About us · where the product comes from
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.
Three platforms, three answers, one budget to defend. Your GA4 export already holds the answer, and the first finding is free and never leaves your browser. Get your first finding free
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
Stores whose spend is too small for a clear signal. When that is you, we say so.
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
The read, acted on
Me Gorgeous acts on its causal read: revenue up 30% in 2025, in the middle of a webstore migration, then up 100% in Q1 2026.
2026
Launch
Open for business. Your dashboards can keep lying; we'll keep doing the math.
Most tools have 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 a data-health score on every channel. Academic-grade rigor, without needing a data team to run it.
Open-source mix-modelling libraries 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 one file, your GA4 export, 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 really drive revenue, and which just take the credit. You stop guessing, and start spending on what works.
Measured outcomes, not projections.
Three of our beta brands saw revenue lifts of +30% to +60%, and one of them reached +100% in Q1 2026 after acting on what the model surfaced. These are signed-off figures from real beta users, not projections.
Four 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.
If your attribution doesn't match your P&L, we should talk. Email the team or see the results.
Your platforms guess.
We run the math.
Upload a GA4 export and see what each channel caused, next to last-click, in 1–2 minutes. The read is yours to keep.
The free finding runs in your browser. Your file never leaves it. The full read is €99, refundable within 30 days, no questions asked. Prices exclude VAT.