27 September 2019: People That Count, Warsaw
The Custom HTML tag in Google Tag Manager is splendid. It’s your go-to tool when you need to run arbitrary JavaScript on the webpage. Some might even use it to actually add HTML elements to the page, but I’m willing to bet running JavaScript is its most common use. However, there’s a downside to Custom HTML tags, which is only made more apparent on single-page apps which do not clear the full page when transitioning from one state to another.

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Thanks to the intrepid detective work of Jørn Reidel and Ahmed Marof, it looks like one of the big hurdles for doing a full migration from using the legacy Google Analytics and Google Tag Manager SDKs to the latest Tag Manager + Firebase SDK is now a non-issue. The issue is, of course, Product-scoped Custom Dimensions or more specifically the lack of support thereof. Until now, I’d been holding against recommending the migration to anyone with Enhanced Ecommerce tracking set up simply because the documentation didn’t mention the possibility of sending these custom definitions to Google Analytics.

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Perhaps you didn’t know this, but there’s a really handy demo account for Google Analytics you can use to check out how Google Analytics works in a real business context (the data is from the Google Merchandise Store). However, you can access the account with nothing more than read-only access. This is annoying if you wanted to customize the setup. Worry not, I have a solution for you! Harnessing the awesome power of customTask, you can create a duplicate of the data collected on any website where you can modify the tracking (e.

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One of the big problems in Google Analytics’ data model is the immutability of historical data. Once a row of data is written into the data table, it is there practically for good. This is especially annoying in two cases: spam and bogus ecommerce hits. The first is a recognized issue with an open and public data collection protocol, the latter is an annoyance that can explode into full-blown sabotage (you can use the Measurement Protocol to send hundreds of huge transactions to your competitor’s GA property, for example).

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In my intense love affair with the Google Cloud Platform, I’ve never felt more inspired to write content and try things out. After starting with a Snowplow Analytics setup guide, and continuing with a Lighthouse audit automation tutorial, I’m going to show you yet another cool thing you can do with GCP. In this guide, I’ll show you how to use an open-source web crawler running in a Google Compute Engine virtual machine (VM) instance to scrape all the internal and external links of a given domain, and write the results into a BigQuery table.

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Scope in Google Analytics’ Custom Dimensions refers to how the value in the Custom Dimension is extended to all hits in the same scope. Hit- and product-scoped Custom Dimensions apply to the given hit alone - they are not extended to any other hits in the session or by the same user. Session-scoped Custom Dimensions apply the last value sent during the session to all the hits in that session.

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Google Cloud Platform is very, very cool. It’s a fully capable, enterprise-grade, scalable cloud ecosystem which lets even total novices get started with building their first cloud applications. I wrote a long guide for installing Snowplow on the GCP, and you might want to read that if you want to see how you can build your own analytics tool using some nifty open-source modules. But this guide will not be about Snowplow.

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Simo Ahava

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

Senior Data Advocate at Reaktor

Finland