The CRO Playbook for Shopify Founders

Part 1: The Ideal Google Analytics Setup

Welcome to the first post in a new series entitled “The CRO Playbook for Shopify Founders”, where we’ll be creating guides for Founders (and Ecommerce Managers) of small, rapidly-growing brands currently using Shopify as their ecommerce engine. The philosophy behind the series is to impart Conversion Rate Optimisation ideas and best practices to enable you to squeeze more value out of your stores and supercharge your growth.

At 54 Bit Studios, we have worked with many small, ambitious brands and this series is borne out of these experiences. Whilst no two businesses are the same, there are certainly common themes when it comes to optimising conversion rates to improve the likelihood that users of your website complete their customer journey with a purchase and not a bounce.

The Ideal Google Analytics Setup

At 54 Bit Studios, we’re huge advocates of data, and you should be too. Gathering meaningful data on how your customers are behaving on your website is invaluable for knowing what is, and isn't working. If you’re looking to get more “bang for your buck” from your website - which I imagine you are - the road to higher conversion rates is paved with data and Google Analytics (GA) is where you’ll find it.

If you follow this guide, I can assure you that, moving forward, your website data will be healthier and more powerful than 90% of other ecommerce SMEs. And better data enables better decisions on where opportunities to improve conversion rates lie.

I’m assuming you’ve already linked your Shopify store with your Google Analytics account but if you haven’t yet got to this point, here’s Shopify's guide to get you started: Setting Up Google Analytics


Raw Data

You’ll most likely have one Account, one Property and one View but it’s important you have, at a minimum, two Views. Other, more in-depth analytics guides might recommend more but simply having two Views will propel your business into the top 10% of data-led SMEs.

Assuming you haven’t already adjusted your “All Site Data” View, this will become your “Raw Data” View. This can be thought of as your backup, should anything happen to your upcoming “Filtered Data” view. First, let’s change the name of your “All Site Data” View so it’s clearer what data it’s holding.

  1. Click on the Admin icon
  2. Navigate to your "All Sites Data" view
  3. Click on View Settings

  1. Change View Name to “Raw Data
  2. Make sure the Website's URL dropdown is https:// and not http://
  3. Hit Save

Screeshot of raw data steps 4 - 6

54 Bit Studios (and our dummy store Treeify) is based in London, United Kingdom so our timezone and currency are set accordingly. Make sure your configuration is correct for your business.

That’s our backup done, now on to our new, squeaky-clean Filtered Data view.

Filtered Data

Let’s make our new View and apply those features that will ensure clean and meaningful data for future analysis.

  1. Navigate to Admin
  2. Click +Create View
  3. Name the view “Filtered Data
  4. Set the correct Reporting Time Zone for your business

Screenshot of creating Filtered Data view steps 1 - 2

  1. Make sure the Website's URL dropdown is https:// and not http://
  2. Enter the following in Exclude URL Query Parameters field: fbclid,refresh_count,preview_key,customer_posted,external_browser_redirect
  3. Enable Bot Filtering
  4. Turn on Site Search Tracking
  5. In the Query parameter field enter: q
  6. Enable Strip query parameters out of URL
  7. Hit Save

Screenshot of creating Filtered Data view steps 5 - 11

The first difference between our new Filtered and Raw views is the URL Query Parameter exclusions. By default, Google Analytics treats URLs with different query parameters as different pages. This is OK if the content of the page is significantly different to justify treating it as a separate page, but if not, it segregates our data and disrupts our ability to analyse page performance. The values provided are those which we've seen cause unnecessary data splitting and acts as a good base for any Shopify store owner.

The second difference is that we've turned on Site Search to start capturing search terms in Google Analytics. You will already have access to this information in Shopify but it’s useful to have it in Google Analytics so you can analyse the value of certain search terms, and what actions users take after searching. Adding “q” to the Query Parameter field tells Google Analytics that Shopify search terms are found in the URL in the format<search term>.

If your site uses filters on listings pages, you can turn on Site search categories in the View Settings and enter the respective query parameter key to, again, treat filtered listing pages as the same page. You will see them added to the URL after selecting a filter, such as Category on your site.

And that's it for the View setup! Next, we need to turn on Enhanced Ecommerce features.

Enhanced Ecommerce

This is, without doubt, the most important part of your setup. Enhanced Ecommerce is a Google Analytics feature that captures and “enhances” data of key behaviours a user takes during their buying journey. It unlocks powerful reports that you will want to have in order to identify what your customers are doing, and where the opportunities are to increase conversion rates.

  1. Go to your Shopify admin site
  2. Navigate to Online Store
  3. Click Preferences
  4. Check Use Enhanced Ecommerce

Screenshot from Shopify turning on Enhanced Ecommerce feature

  1. Go to Google Analytics
  2. Navigate to Admin
  3. Ensure you’re “Filtered View” is selected
  4. Click Ecommerce Settings
  5. Switch on Enable Ecommerce
  6. Switch on Enable Enhanced Ecommerce Reporting
  7. Hit Save

Screenshot from Google Analytics turning on Enhanced Ecommerce features

This will give you access to the most valuable reports for an Ecommerce website owner: the Shopping Behaviour report. This report shows you how users are progressing through the buying journey, and thus where efforts should be funnelled in order to optimise sales-related metrics such as Conversion Rate and Revenue per User. In a future post, we’ll dig into this report in more detail to get the most value out of it. The report will appear once Enhanced Ecommerce data starts arriving in your Google Analytics property so if you have just enabled it, check back in 24 hours. You’ll find the report in Conversions > Ecommerce > Shopping Behaviour.

Filter Out Internal Traffic

A significant amount of traffic to your website will be coming from “internal” users to your company which is obscuring the picture that your data is painting. The ideal scenario is that you remove all non-customer traffic, so site visits from you, your marketing team, your development guys, etc. are removed from reports in your "Filtered Data" view leaving sessions from “real” customers only. 

Google Analytics uses IP addresses to identify traffic that should be treated differently so you need to add all “internal” IP addresses as individual Filters to remove internal traffic from your reports. IP Addresses are unique to internet connections so you should think about all the different WiFi networks you, and members of your team, use on a regular basis. The office and your team members’ home WiFis are the obvious ones to get in there. It’s worth saying that if you work in a large, shared office and you filter out the office IP you may be excluding all traffic from all users on that network.

Click here to find out your IP address and ask colleagues to search in Google: “what is my IP address”. Copy the address to your clipboard.

  1. Navigate to Admin
  2. Ensure you have your Filtered View active
  3. Open Filters
  4. Click +Add Filter

  1. Name your filter something obvious, eg. Exclusion: Office IP or Exclusion: Home IP
  2. Keep the Filter Type as "Predefined"
  3. Change the first dropdown to "Exclude"
  4. Change the second dropdown to "traffic from the IP addresses"
  5. Change the third dropdown to "that are equal to"
  6. Enter your IP address into the IP address field
  7. Hit Save

Screenshot of Google Analytics setting up exclusion filters for IP addresses

You’ll need to repeat this step for each IP address you want to exclude from your reports.

As an additional safeguard, you can also request members of your team install the Google Analytics Opt-Out Chrome Extension. This is recommended for at least your web development team who create a lot of internal sessions whilst they work.

Combine Referral Channels

Chances are you’re advertising on Facebook and Instagram and if you’ve looked into your Google Analytics data much to date, you’ve also probably noticed referral traffic such as

Screenshot showing segregated referral traffic from instagram

This extra information (which is dependent on the device type this user is on) is not useful for your Analytics and is splitting up your data to make life harder when determining traffic value. For now, we want to unify all Instagram referrals, and subsequently, all Facebook referrals too.

  1. Go to Admin
  2. Ensure your "Filtered Data" view is active 
  3. Click Filters under the View Column
  4. Click +Add Filters

  1. Enter “Combine Instagram Referrals” as the name.
  2. Select Filter Type "Custom"
  3. Select "Search and Replace"
  4. Filter field select Campaign Source
  5. Search String enter: .*instagram
  6. Replace String enter: instagram
  7. Hit Save

  1. Create a new Filter for "Combine Facebook Referrals" and repeat the steps above but wherever you’ve typed "instagram" replacing it with “facebook”.

Exclude Self-Referred Traffic

Referral Traffic is all traffic that originates from another website. By default, say a user is on your website, leaves and then comes back via a link Google Analytics will count two sessions. However, there are some occasions when this works against analysis efforts, particularly when it comes to payment gateways and some third-party apps you may have installed.

For example, if a user chooses to checkout with PayPal, they get temporarily taken to only to be returned to the store after taking payment. Google Analytics sees this as two sessions - firstly, it'll see a user who's made to the payment stage of the checkout flow, only to leave the site, and another, separate session where a user arrives from and immediately purchases a product... Not very helpful! I've amassed a list of those sites which commonly cause these issues:

  1. Navigate to Admin
  2. Under the Property Column open Tracking Info
  3. Click Referral Exclusion List
  4. Click +Add Referral Exclusion
  5. Enter
  6. Hit Save

  1. Repeat the above steps for,,,, your own store URL and your Shopify-assigned URL (<your store name>

As you start digging into your Acquisition report, if you notice any other referrals that shouldn’t be there, you can add them to this list.

Enable Demographic Reporting

The final step to this guide is to enable some additional data collection and reporting features in Google Analytics that will help you understand who your customers are and which demographics are performing well on-site. You can feed this information back into your marketing efforts or adjust website content to cater for your high-performing audiences.

  1. Navigate to Admin
  2. Under the Property column click Data Collection
  3. Switch on Advertising Reporting Features
  4. Hit Save

  1. Go to Admin
  2. Under the Property column click Property Settings
  3. Turn on Enable Demographics and Interest Reports
  4. Whilst in your Property Settings, change your default view to your Filtered Data view
  5. Hit Save

Once you hit enable, data starts being collected and soon you’ll have access to reports such as this:

Screenshot of Demographic Report

Pretty interesting, right!

Wrapping Up

Congratulations on making it to the end of the guide! Whilst there was a lot of stuff in there, you can now rest assured that you’re in the top 10% of SMEs when it comes to gathering clean onsite behavioural data. Soon, once you’ve gathered some data, you’ll be primed and ready to analyse how your customers are using your website, and where efforts should be focussed to drive those KPIs in the right direction.

Keep your eyes peeled for the next post in the series where I’ll dig into some of the more useful reports in Google Analytics for Shopify store owners, but until then, happy data gathering!

If you have any thoughts or questions, I’d love to hear from you and if you found this guide valuable, please share it with your networks.

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