How we handle GDPR article 17 requests using Google Tag Manager and email?

FYI: Also try our GDPR Delete tool

We needed an easy way to delete users from our Google Analytics Free to comply with GDPR article 17 and we wanted it to be as easy as possible.

We succeeded and decided to make it easy for you as well – and yes it is free, but we would appreciate it if you helped us spread the word.

Here is what we did and what you should do!

So! we wanted to spend as little time as possible doing the implementing as we have very little time and many things to do.

The solution has 4 steps:

Step 1 – provide the user with easy access to their clientId

Step 2 – make it easy for the user to send us their clientId

Step 3 – delete the user’s data with this tool

To do this we needed 2 things.

  1. To read the clientId while the user is on our site.
  2. Write out the clientID to the user, so he/she can copy/paste it to us.

We decided that Google Tag Manager (GTM) was a good tool for this.

Part 1: Reserve a spot on the website for the clientId

We decided that the user should click on some text to reveal the clientId. So we added this HTML to our page.

<p>Your Client Id on this page is: <i id=”clientId”>[CLICK TO REVEAL]</i></p>

Part 2: Monitor clicks on “clientId” element then write the clientId

In GTM, create a trigger and call it e.g. “Get-Set clientID”


Configure to Click ID, equals, clientId

Click Save

In GTM, create a new Tag of the type Custom HTML

Paste following code:

(function(){(function(){ function getClientIdCookie(name) {  var value = "; " + document.cookie; var parts = value.split("; " + name + "=");  if (parts.length == 2) return parts.pop().split(";").shift(); } var clickedElement = document.getElementById("{{Click ID}}"); var _ga = getClientIdCookie("_ga"); if(!!_ga) {   var parts = _ga.split(".").reverse();   if(parts.length > 2)   clickedElement.innerHTML = parts[1] + '.' + parts[0]; })()

Add the trigger we created above


Click Save. Click Submit. Click Publish

Load the page where you added the HTML text. This is how the result looks on our site.


When the user clicks the [CLICK HERE TO REVEAL] text is looks like


See for yourself here.

We would love ideas and feedback. Let us know on Twitter,  or via the chat on our main site.

Visualize your raw GA data instantly with this Power BI template

Okay, so you’ve implemented SCITYLANA and pulled out loads of nice hit-level data from your Google Analytics account.

Now you want to put all that data to impressive use! But what to focus on and how to get started?

Use this free Power BI template

Although SCITYLANA works with all sorts of tools (BigQuery, Data Studio, Tableau, Targit, Qlik, etc.), we suggest you start with this template for Power BI.

We’ve chosen Power BI as our starter tool, because it’s free, easy to use and extremely versatile when it comes to analyzing, reporting and integrating data.

In this post we’ll give you a quick rundown on the contents of the template. At the end, we’ll also show you how to populate it with your own data.


The first report tab in the Power BI template gives an high-level view of your traffic.

You can use each visual as a filter. For example, clicking on Organic search in the pie chart will immediately filter all other visuals.

You can also define a custom date range using the slicer in the upper right corner.


Traffic sources

The next tab shows your traffic sources. The bar chart shows all traffic sources, but you can easily filter these by channel grouping using the slicer to the right.


We’ve included a bubble chart showing visit engagement by channel grouping. The y-axis shows the average number of pages viewed by a session, while the x-axis shows the average time spent on each page.

Notice the Organic Search bubble in the upper right corner? These sessions view many pages and spend a long time on the site.

Content usage

What’s special about this report? Well, it shows Hostname (domains) and Page combined with Sessions.

In GA you actually can’t do this. You can’t combine Hostname or Page with Sessions. This is because of the way GA has organized its data storage.

What is great about the report tab below is that you can easily filter your top pages by hostname. Simply click on one of the domains in the bar chart to the left, and you will see the other one changes immediately.


Visiting time

Here you can see traffic during working hours, weekends and even seasons such as summer or winter. Again we’ve gone a bit beyond what you can do in GA. We’ve added a calendar and a time of day dimension with more interesting attributes.


Now comes our favorite part: Clickstreams! This is kind of the “proof” that we deliver hit-level GA data. Each row is a hit (a pageview or en event).

You can see exactly what individual visitors do!



Geography: Isn’t that more or less the same as in the GA interface? Not quite! The treemap in the upper left corner divides North Americans into Northeast, West, South, and Midwest. Yet this dimension doesn’t exist in GA!



Waiting for another surprise? Well, this one is not that special, but nonetheless useful. It shows statistics on devices, browsers and operating systems.


How to use the template with your own data

  1. Sign up for and implement SCITYLANA (it’s free!)
  2. Start a new data extraction so that your GA data is downloaded to your hard drive
  3. Download and install Power BI Desktop (it’s free!)
  4. Download and open our Power BI template
  5. Enter the path of the data folder (the destination you chose during step 2)



Now it’s your turn 🙂 Do you have ideas on how to visualize GA data in new interesting ways? Please let us know and we’ll add them to the template.

What if I could just Ctrl+Copy ALL of my Google Analytics data and Ctrl+Paste them anywhere I would like?


That would be great, certainly fun and probably very powerful!

Well… some people have already been doing this for a while.

The challenge: GA data are aggregated and not super suited for moving anywhere else. I’m not stating that you can’t move it already, but just that aggregated data has a lot of limitations. Behind the scenes, GA tracking data (hits) are counted, grouped, packed and stored in a fixed number of buckets. This is actually pretty smart and practical… when these buckets fit my certain needs.

The frustration: But if they don’t fit my needs?


The solution: SCITYLANA makes sure you can access the original hits and enables you to Ctrl+copy/paste non-aggregated GA data to a destination of your choice. We recommend everyone to store the data in a database and make some really great business decisions using your favorite visualization tool. We have already seen our customers using the hit level data in Microsoft Power BI and Excel. We hope to see it in Tableau and Data Studio soon too.

Psst…! You can try it here