You are here: Tags / Google Analytics
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. The customTask API is a feature of the Universal Analytics library (used by Google Tag Manager’s tags, too).

Continue reading

When the Google Analytics Settings variable was introduced in May 2017, it resulted in a significant change in the Google Analytics tag user interface in Google Tag Manager. The default UI for editing a tag was stripped down of all GA-specific settings, and the new Google Analytics Settings drop-down was the replacement. Unfortunately, the bulk of Google Tag Manager articles online (including those on this blog) still refer to the old interface in screenshots and instructions.

Continue reading

A while ago I posted a #GTMTips post where I detailed the steps you can take to opt-out of all Google Analytics tracking and the DoubleClick redirects that often follow. It was a fun exercise, but because it relies on preventing requests on a tag-by-tag basis (using the ubiquituous customTask), it can be a chore to handle in large containers. In this article, we’ll continue with the theme of opting out from Google Analytics tracking by leveraging a solution provided by the tool itself.

Continue reading

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.

Continue reading

The steady increase in mobile use over the last years has introduced some new challenges for web analytics. It’s not just about mismatches in the tracking model (the concept of sessions is even more absurd for apps than it is for desktop browsing), but about something more fundamental, more basic. Think about it: if a visitor visits the website using a mobile device, there’s a significant chance of them losing internet connectivity and going unintentionally offline.

Continue reading

More often than not, much of what we do in web analytics can be automated. This applies especially to implementations, audits, configurations, and reporting. So when I’m faced with a menial, manual task that might take hours for me to complete if done by hand, I always look at what could be done with some scripting and API work. I want to introduce a couple of Google Sheets add-ons I’ve written and released to the public.

Continue reading

Autocomplete search is a tricky thing to track. The underlying logic is that when the user starts feeding characters into a search form, the search suggests results based on a limited input. If the user is not satisfied with the results, they can continue adding characters to the search, thus increasing the accuracy. Often there’s also the option to revert to a regular search with what they’ve already written. Tracking this logic in tools like Google Analytics is difficult, because there’s really no way to know if the search was successful.

Continue reading

Author's picture

Simo Ahava

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

Senior Data Advocate at Reaktor

Finland