Three disciplines.
One intersection.
Marketing attribution is broken. The platforms report what touched a sale, not what caused it. Causality Engine exists because four founders sat at the intersection of marketing, data science, and business administration, and built the causal attribution tool none of them could buy. Hover the diagram to see what each discipline brings, and what it misses on its own.
All three · Causality Engine
“Causal attribution an operator can use and a CFO will believe, from your GA4 export. No pixel, no data team, no last-click guesswork.”
What it brings
Marketing instinct, causal proof, and the CMO and CFO lens in one tool.
What it still misses
Nothing. That is the point, and the moat.
Not a data-science tool dressed up for marketers. Not a dashboard pretending to be causal. The one tool that tells you what actually worked, in plain words both sides trust.
A ten-year headache, solved. Operator problem to Excel method to causal software.
We did not assemble around a pitch deck. We converged around a product that already worked.
- 2014
The itch
Years before the product, one question nobody could answer straight: which marketing actually makes money?
- 2016
Pivot tables. Actual pivot tables.
The first working attribution model, built by hand in spreadsheets. Ugly. Slow. Right.
- 2023
The algorithm gets real
The hand-built model becomes a proper causal attribution algorithm. Causality Engine is founded in December.
- 2024
The model meets reality
The Two Sisters and Twinkels run it: +60% revenue lift each. Last-click said cut Pinterest. The model said keep it. The model was right.
- 2025
Scaling without the usual pain
Me Gorgeous goes from €80K to €180K a month in ad spend. CAC flat. Revenue up 30%.
- 2026
Launch
Open for business. Your dashboards can keep lying; we'll keep doing the math.
Every competitor has one or two. We were built on all three.
Marketing
Ten years running the ad budget. We know which question actually matters to the operator, because we lived the problem.
Agencies and operator dashboards stop here: pretty numbers, no proof of cause.
Data Science
Real causal inference, with honest confidence intervals. Academic-grade rigor, without needing a data team to run it.
Meridian, Robyn, Recast stop here: rigorous, but you need a data-science team to run them.
Business Administration
We build through the business lens. We have lived the CMO and CFO standoff, spend to grow versus prove every euro, and the product resolves it natively.
Most tools pick a side: a growth dashboard for the CMO, or a spreadsheet for the CFO.
Your data in. A clear answer out.
Causality Engine reads your GA4 export, plus your Shopify and ad-platform data, and runs causal attribution. It separates the sales your marketing actually caused from the ones that would have happened anyway. The answer is plain: which channels, campaigns, and creatives really drive revenue, and which just take the credit. You stop guessing, and start spending on what works.
Measured outcomes, not projections.
Brands that switched to causal attribution have seen revenue lifts of +30% to +60%, with one reaching +100% after acting on what the model surfaced. These are signed-off figures from real customers, not projections.
Read the named case studiesFour co-founders. Four specialisms. One problem.
We have managed teams, scaled brands, and shipped and exited products. This is not a theoretical exercise. It is the tool we wished we had when we were in the trenches.
Joris van Huët
Performance marketing and growthThe operator who lived the ten-year headache and built the first manual method. 14+ years in EU programmatic and growth at Publicis (Zenith) and Omnicom (OMD), on accounts including L'Oréal, Renault, Levi's, PepsiCo, and AirJet; early team on United Wardrobe's France entry (acquired by Vinted); fractional CMO specialized in helping DTC brands, with a positive track record.
Atalay Deveci
Causal data scienceFounding scientist since 2023. Turned the manual method into the engine: Markov-chain and counterfactual inference, a proprietary estimator-quality grading metric, a deep-learning ensemble, and the zero-sum to positive-sum simulator that shows the impact of a change before it is made.
Kevin Hoogerwerf
Software engineeringAlready built and exited this category: co-founded CodeBridge (2011) and Buckles (2019), a data-integrations aggregator for ecommerce martech acquired by Spotler in 2023. Twelve years of production clean-systems discipline.
Ralf Harmens
Operations and scaleTechnology leader with experience at Shell, Axpo Solutions AG, Uniper, and MET Group, with a strong background in software delivery, multi-vendor environments, and digital transformation across energy and trading organizations. Known for combining strategic perspective with hands-on execution, a global outlook, and a focus on building high-performing teams and simplifying complex systems.
Built in the Netherlands. Usable anywhere on GA4.
We started with Dutch ecommerce because it is our backyard and the problem is sharp here. But nothing about the product is local. If you run GA4, you can run Causality Engine, wherever you are. The Netherlands is our beachhead, not our boundary. The product is live, priced simply, and built for teams that want clarity over complexity.