopix, to illustrate what the changes mean.

Viv’s favourite website is Etsy. She recently bought a brass lobster from there, apparently this lobster serves no actual practical purpose, but that’s another story. Her journey to that purchase might have looked like this:

  • Viv started by searching for Etsy on her work laptop; she browsed the site, and then registered with Etsy for updates on relevant offers.
  • On her train home, she checked the brass lobster on her iPhone.
  • When she got home, she got out her new iPad to have a final look (everything, even brass lobsters look better on an iPad) and made the purchase.

That’s great for Etsy, which was able to provide all the right browsing experiences for Viv to make her decision. But if I was an analyst, or a marketer at Etsy, Viv is a nightmare; I wouldn’t be able to get a full picture of what she’s doing.

I’d know she started with a Google search for Etsy, browsed the site and registered. And even though she logged in on her iPhone and iPad using her unique registration number (and would then be given a new logged in user ID, that’s not personally identifiable), I wouldn’t be able to connect those actions. I’d see her as three separate users on three separate devices.

That’s not very useful for Etsy. In this instance, they would have learned that iPad users are brilliant and spend lots of money, and that desktop/laptop users don’t spend anything.

The keyword she used originally would have received zero credit and the sale would have been attributed most like to a brand term or direct visit, and yet Viv’s journey started with a search, on a laptop.

It would, in effect, look something like this:

Periscopix - Econsultancy GA post image 1

But there are obviously things that are common across each device that you could connect, in order to see that those three visits are from the same person, and that’s exactly what GA is doing.

It ‘stitches’ the logged in user ID to the original unique user ID, and the purchase to the logged in user ID. The end result is that we can now see one user using three devices and making a purchase.

Now we have something more joined up, like the below:

Periscopix - Econsultancy GA post image 2
This is dynamite for anyone with a transactional website, or a site that requires a registration or login interaction, so you can understand the true user journey.

Google have realised how many practical applications there are for this. For example, it will be possible to stitch online and offline purchase. If you want to buy a sofa, you might research it online, but you’ll probably want to go and sit in it, and bounce up and down to try it out.

Now, you connect the online research with a customer purchase in the shop, if you have (for example) a loyalty card, or customer number, or postcode – anything that can tie that customer to the website activity.

That has implications for attribution, too. For example: Superdrug has a loyalty card. Let’s say Viv looks at nail varnish online, but wants to buy next time she’s in town.

So if she browses online, then buys offline, that offline purchase could be tied to the online activity – such as a search -  that initiated the offline sale. . Good news if you are running a PPC campaign for Superdrug.

In the same launch we learned of so many other exciting new Google Analytics features that should keep us in the world of web analytics very busy for the next 12 months. Think what we can do with free attribution modelling for all, inter-session analysis, sequential intra-session analysis, data imports. The list goes on…

All this is based on a much-simplified tracking system, which makes tracking a lot easier to manage and to spot (and fix) issues, with a reduction in cookies from at least three down to one. Ultimately, this means that you’ll spend less time paying people to fix problems, and more time on proper analysis that will improve the effectiveness of your marketing.