Last updated 4 September 2018 If you have been reading my blog articles over the past year, you might have noticed a disturbing trend. I’ve published 9 articles on customTask since the API was released. It might not sound like much, but I can’t think of a single feature in Google Analytics or Google Tag Manager that has so completely convinced me of its usefulness in such a short time. Read More…
A recent guide of mine introduced the Google Analytics adapter in Snowplow. The idea was that you can duplicate the Google Analytics requests sent via Google Tag Manager and dispatch them to your Snowplow analytics pipeline, too. The pipeline then takes care of these duplicated requests, using the new adapter to automatically align the hits with their corresponding data tables, ready for data modeling and analysis. While testing the new adapter, I implemented a Snowplow pipeline from scratch for parsing data from my own website. Read More…
Over the past few weeks, I’ve been coding like crazy. The three biggest outcomes of this frenzy have been this new blog design (switched finally away from WordPress and took the plunge back into the world static sites using Hugo), a new Google Sheets add-on for managing Google Tag Manager containers and assets, and a Slack integration in GTM Tools. In this article, I’ll quickly introduce the last two, as I’m writing a separate article about the site redesign. Read More…
When Google released gtag.js, the new, global tracking library designed to (eventually) replace analytics.js, many Universal Analytics practitioners and users were confused (see e.g. Jeff’s great overview here). It seemed like gtag.js wasn’t really solving any immediate problem, since analytics.js had done a bang-up job with Universal Analytics tracking for all these years. However, gtag’s modus operandi is the ability to leverage the same semantic information (distributed across dataLayer!) across a number of Google products, starting with GA and AdWords. Read More…
I really like Google Optimize. It has a fairly intuitive UI, setting up experiments is easy, and there’s integrations for both Google Tag Manager and Google Analytics built into the system. It’s still a JavaScript-based, client-side A/B-testing tool, so problems with flicker and asynchronous loading are ever-present (though this is somewhat mitigated by the page-hiding snippet). One issue with the Google Analytics integration is the difficulty of creating segments for sessions where the users were actively participating in the experiment. Read More…
Scroll depth tracking in web analytics is one of those things you simply must do, especially if you have a content-heavy site. Tracking scroll depth not only gives you an indication of how much users are digesting your content, but it also lets you turn meaningless metrics such as Bounce Rate into something far more useful. If you’ve already been tracking scroll depth in Google Tag Manager, you’ve probably been using either Rob Flaherty’s brilliant Scroll Depth jQuery plugin, or Bounteous’ equally ingenious Scroll Tracking recipe. Read More…
Holy visibility, Batman! Visibility is a seriously undervalued aspect of web analytics tracking. Too often, we fall into the trap of thinking that “Page Views” actually have something to do with “viewing” a page. Or that tracking scrolling to 25%, 50%, or 75% of vastly different pages makes sense on the aggregate level. So you will be very pleased to know that the Google Tag Manager team (who have been on FIRE recently), have just published the Element Visibility trigger. Read More…
5 years ago, on 1st October 2012, this lovely video popped up in Google’s Analytics Blog: It was accompanied by a blog post, which contained a brief look into many of Google Tag Manager’s key features, some of which are still relevant today. At this time, those of us who started using the tool immediately, or who had been beta-testing it, saw quickly what the key selling point of GTM was. Read More…
Universal Analytics can collect Page Timing data from users that load your pages. This data is populated in to the Behavior -> Site Speed -> Page Timings report, and it’s a very useful feature for optimizing your website. However, there’s a murky underside to this generous feature. The way Page Timings collection works is that when Pageview hits are sent from the site, a sample of these (1% by default) are automatically followed by a timing hit which includes page performance data grabbed from the Navigation Timing API. Read More…
Ever since the Lookup Table variable was introduced in Google Tag Manager, users have been craving for more. The Lookup Table does exactly what it promises: lookups. These are exact match operations, which are extremely inexpensive to perform, because they can only have a binary result: either the match exists in the data store being queried or it doesn’t. This performance stays constant even if the data store being queried increases in size. Read More…