Passing Customers’ Data to Google Analytics from Shopify

20 July 2020


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Hey, world of analytics experts and enthusiasts!
We want to share with you a quick ‘how to’ guide on passing customer identifier and customer type (new vs. repeat) into Google Analytics from Shopify using Google Tag Manager.
Note: the same logic could be used to track purchases by new vs. repeats customers within ad platforms – Facebook Ads, Google Ads, etc.
Business impact of this data being collected:
1. Ability to measure/analyze customer LTV (by customer Id) and retention.
2. Viewability into what drives (channels, sources, campaigns, landing pages, etc.) new customer acquisition vs. repeat customers.
Step 1: Add ‘Customer ID’ and ‘Customer Type’ custom dimensions in Google Analytics:

Step 2: Make sure you have installed GTM snippet in your Shopify account. You can use the following guide.
Step 3: Go to the ‘Settings’ -> ‘Checkout’ in Shopify:

Find ‘Additional scripts’ field under ‘Order processing’ section:

And add the following script to this field:

{% if first_time_accessed %}
   {% if order_number %}
         var customerType = {{customer.orders_count}};
         customerType == 1 ? customerType = "new" : customerType = "repeat";
         window.dataLayer = window.dataLayer || [];
             'event': 'GTMevent',
             'eventCategory' : 'purchase',
             'eventAction' : 'complete',
             'eventLabel' : '{{}} | ' + customerType,
             'customerId': '{{}}',
             'customerType': customerType
   {% endif %}   
{% endif %}

The code should look like:

Save the changes.
Step 4: Add the following dataLayer variables in the GTM:
1) Customer Type variable:

2) Customer Id variable:

3) Event Category variable (as we will be passing the data via event hit into GA):

4) Event Action variable:

5) Event Label variable:

Step 5: Add the custom event trigger to fire on ‘purchase’ event:

Step 6: Add Google Analytics Event tag to push the data into analytics:

That’s it! Publish GTM container and start collecting your data in Google Analytics.

Author: Alex Zakharych, analyst and data scientist at Viden.


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