Every platform claims the same sale.
Only one of them caused it.
Upload your GA4 export. In 5–10 minutes you see which channels actually drove revenue, with confidence intervals. Unlike the platforms, we have no ad budget to protect.
No signup for the demo. Full refund on your first read if it doesn't move a decision. Or book a 20-min call.
- Shopify
- WooCommerce
- Meta Ads
- Google Ads
- Amazon Ads
- eBay Ads
- TikTok Ads
- Klaviyo
- Awin
- CJ Affiliate
- Claude Commerce
- and more
Four Dutch DTC brands and our own store. Real engagements, numbers they let us publish.
No anonymous logos, no inflated brand counts. Four brands ran a real causal read on real GA4 data and signed off on the figures and quotes on the case-studies page; two of them also tell you when we said the product wasn't the right fit yet. The fifth, Maison Tanger, is ours: we run it on the model's output alone, to live the day-to-day our users live rather than just measure it.
Me Gorgeous
megorgeous.nl
+30% revenue lift, 2025
Causal read flagged 2K EUR/mo of Meta spend with no incremental contribution.
The Two Sisters
the-twosisters.nl
+60% revenue lift, 2024
Last-click said cut Pinterest. Causal read kept it live.
Twinkels
twinkels.nl
+60% revenue lift, 2024
Hidden Meta return-rate gap surfaced by causal lift, not gross ROAS.
Maison Tanger
maisontanger.com
Our own store
Founder-owned. We run it on the causal read alone, to live the day-to-day our users live.
OFFFTRACK
offftrack.com
Honest fit floor
Causal gap inside the confidence interval at current spend. Revisit when scale lifts.
Watch the model work.
A sample store's GA4 data, the real causal model, the per-channel read. No account, about three minutes.
Two ways in. Both start with your GA4 export.
No annual contract, no pixel, no onboarding call. A one-time causal read for the price of a dinner, or the same model running continuously.
One read
Start hereThe fastest way to see whether causal moves a decision.
- Per-channel incremental ROAS with confidence intervals
- Platform-reported vs causal comparison for every channel
- Budget reallocation recommendations
- Exportable report
- 14-day Pro trial included
- Full refund if it doesn't move a decision
Pro
Continuous causal attribution, ingestion, chatbot, API.
- Automated GA4 ingestion (no more manual upload)
- Insights that compound month over month
- Chatbot for ad-hoc questions of your attribution data
- Developer API so marketing agents can pull insights
- Same causal model, run continuously
- Cancel any time
Choose €99 for a one-shot answer to one question. Choose Pro once you want the model watching every month. Full comparison on the pricing page.
This is what €99 buys. The report, not a dashboard tour.
One view per channel: what the platforms claimed, what actually caused revenue, and how sure the model is. Exportable, CFO-ready, yours to keep.
Attribution by Channel
Share of revenue credited, platform-claimed vs CE causal (95% CI)
| Channel | Platform-claimed | CE causal | 95% CI |
|---|---|---|---|
| Direct | 18.4% | 39.6% | ±2.4 points |
| Organic | 9.6% | 19% | ±1.8 points |
| Paid Search | 31.2% | 14.9% | ±1.6 points |
| Paid Shop | 22.7% | 10.2% | ±1.3 points |
| Cross-net | 16.1% | 7.3% | ±1.1 points |
| 12.4% | 4.8% | ±0.8 points | |
| Referral | 5.8% | 2.1% | ±0.5 points |
Platforms together claim 116% of revenue. It only happened once.
Sample numbers for illustration. Open the interactive demo to see the same report on real data from a real brand.
Here's exactly what happens. All four steps, before lunch.
The Q3 budget you already spent is auditable today: the model runs on GA4 history, so there is no ramp-up period and no model-training wait.
- 01~2 min
Export
Download any historical period from GA4. No pixel, no SDK, no access grants, nothing touches your stack.
- 02~1 min
Upload
Drop the CSV in and pay €99 by card. No contract, no sales call, full refund if it doesn't move a decision.
- 035–10 min
The model runs
Proprietary causal inference separates incremental revenue from would-have-happened-anyway, per channel.
- 04same day
Decide
Per-channel causal answers with confidence intervals and reallocation recommendations. Move budget with evidence.
This is built for a very specific brand. Is it yours?
We don't serve everyone. We built a precision instrument for one type of e-commerce operator. If this list doesn't describe you, we just saved you a click.
You use GA4.
Even if you secretly hate what it tells you.
You do €10k+ revenue per month.
Real revenue. Real ad spend. Real decisions to make.
You run more than 4 active marketing channels.
Meta, Google, TikTok, email, affiliate, influencer, at least four are live right now.
Every platform tells you to spend more on that platform.
Meta says scale Meta. Google says scale Google. Each one defending its own budget.
You suspect your dashboards are lying, the revenue never adds up.
Add up the platform-reported revenue, compare it to your actual orders, and the platforms have claimed more than you sold.
Checked all five? You're in the right place.
And one of two people is reading this.
You own the brand and the budget.
You decide alone, and you want the answer before the next spend. Upload a GA4 export, get per-channel incremental ROAS with confidence intervals in 5 to 10 minutes, and act on it. €99, refunded if it does not move a budget decision.
The refund terms are in the pricing FAQ.
You run the channels. Someone else signs off.
You have to defend a number to the owner or to finance. Start with the live demo on a sample store, then take the read in with its intervals, the method in plain language, and the four answers your CFO will ask for.
The four CFO answers are on the pricing page.
Your platforms guess.We run the math.
Last-click is lying to you. Watch the model work on a sample store, then run it on your own GA4 export — €99, once.
No signup for the demo. Full refund if you don't see the value. Or book a 20-min call.
You have questions.
We have math.
What is marketing debt?
Marketing debt is the compounding cost of budget decisions made on wrong attribution. Each quarter you allocate spend on correlated numbers instead of causal evidence, the misallocation carries into the next plan and grows. Like technical debt, but on the marketing P&L. A causal read on your GA4 export quantifies it per channel.
The full breakdown of marketing debtWhat is attribution debt?
Attribution debt is the gap between what your ad platforms claim drove revenue and what actually caused it, carried quarter after quarter into the budget. It is how marketing debt accrues: allocate on claimed conversions long enough and the plan itself becomes the liability.
Both terms, definedI'm using GA4 and I don't trust the attribution numbers. What do I do?
Upload any historical period from your GA4 export. Our proprietary causal-inference model runs on it and within 5 to 10 minutes returns a per-channel view of which campaigns actually drove incremental revenue, not just which ones happened to be there at the click. €99, pay-per-use. No subscription, no setup call. Go Pro at €299/mo to unlock the cool stuff: automated GA4 ingestion (no more manual upload), insights that compound on each other over time, a chatbot for asking questions of your data, and a developer API so your marketing agents can pull insights in real time. Works for any ecommerce vertical, fashion and beauty brands were our launch users, but the model is vertical-agnostic. GA4 is enough today; the native Shopify integration is on the roadmap.
What €99 and Pro includeWait, what even is attribution?
Attribution is how you figure out which of your ads actually led to a sale. Right now, most tools just credit the last ad someone clicked, even if they saw five other ads first. It's like giving all the credit to the waiter and ignoring the chef.
Causal attribution, explainedWhy should I care if my attribution is wrong?
Because you're making spending decisions based on lies. If your dashboard says Meta is your best channel but it's actually TikTok creating the demand, you'll cut the thing that's actually working. Wrong attribution means wasted budget. Every single month.
Why last-click is lying to youMy Shopify dashboard shows me sales. Isn't that enough?
Shopify tells you what sold. It doesn't tell you why it sold. Was it the Instagram ad they saw Tuesday? The Google search on Thursday? The email on Saturday? Shopify just sees the finish line. We show you the whole race.
The Shopify attribution guideI'm not technical. Can I actually use this?
If you can export a CSV from GA4, you can use Causality Engine. No code. No pixels. No 90-day onboarding. Upload the file, wait 5–10 minutes, see which channels actually cause sales. Native Shopify integration is on the roadmap but GA4 alone is enough today.
How it works, step by stepHow is this different from what Meta and Google already tell me?
Meta says it drove the sale. Google says it drove the sale. TikTok says it drove the sale. They all take credit for the same purchase. We're the only ones who don't have an ad budget to protect. So we tell you the truth.
How the attribution tools compare