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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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(Updated 13 August 2017) A little over a year ago, in April 2014, I wrote the post “Advanced Form Tracking In Google Tag Manager", and it's been at the top of my best seller list ever since. Turns out that many people are rightfully passionate about making the web forms on their websites as fluid and intuitive as possible, since a web form is often the only thing that stands between a prospect and their transformation into clienthood.

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A recent update to Google Tag Manager introduced a feature which has been on the wishlist of many users for a long time. It's called Tag sequencing, and its purpose is to facilitate the sequential firing of Tags. The idea is that you can specify a setup and a cleanup for each Tag in your container. This article is intended to function as a quick tour of the feature.

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The web is stateless. It's basically blind to your past, and it does a poor job of predicting what you might do in the future. When you browse to a website, the browser requests the page from the web server, and then proceeds to render it for you. This is a detached, clinical process, and any personalized or stateful data transfer is left to the sophistication of your web server.

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Simo Ahava

Husband | Father | Analytics developer
simo (at) simoahava.com

Senior Data Advocate at Reaktor

Finland