Solution: performance marketers
Incrementality for Performance Marketers
You are judged on ROAS you suspect is inflated. Scaling the best channel quietly stops working. You need the incremental truth before you defend the number.
The problem you are living with
Your dashboard reports 5x ROAS on the channel you scaled. You scale further, and conversions plateau or fall. Then you defend the original number to the CFO. Reported ROAS includes retargeting that captured existing intent, branded search that intercepted free demand, and view-through credit you would never claim if you saw the underlying paths. Until you measure incrementality, you are optimizing toward an inflated number.
What causal attribution changes
Causal attribution gives you the incremental component of each channel separately from the captured-demand component. The 5x reported channel might be 1.4x incremental. The 2x channel that looks marginal might be 3x incremental because it creates the demand other channels close. With confidence intervals, you can size scaling decisions correctly and defend them with math.
Find your wasted ad spend in 5–10 minutes.
Watch the model work on a sample store first, no signup. Then upload your last 40–90 days of GA4 sessions and get incremental ROAS with confidence intervals. No pixel, no SDK. €99 per read.
Prefer to talk it through? Book a 20-min call, or read how it works.
How it fits your workflow
Run a causal attribution check before any spend-reallocation meeting. €99, 5–10 minutes, on your existing Shopify and GA4 exports. Bring the incremental ROAS table and the confidence intervals into the meeting instead of platform-reported screenshots.
Frequently asked questions
How does this compare to a Meta conversion lift study?
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Meta designs and grades its own lift study. Causality Engine runs causal attribution on your first-party data, independent of any platform's incentives. You get an incremental read on every channel at once, not one channel at a time.
What about MMM?
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Causal attribution and MMM are different framings of the same job. Modern Causality Engine MMM runs on the same Shopify + GA4 exports, in the same 5–10 minutes. See /marketing-mix-modeling for the MMM-framed version of the same analysis.
How often should I re-run it?
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Before any meaningful spend reallocation, or weekly during scaling pushes. As spend changes, incrementality changes - that is the point of measuring it instead of trusting platform-reported ROAS that lags reality.
Keep reading
Related
Causal attribution
What it is and how it differs from platform ROAS.
Incrementality testing
From geo holdouts to causal modeling on existing data.
Meta Ads incrementality
Meta's true incremental contribution, not reported ROAS.
Google Ads incrementality
Separate captured demand from caused demand on Google.
Real reports from performance teams
See what attribution looks like for performance teams.
Anonymised reports from teams already using Causality Engine. Per-channel incremental ROAS with confidence intervals.
Browse all reports for performance teams →Use cases
- Set a target ROAS by channel
- Set a target CAC by channel
- Reallocate spend between paid channels
Causal attribution check
Find your wasted ad spend
in 5–10 minutes.
Watch the model work on a sample store first, no signup. Then upload your last 40–90 days of GA4 sessions (and Shopify orders if you have them) and get incremental ROAS with confidence intervals. No pixel, no SDK, no integration project. €99 per run. Every quarter on last-click adds to your marketing debt.
Prefer to talk it through first? Book a 20-min call, or read how it works.