Stop debating which channel drove the sale.
Your team has more attribution data than ever: platform reporting, GA4, third-party tools, and post-purchase surveys. SourceMedium helps you compare those signals using documented logic you can inspect.
The Problem
The attribution confidence paradox
The typical ecommerce brand now tracks attribution through platform reporting (Meta, Google, TikTok), GA4, at least one third-party MTA vendor, and post-purchase surveys. Each shows different numbers. Each has its own methodology. Each claims credit for the same revenue. Reconciling them is nearly impossible.
Meanwhile, the real decisions get stuck. Is branded search actually driving demand, or just capturing it? Are repetitive ads in a single session inflating your Meta ROAS? When the board asks "what's our true CAC?", the team scrambles to build a defensible answer from conflicting sources.
Adding another pixel or attribution interface does not resolve the disagreement. The team needs a documented way to reconcile the tracking and transaction data it already has.
Market Landscape
What most brands try first
Platform reporting (Meta, Google, TikTok)
Useful for optimizing within each platform, but credit can overlap across platforms. Reconcile those claims against completed orders and your agreed revenue definition.
Last-click / GA4
Easy to understand, but it assigns all credit to the final measured interaction and can miss earlier influences in the journey.
Black-box MTA vendors
Some products offer sophisticated models, but buyers should verify whether they can inspect the joins, assumptions, and underlying journey records.
Post-purchase surveys
Useful directional evidence for channels such as podcasts and word of mouth, but survey responses do not identify every ad creative or landing page in the measured journey.
The Solution
Attribution built on data you already have, with logic you can inspect.
SourceMedium combines the first-party funnel data you already collect, including GA4 events, server-side CAPI data from tools such as Elevar or Blotout, and Shopify orders. For each purchase, documented journey-source rules select the most complete available record.
The 120-day lookback captures longer consideration cycles. Attribution can use revenue, net revenue, or profit when the required cost and order data is available.
Identity resolution, session deduplication, and channel definitions are documented in BigQuery. Compare first-touch, last-touch, and deduplicated linear models side by side instead of relying on one view.
Aggregation, not addition
Uses your existing GA4, CAPI (Elevar/Blotout), and Shopify data. No new pixels. No site speed impact.
120-day lookback window
Capture the full journey from initial discovery to final purchase, even for slow-converting products.
Session-based deduplication
Linear attribution that intelligently ignores repetitive clicks in a single session to prevent over-crediting.
Profit-based attribution
Use gross margin or net profit when the required product-cost and order data is available.
Full BigQuery transparency
Direct access to the underlying journey data. Audit every touchpoint and build custom ML models on your data.
Dimensions: Ads & Landing Pages
Not just channels. Break down performance by specific ad creatives and landing page paths.
Implementation
Live in two weeks.
The two-week target applies to a standard launch with supported connectors. Custom sources and customer dependencies can change the timeline and are scoped separately.
Week 1: Connectivity
Data sources connected. Journey-source rules applied across available GA4, CAPI, and Shopify data. Reconciliation run against completed orders and the agreed revenue definition.
Week 2: Insights
Attribution dashboards live. Compare First, Last, and Linear models side-by-side. SQL-backed answers available via AI Analyst in Slack.
“Best-in-class attribution, excellent team, and the customer experience is beyond anything I've experienced with a SaaS product. We've surfaced new, actionable insights about our business using the SourceMedium platform.”
Dir. of Performance Marketing, LMNT
LMNT scaled from low eight figures to high nine figures with SourceMedium and remains on the platform.
Why SourceMedium?
What makes us different
Documented journey-source selection
SourceMedium evaluates the available GA4, CAPI, and Shopify records for each purchase, then selects the most complete journey using documented rules.
Transparency as a feature
Inspect journey records, credit assignments, and joins in BigQuery. When coverage is incomplete, the underlying records show where the gap comes from.
Net Revenue & Profit focus
When product-cost and order data is available, compare channel contribution using net revenue or profit instead of top-line revenue alone.
Learning Center
Related Resources
Ready to stop debating the numbers?
See your attribution data, unified and verifiable.
In a 30-minute walkthrough, we'll review your current data stack, show how SourceMedium would replace or complement it, and demonstrate workflows relevant to your business.
Choose a time for your walkthrough
We couldn't load available times here.
Open the scheduling calendar in a new tab. If you cannot schedule now, we will still follow up.
Open scheduling calendar