Tracking Data Studio Report Usage via Google Analytics

Did you know you can track your clients data studio report usage via Google Analytics?

Trackify recommend setting this up to see who is and isn’t using all those lovely dashboards you’ve set up!

To add tracking to your reports, follow the following steps:

Step 1

For this tracking we recommend setting up a new Google Analytics Account so you don’t risk skewing any existing data. Setup a new Google Analytics account here. We recommend excluding your personal IP address if you are responsible for building the dashboards. You can find out how to do this here.

Trackify recommend making the account name something recognisable such as ‘Data Studio Tracking’ and the website URL ‘’ as below:

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Step 2

Once your account has been created - make a note of your property ID under Property Settings.

Then go over to your Data Studio report in ‘Edit’ Mode and click File > Report Settings

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Enter your noted Property ID under ‘Google Analytics Tracking ID’

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Click out of settings and this change will be saved.

Step 3

Test your setup by changing to ‘View’ mode in your Data Studio Report and watching your data filter through into Google Analytics Real Time Reports. If you’ve already excluded your IP address this won’t work but you can still test using Google Tag Assistant.

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Step 4

As you can see above, the report URL is coming through as the page URL and the Report Name & Page Name is the Page Title.

I recommend having a standardised naming format for all of your Data Studio reports such as:

‘Client Name’ - ‘Report Name’

E.g. Auckland Barbers - Adwords Performance Report

This way you can easily create reports and filter by client name etc.

Step 5

Optional : Create a Data Studio report to see your top used Data Studio reports.

Here’s a free template designed by Trackify for you to use:

Happy Tracking!

How To Easily Set Up your Shopify and Google Analytics Enhanced Ecommerce Integration

Setting up eCommerce tracking in Google Analytics isn't always straight forward.  However, if you're using Shopify to run your online store you're in luck! 

Shopify have made it really easy for you to see your Ecommerce Data within Google Analytics but first you'll need to set it up using these 4 steps:


Step 1 - Log in to Google Analytics.

You can login in to your Google Analytics account here.  If you don't have Google Analytics set up yet you can get in touch with Trackify to help.

Step 2 - Switch On Enhanced Ecommerce Tracking within Google Analytics

1. Go to the admin settings in your Google Analytics Account by clicking on the cog icon in the bottom left hand corner:

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2. Within the settings screen - click 'Ecommerce Settings' under your Main View.  Find out about different view types here:

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3. Within the Ecommerce Settings ensure Ecommerce is set to 'ON'

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4. Also ensure Enhanced Ecommerce is set to 'ON' and click 'SUBMIT'

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5. While logged into Google Analytics, make a note or copy your tracking id that is found under admin > property > property settings:

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Step 3 - Add Google Analytics to Shopify & Enable Enhanced Ecommerce

  1. Copy the analytics tracking id from your Google Analytics account as above (admin > property > property settings)
  2. Open your Shopify Admin in a new browser window
  3. Go to Online Store > Preferences
  4. Under preferences, paste the analytics tracking id in the Google Analytics field
  5. Tick 'Use Enhanced Ecommerce'
  6. Click on the save button.

Step 4 - Analysing your Data using Data Studio

Once you have completed Steps 1 -3 your data will start collecting with Google Analytics.  Once you've collected a few weeks of data you'll be able to start answering the following questions:

  1. What is my eCommerce Conversion Rate?
  2. How many views/impressions are my products getting?
  3. What products are being 'added to cart'?
  4. What is my 'Cart-to-Detail' Rate? (The number of products added to a shopping cart per number of product-detail views)
  5. What sources are driving my sales and revenue?
  6. Which cities are driving my sales and revenue?
  7. What device type is driving my sales and revenue?
  8. Are my sales from new or returning visitors?

You can find this data within the eCommerce section of Google Analytics (found under 'Conversions)'.  Or you can use this prebuilt Trackify Google Studio dashboard here.

When using this dashboard ensure you change the data to the appropriate Google Analytics View:

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Google Analytics Cross Device Remarketing Explained

If you've logged into Google Analytics recently, chances are you've noticed this alert pop up in your account :

As of May 15th 2017 you will be able to take advantage of Google Analytic's new cross-device remarketing functionality. 

Google Analytics Remarketing

A remarketing audience is a list of cookies or mobile-advertising IDs that represents a group of users you want to re-engage because of their likelihood to convert. You create remarketing audiences based on user behavior on your site or app, and then use those audiences as the basis for remarketing campaigns in your ad accounts like AdWords and DoubleClick Bid Manager.

Currently Google Remarketing does not allow you to target across device and has historically relied on cookies and mobile IDs to identify users for remarketing lists. This is obviously not ideal as it's pretty normal behaviour for users to browse the web across multiple devices.  In fact, according to a study, '6 in 10 internet users start shopping on one device but continue or finish on a different one'.  

Currently, if a marketer built a remarketing audience in Google Analytics then they would only be able to reach them via browser cookies on a singular device.  Obviously this is not ideal and Google has noted that a solution is one of the top requested features.  For years marketers have been trying to find a work around for the problem.

Problem Solved

As of May 15th 2017 this problem will be solved.  Marketers will be able to reach users across devices similar to Facebook and Twitter.  As of May, if someone visits your website on one device, you can now reach them with more relevant ads when they search or browse on another device. By using signed-in user data, ads can be shown to visitors across any device which is linked to their Google account. 

"Google will use data from its signed-in users together with your Google Analytics data to build audience lists for cross-device remarketing. In order to support this feature, two things will happen:

First, for users on your site, Google Analytics will collect Google-authenticated identifiers associated with users’ Google Accounts (and therefore, personal information).

Second, Google Analytics will temporarily join these identifiers to your Google Analytics data in order to support your audiences."


What changes will I need to make?

Marketers should reconsider their remarketing strategy now that ads are going to be seen across multiple devices. 

To take advantage of these changes, ensure you have enabled remarketing in your Google Analytics account and made the relevant changes to your privacy policy:

Google Analytics Real Time Reporting Attributing Source/Medium to direct/(none)

Real-Time reporting in Google Analytics allows you to monitor activity on your website or app as it happens. The reports are in real-time and great for testing your analytics setup if (like me) you're not great with debugging tools such as Charles.

Recently I've been having difficulty testing attribution in the reports and have spent hours trying to solve why conversions and events have be showing up incorrectly as direct/(none) in the real time data.

If you're reading this then you've done the smart thing and Googled it!

After wasting hours of my life going around in circles trying to solve the issue,  I realised that Google Analytics was in fact the problem...

Quote Google:

Due to a change in the way Universal Analytics sends and stores campaign information for Real-Time reporting, it is possible that, during a single session, a user stops being recognized as coming from a specific campaign and is instead counted as a direct referral. As a result, you’ll see traffic and conversions incorrectly attributed to a Source of (direct). You’ll only see this in Real-Time reports; in standard reports, traffic and conversions will be attributed correctly.

An upcoming version of Real-Time reporting will not have this issue. In the mean time, however, you should be aware and interpret referral counts in Real-Time reporting appropriately. To mitigate this issue, you can either force the sending of campaign information on every hit within a session, or use standard reports (instead of Real-Time) when analyzing or reporting referral counts.”

Hopefully you've read this before pulling your hair out trying to solve a problem that doesn't exist!

Google Analytics Set Up & Configuration - 7 Basic Steps to Data Success

99% of clients that come to Trackify for an audit do not have trust in their Google Analytics data.  They're not convinced their data is accurate and tend to use the tool less than they could.  After carrying out hundreds of audits, Trackify have found that the main reason for inaccurate data is because Google Analytics hasn't been configured and set up correctly from the start.

In this blog post I am going to run through my top 6 basic recommendations for configuring and setting up a new Google Analytics Account.

1. Google Analytics Page Tracking Implementation

Before we actually get into the Google Analytics account, it's vital that Google Analytics is implemented correctly on all pages of your website.  If it's not implemented correctly, it's likely your metrics will be incorrect.  You can check this implementation using a free tool such as gachecker.  This tool will scan your site and identify which of your pages contain Google Analytics and more importantly - those that do not.  If you have pages that are missing Google Analytics, it's important you get this fixed ASAP to ensure your data and reporting is correct.

2. Rename your 'Default View'

On creation of an Account, Google Analytics will set up a 'view' of your data by default called 'All Web Site Data'.  You can find this under the admin section within Google Analytics:

I would recommend naming this view': '2. Unfiltered View' by clicking on 'View Settings' as below:

This will be your unfiltered 'raw' view which should not have any filters added to it.  This view will act as a backup in case anything you do in your main views messes up the data.

3. Create a 'Main View'

Next I would recommend creating a new view and calling it '1. Main View' by clicking 'Create New View':

This will be your main view where you will set up filters, goals, reports and dashboards.

When setting this new view up, ensure you do the following under 'View Settings':

  1. Name it '1. Main View'
  2. Check your reporting Time Zone is correct
  3. Check your Currency is correct
  4. Check your Website URL is correct
  5. Check you've ticked 'Exclude all hits from known bots and spiders'

4. Internal IP Filter Exclusion

This is such an important step that lots of companies tend to overlook.  I can't stress enough how important it is to remove internal IP addresses to ensure your data is not skewed.  This includes your office, your agencies, your development team and anyone else who may be accessing your website for internal reasons.

Find out how to create an IP Exclusion Filter here.

5. Goal Set Up

To get the most out of your Google Analytics Account, it is important to have goals set up in your Main View.

A Goal is a measure of success for your website and they can vary for different business types:

  • An eCommerce website could define success to be users making a purchase on their site
  • A Saas website could define success as users signing up for a free trial of their software on their site
  • A blog website could define success as users spending a certain amount of time on their site

All of these goals are measurable within Google Analytics but it is important to set them up under the 'Goals' section of your Main View as soon as possible:

6. Data Studio Dashboard

The Google Analytics interface can be very confusing to newbies without any training.  We recommend using a data studio dashboard to bring in all your key metrics into one place. Here are some templates you can use to get you started:

Trackify Ecommerce Dashboard

Trackify Audience Overview Dashboard

When using either dashboard ensure you change the data to the appropriate Google Analytics View:



For more information on goals you can read Google's support page here or get in touch with Trackify for a free consultation.

I've had a play around with Google Data Studio beta...and it's good!

When I heard that Google was released a visualisation tool as part of its Analytics 360 suite, I wasn't surprised given how important reporting via a dashboard is to enterprise-level organisations.  With the beta being released only recently, I was excited to get my hands dirty and have a play with it.

Given it was initially (and as of July 12, still is) only to users in the US, I had to use a VPN (*cough*) to access the beta, allowing me to create 5 custom reports.

After about an hour, I've been very impressed with the tool and whilst there's some bugs, it's to be expected (given it's in beta).  Here are some highlights:

1.  A lot of data connectors possible (esp. via Google Sheets)


Whilst the default data connectors are only Google properties, this increases exponentially with Google Sheets given the vast sources of information you can import via Supermetrics plug-in.  Having all sources (e.g. cost data) in a single dashboard will ensure that important calculated metrics such as ROI will be easily calculated.

Once the product is released (also a part of the Google 360 suite, I'll also be interested to see what Attribution 360 data can be added.  Especially if it will be used to put data from other sources in context!  I'm a big believer in always putting figures and facts in context to assess whether its "performing or not".

2.  Connecting sources a breeze!

With other dashboards, I've (almost always) had issues with connected external data sets.

The process of actually connecting data sources couldn't have been easier (disclaimer: I've only connected Google Analytics data).  This is in relation to other third-party dashboard solutions where I've found it much more cumbersome to connect data sources.  It shouldn't be surprising given the connectors are all under the Google "eco-system".

The business implication here is that it makes creating dashboards much easier for anybody.  This is only good news for those that may not have the "technical" skills that may have been needed with other solutions.

3.  Ability to customise "look & feel" of dashboards are endless

My personal philosophy with dashboarding and reports is that it (along with being meaningful, of course!) must aesthetically look appealing.  It is my experience that reports that look great have more chance to have attention spent on it by your target audience (unless your target audience are finance people / accountant - in which case, just give them tables full of figures!)

Google Data Studio not only made customising the look & feel very easy - but the options that it gives is almost endless.  This is fantastic when analysts think about dashboard layout and strategy around meaningful information to report on and how (pie chart, table, line graph etc.) this information will be represented.

Dashboards that are meaningful and look great are gold!

Dashboards that are meaningful and look great are gold!

4.  In short, Google Data Studio is very promising!

As someone that loves creating reports and dashboards (nerd alert!), I've been very impressed with Google Data Studio.  

I'm going to hold off on calling it such things as a "game changer", but only because official pricing for the product has not been released yet!  The tool itself is fantastic, but given that it's part of the 360 suite, it will be price geared towards enterprise (i.e. cha ching!!! i.e. not cheap).  However, as a beta, it is certainly warranting itself as a tool that will justify a premium.

What do you think?  Have you had experience with Google Data Studio?  I'd love to hear of your experience and your thoughts!