Data layer standards

I just listened to the latest episode of Rudi and Adam's Beyond Web Analytics podcast, all about data layer standards. This may sound like an esoteric subject but it's going to become really important in the future, and is key to out industry moving to the next level.

As technologies mature, there is always a tendency to standardize so that we can move to the next layer of abstraction. It means we've worked out the details of things that practitioners have embedded in their practices and we can move on to bigger and better things at higher levels.

So what is a data layer? In "traditional" web analytics implementations, you push information to your web analytics platform using its own platform-specific mechanisms. To record a "Newsletter signup" event in Google Analytics you might use:

_gaq.push(['_trackEvent', 'Newsletter', 'Subscribe', 'Customer list']);

in Omniture you might set:"event34";

If you wanted to switch between vendors or have something like an ad server conversion beacon inserted on the page, you have to write yet more platform-specific code. More code means more scope for error and for the events to fire on subtly different criteria, so your numbers never line up across systems.

A standardized data layer means instead you'll record things in a common manner and if you're using tag management you can very easily set up whatever analytics, ad server or other tools you want to fire on the same criteria. If well adopted we'll see platforms like Shopify, BigCommerce, Magento, CMSes and the like all supporting it and having turnkey web analytics implementations for 80-90% of use cases. Now that's a good thing so we practitioners can start working on more cool stuff and less tedious implementations and reimplementations.

This is a fantastic initiative and incredibly important. Check out the W3C community:

I'll be giving a talk on this next month at Web Analytics Wednesday Sydney.