Skip to main content
Google Analytics is a powerful system for understanding user behavior. When you connect SourceMedium to Google Analytics, SourceMedium will stream and integrate your ‘GA’ data into your dashboard and other data sources. The integration of this data can be fairly involved, so let’s break it down to just the main things that give the maximum amount of clarity.

​
How Google Analytics data is integrated: the Attribution Source Hierarchy

When integrating data, we focus on Best-Signal Selection. For Shopify orders, SourceMedium uses Shopify as the transactional foundation for “what was sold,” then actively enhances that record with attribution signals from Google Analytics and other platforms. Rather than just “trusting” one over the other, we intelligently merge them. We prioritize the most specific and reliable signal for each order—this is our Attribution Source Hierarchy. In short, we report an aggregated dataset where commerce-platform order records are enriched by GA’s behavioral data. For the full priority order, see Attribution Source Hierarchy. This enrichment can fill in gaps in both data sources — SourceMedium can regularly provide attribution for 10-30% more orders than Google Analytics on its own.

​
Technical matching note

For GA transaction-to-order matching, Shopify-style transaction IDs like #1234 are now tie-eligible alongside longer numeric-suffix IDs. Matching is still bounded by attribution windows and overall data quality, so discrepancies can remain when upstream tracking is missing, delayed, or inconsistent. For full matching and source-priority mechanics, see Attribution Source Hierarchy.

​
Why doesn’t Shopify/SourceMedium match Google Analytics?

Some divergence between Shopify/SourceMedium and Google Analytics is expected. It is generally reasonable to expect 10-20% discrepancies between Shopify order data and GA, driven by subscription checkout handoffs, ad blockers, faulty UTM tracking, and other factors GA cannot see. For the full list of failure points and how to address them, see Common GA Failure Points.

​
Intelligent Data Aggregation

SourceMedium doesn’t just rely on one method. Instead, we aggregate first-party data captured from all sources and intelligently merge it to create the highest quality record. This means:
  • More Data Sources = Better Output: Connecting more platforms gives SourceMedium more signals to resolve identity and attribution.
  • Better Capture = Better Output: Improvements to your upstream tracking (e.g., a robust GA4 setup or server-side tracking) directly improve SourceMedium’s accuracy.
We use Shopify as the transactional backbone (financial truth) and enrich it with the best available attribution signals from your entire stack.

​
What do (direct) / (none) and (none) / (none) mean?

(direct) / (none) means the selected attribution evidence resolved to direct traffic with no medium. It is different from (none) / (none), which is the fallback when no usable source/medium evidence is found. High direct or no-source traffic usually means attribution can be improved, but the two values are not the same thing. See (direct) / (none) for the canonical definition and troubleshooting steps.

​
How to improve your UTM tracking

The biggest lever is consistent UTM tagging on every campaign link you control. For the full setup checklist, naming conventions, and common pitfalls, see Improving Last-Click Attribution and the UTM link-building template. One SourceMedium-specific note: Google Analytics may not be able to distinguish between new and returning customers, since it does not have a complete history of your new versus repeat customers. To address this, SourceMedium ingests historic data for your business and matches each customer against previously ingested customers to determine whether they are new or returning.