Readers of my previous blogs and posts might remember my obsession with clean data and transparency in digital marketing. My stomach hurts when I see bad implementations of Analytics, Tag Manager and even worse when the data is just plain wrong.
To help you avoid these nauseating moments here are 3 tips to get everything just a bit better.
1. Are you having duplicate transactions in your e-commerce reports?
How can it happen? Well, it can have multiple reasons, most common is the implementation of Google Tag Manager with 1 or more additional Analytics accounts added.
What is the impact? For one, your revenue figures will be wrong, you cannot allocate your digital marketing spend correctly and you make this Dutchman cry a little bit inside.
So how can see this? First of all, we need to identify if we have duplicate transactions, you will be able to recognize this by seeing a unique transaction ID counting the transaction twice or more times. I’ve created a custom report which you can download/link to your analytics here
Ok, I have duplicate transactions! Now what? The best approach is to contact the people who made this implementation mistake and get them to fix it. If you did it yourself feel free to leave a comment below and I’ll try to help!
2. Tag Manager containing way too many tags
How can it happen? 9 out of 10 times it’s a lack of knowledge when it comes to the tag manager implementation.
Tag manager is in a way a programming language on its own. Because of this, you can create tag’s that to a certain function like tracking a video play, pdf download or a scroll action etc. However what we see often is a tag for tracking a specific download, for example, which has been split up between many individual tags.
So if you have 100 PDF’s you want to download and you are setting up 100 Tags you’re doing it wrong.
The risk by not optimizing your GTM is double firing, tracking of double page-views, transactions etc. or even worse breaking your site. On top of that the more tags the “heavier” your solution becomes even with an asynchronous implementation.
3. You’re not filtering your data correctly
If you are reading filtering and have no clue what this means in analytics than it’s important to read on!
As most of you know, the internet can be a scary place. Full of unwanted traffic, spam sources and even our own staff can be in the way (From a data perspective that is).
So, we will need to start filtering as this type of traffic will impact your engagement rates, bounce-rates and overall performance in the analytics reports.
What can you filter on? Well, the easiest one is to make sure all the traffic is genuinely going to our website. You might notice in your reports that you received traffic from sources such as Reddit, CNN, BBC etc but when following back the referral link you end up on a spam page.
Filter based on your organization hostname(s) only. Everything else is spam
So that’s it! 3 Tips to make the world of conversion optimisation a little bit cleaner!
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