Agile analytics isn’t a novel concept in any shape or form. Things like feedback loops and process-oriented development seem to integrate flawlessly into the analytics paradigm, at least on paper. Heck, there’s even the Build-Measure-Learn framework for continuous development. It would be difficult to argue that analytics doesn’t have a role in something with measure in the name! However, past three years of working at Reaktor, one of the world’s top agile technology houses, have introduced me to a whole new set of problems with integrating an “analytics mindset” into an agile workflow, or an “agile mindset” into the analytics process.

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Last updated 13 March 2024: Clarified that you can add a trigger like Initialization – All Pages as a Custom Evaluation to give the Zone full access to page state. Google Tag Manager supports loading multiple containers on the same page. It’s useful if you have multiple companies or organizations working on the same site, but for one reason or another (e.g. governance) you want to restrict access to your main container.

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Last updated 9 March 2018 with some new tips. The Scroll Depth trigger in Google Tag Manager has a lot going for it. Tracking how far users scroll down a given page has long since been recognized as an important cog in the engagement tracking machine, and there have been really great solutions for implementing scroll depth tracking for web analytics over the years. With Google Tag Manager’s native Scroll Depth trigger, it’s tempting to think we now have a be-all end-all solution that covers all the bases.

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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.

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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.

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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.

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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.

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