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 Google Studio dashboard: https://datastudio.google.com/open/1wB0rAXP-tt032XUooevRyqbbDlDvgVnf

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

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Google Data Studio Unique Events System Error

If you're using Google Data Studio for your Google Analytics reporting, it's likely you've logged in today and seen a system error for any widgets containing the 'Unique Event' metric:

Google Analytics have renamed the 'Unique Events' metric to 'Unique Dimension Combinations'.  To add to confusion, they've deprecated the api field and also created a new metric called 'Unique Events' which is calculated differently to the previous Unique Events metric.  For more details check out this post https://www.clickinsight.ca/about/blog/unique-dimension-combinations-udc

How To Fix This Issue

To resolve this issue and get your reports working again you'll need to refresh your report data source and update the metric in your widget.

Step 1 - Refresh Your Data Source

Firstly, in edit mode, click on the widget showing the system error and click on the pencil icon next to your data source:

 

Then click 'Refresh Fields':

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Step 2 - Update Your Metric

Once the fields have been refreshed you will notice that the widget error and metric have updated as below:

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At this point you will need to click on 'Invalid Metric' and select 'Unique Dimension Combinations' or 'Unique Events' depending on which metric you want to use:

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Once you have selected your new metric your report widget should be working again:

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You will need to carry out the above steps for all widgets showing this error.

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.”
— http://www.trackify.co.nz/blog/2017/3/9/google-analytics-real-time-reporting-attributing-sourcemedium-to-directnone

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

Google Analytics Set Up & Configuration - 6 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. Make the Main View your Default View

I would recommend making the 'Main View' we just created your default view.  This means that every time you login, this is the view you'll be taken to.  You can make this change under 'Property Settings':

5. 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.

6. 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:

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)

THE CURRENTLY SUPPORTED "OUT OF THE BOX" CONNECTORS ARE (NOT SURPRISINGLY) ALL GOOD PRODUCTS.

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!  

Bot traffic in Google Analytics...from Amazon servers located in Ashburn! Wait...what?!

We were recently contacted by a NZ based client with the following question...

We’ve noticed a spike in traffic from Ashburn. Can you please let us know where that is?
— client X

Looking into Google Analytics data, it was noticeable that this traffic was out of Ashburn, USA.  Applying this as a segment, the associated metrics screamed out that this was indeed bot traffic (Time on page = 0.00; Bounce rate = 100.0%; all sessions generated using Chrome version 27.0.1453.116)

But what was unexpected was the Service Provider.  It was Hubspot - with the Network Domain being amazonaws.com.  The bot traffic was actually coming from Amazon Web Services.

In conducting further research on this, this issue looks to have been happening for quite a few years (such as this post from 2013) but it seems that this is becoming more frequent.

Should we be worried about bot traffic from Amazon?

In short, yes!  Treat them as you would any other potential malicious bot.  The reason being is that the bots may not be coming from the company itself - but could be disguised as such.  

We recommend to create filters to exclude this traffic from your Google Analytics profile.  Use segmentation to isolate traffic to the sure-tell signs of bots (Time of Page = 0.01 seconds (or a number extremely low); Bounce rate=100%Source/Medium = "Direct" - amongst others.  We suggest also checking Browser and Browser version too).

(Note: in the above filter, we did ensure that all traffic to "City=Ashburn" was bot traffic by cross referencing against other metrics such as bounce rate.  Also, given that client is local, any traffic from the US would be unqualified traffic anyway)

Doing this will ensure your data (or your client's data) will be clean, accurate and reliable!  Happy filtering.