No products in the cart.
Server side tracking has become an essential aspect of data collection in the digital age. Unlike client side tracking, which relies on tags and pixels embedded in a website's code, server side tracking involves sending data from these tags to a web server. This method offers several advantages, including improved reliability, control, accuracy, and application and device performance.
A client-side tracking website uses a container on the page to transfer measurement data to multiple third-party tracking platforms. This container operates on the user's browser and has a direct connection to your tracking tools' mother server.
Server side tracking bridges the gap between the two by allowing you to develop your tracking server side container. Google Tag Manager server side tagging is hosted on the servers (Like Google Cloud Platform, Stape.io, or your server) and functions as a middleman between your client-side tracking and marketing vendors.
Data is delivered from the browser to the GTM server-side instance and then forwarded to your tracking tools. This allows you to control data from being sent to your tracking tools and save data resources, resulting in a better user experience.
In this blog, I will walk you through the process of configuring Google Tag Manager server side tagging.
Most teams that set up GTM server-side tracking hit the same wall: the web container and server container aren't talking to each other correctly. Data gets lost, events don't fire, and you're left guessing whether your server-side setup is actually working.There are two ways to send data from your GTM web container to the server containerthe native GA4 transport method and Stape.io's Data Tag. The native method works for basic GA4 setups, but it has limitations: it can't send data arrays, it requires manually mapping every variable, and it gives you no way to transform or store data between pages.This guide shows you how to use the Data Tag + Data Client method to transfer data from your web container to your server container with the exact configuration we use for client setups.