NOTE! This solution has been upgraded, and the new approach can be found here. If you’re unfamiliar with the lingo, cross-domain tracking is a hack used by Google Analytics to circumvent the web browser’s same-origin policy. Essentially, the policy dictates that browser cookies can only be shared with a parent domain and all its sub-domains. In other words, domainA.com and domainB.com do not share cookies. Since Google Analytics calculates sessions and users by using a cookie, this is problematic.

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I’ve been meaning to write about Google Tag Manager for mobile apps for such a long time. Finally, I have some great use cases to share, as well as some useful examples for implementing GTM for iOS. That’s right, this is an iOS guide, and, to be more specific, geared towards a successful Swift implementation. If you didn’t know, Swift is a relatively new programming language, developed by Apple for iOS and OS X programming.

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So, looks like iOS 9 has built-in support for integrating “content blocking” extensions on your iPhone. Now, blocking ads and other intrusive content is nothing new, nor do I want to get into a debate about whether it’s a good thing or not. But as a data geek I’m very interested in knowing just what share of my site tracking has some content blocker enabled. In this post, I’ll show two tricks (easy and advanced) to expose these content blockers.

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Here’s an interesting and hacky use case for you. It’s all about uncovering bounce metrics for visits which originate from organic Google search results. In particular, the metric we’re interested in is how long user dwelled on the landing page after arriving from organic Google search AND returned to the search engine results page (SERP) using the browser’s back button. The inspiration for this post came from an audience question at the Best Internet Conference in Lithuania, which I recently attended as a speaker.

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Every now and then we want to create a bridge between the stateful machines we send data to (e.g. Google Analytics), and the stateless environment where we collect the data itself (e.g. Google Tag Manager). This is not easy. There is no synergy between Google Analytics and Google Tag Manager which would let the latter understand anything about things like sessions or landing pages or Bounce Rates. One thing we can reliably measure, however, is whether or not the visitor is a New User in Google Analytics.

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Enhanced Ecommerce is undoubtedly an excellent feature of Google Analytics. It provides us with a set of reports that truly extend the capabilities of funnel-based website analysis. As I’ve shown before, it’s also very useful for tracking other transactional events on your site, such as content engagement. However, here’s the thing. It’s not very easy to implement. Even if you get everything right according to the documentation, there are still quite a number of pitfalls, and many of the learnings emerge only through experience.

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Unfortunately, iFrames still exist. They are used to embed content from one page into another. Frames are horrible, nasty things, very often riddled with cross-domain problems, performance issues, responsive design obstructions and other crap from the nether pits of hell. Regardless, if you’re stuck with an iFrame which also collects data to your Google Analytics property, for example, you probably want to prevent at least the first Page View from firing, since otherwise you’ll be double-counting Page Views: once on the main page and once in the iFrame.

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