TABLE OF CONTENTS
Why Leverage Fueled’s Data Layer?
If a merchant needs to set up multiple client-side attribution scripts to run on their Shopify store, leveraging our data layer can help ensure that the same event data is sent to all destinations. Our data layer defines a data model in one place for consistent tracking and metrics.
Enabling Fueled’s Data Layer
Fueled’s data layer is enabled whenever the Theme App Extension is enabled for our Google Analytics 4 Connector App.
The App Extension settings can be found in your theme, as see below:
Note: You do not have to check the “Track client events” box in the App Extension Settings to utilize our data layer. In fact, if you’d like to leverage our data layer in combination with our client-side event library to manage all of your own client-side events, you would disable this checkbox.
Data Layer Object Definitions
Leveraging Fueled’s Data Layer with Google Tag Manager
- Google Tag Manager is stripped from websites by ad blockers up to 12% of the time in the United States.
- It’s difficult to document and control attribution configuration with GTM.
- It’s difficult to debug errors in attribution scripts that are managed via GTM.
That said, you can still leverage Google Tag Manager with our data layer to help ensure consistent tracking and client-side metrics.
Fueled’s data layer is instantiated in the DOM’s window.dataLayer object, as a variable called fueled.
Inside your Google Tag Manager instance, you can map the data layer to the variables you need for GTM events.
Go “Variables” and click “New” to to create new user-defined variables.
Then click “Data Layer Variable” as seen below.
An example of how you would access properties of Fueled’s data layer are described in the screenshot below.
fueled is the javascript variable to which we populate all of our event and data layer data. To access customer-related data (when a shopper is logged in), you’d select values such as:
fueled.customer.first_namefueled.customer.email
Getting Assistance with Fueled’s Data Layer
For help working with our data layer, please consider joining our Community Slack Channel.