Multi-market

One model.Every market.No exceptions.

Marketing math doesn't change at borders. Plug in data from one country or fifty. and get answers your CFO can defend.

Plan a demo with your data

30 minutes. Live in your dashboard. No deck.

The problem

Five markets, five dashboards, one impossible question.

Where does the next €10K go?

Local teams optimize inside their own silo. Headquarters sees aggregated numbers. Nobody can show. with math, not opinion. where one euro produces the most return across markets.

So the answer becomes whoever shouts loudest in the meeting.

How we solve it

One engine. Three things that change.

01

One model, every market

Bayesian decomposition. Per market, per channel, per week. Local signals. holidays, weather, search demand, seasonality. go in as regressors. Output is a single number for every channel, in every market, with confidence intervals.

Not five dashboards stitched together. One model.

02

Reallocations that cross borders

> Reallocate €18,000 from BE-Wallonia Display to NL-Rotterdam Search. Detected diminishing returns at current spend. Calculated optimum within total budget.

That's a real recommendation from a real run. No country team had to lose anything for another to gain. the model already knew the math.

03

Routes to whoever owns it. however you're organized.

Some brands run channels through one central specialist. Others run through local agencies in every country. Most are somewhere in between. central team, local partners, freelancers, all mixed.

The engine doesn't care. Each recommendation routes to whoever owns that channel in your setup. central team, local agency, freelancer, or the CMO directly. One inbox at the top, mapped to how your org actually runs.

Decentralized execution. Centralized decision-making.

Built for the question

Built for the question, not the country

You're comparing us to Nielsen, Marketing Evolution, Analytic Edge. Those tools work. But:

Enterprise MMM vendorsStevin
Implementation3–6 months consulting engagement2–4 weeks, your team in the dashboard
OutputQuarterly slide deckWeekly model run, live recommendations
Lock-in12–24 month contractsNo annual lock-in
MathBlack box, vendor explainsTransparent. your team can defend it to a CFO
CostSix figures upBuilt for mid-market and up

We're not cheaper because we're worse. We're cheaper because we engineered the consultants out, not in.

What you get

What you actually get

  • Full Bayesian MMM, refreshed weekly
  • Saturation curves per channel, per market
  • Cross-market budget optimizer (within total spend, no fairy money)
  • Closed-loop: model → recommendation → owner → status, in one system
  • Multi-currency, multi-language, multi-timezone
  • Pick your data region. EU, US, or APAC
  • Direct line to the team that built it. No tier-1 support.
  • Works with what you already run. paid platforms, web analytics, CRM, CDP, data warehouse, owned channels.

Connects to your stack

Built for the tools enterprise marketing already uses.

From paid platforms to data warehouses. Native integrations across the marketing stack, plus open API for the rest.

Paid platforms

MetaGoogleLinkedInTikTokThe Trade DeskDV360Amazon AdsSnapchat

Analytics

GA4Adobe AnalyticsMixpanelAmplitudeContentSquareHeapHotjarMicrosoft Clarity

CRM & MA

SalesforceHubSpotMarketoBrazeIterableKlaviyoMailchimpAdobe RT-CDP

Commerce

ShopifyMagentoBigCommercecommercetoolsSalesforce CommerceSAPBloomreach

Data

SnowflakeBigQueryDatabricksFivetranSegmentmParticleTealium

BI

TableauPower BIQlikMetabaseLooker Studio

Pilot

How a pilot works

01

Week 1–2

We model one market. Your data, your channels. Output: contribution analysis, saturation curves, first recommendations.

02

Week 3–4

Second market plugged in. Cross-market reallocation becomes possible.

03

Month 2

Third market and up. Specialist routing live.

04

Month 3

Decide. Continue or part ways. Quarterly checkpoints from here. no automatic renewal.

No annual commitment. No data hostage. Quarterly checkpoints, never on autopilot.

How we earn trust

See the math, not the marketing.

We're early in our journey. There's no logo strip yet. There's something better: a working dashboard, refreshed every week, with the math in the open.

01

Weekly model runs

Bayesian decomposition rebuilt every week. You watch the numbers settle as more weeks of data come in. No quarterly slide deck from a black box.

02

Confidence intervals on every line

Each contribution and recommendation comes with a credible interval. If the model is uncertain, you see it. No false precision dressed up as authority.

03

You can run it before you buy

We model one of your markets as a pilot. If the output doesn't reconcile to what you already know is true, we resolve that before the pilot ends. no contract, no invoice.

A different kind of return

When platforms make mistakes, the math notices first.

Billing errors. Serving outages. Reporting lags. At enterprise scale, those are six-figure mistakes. and most brands never claim them, because no one is watching the numbers at the level where the numbers get made.

Stevin reconciles spend, delivery, and reported outcomes across every platform you run. When the numbers don't add up, we build the case file. timestamps, evidence, platform admissions. and put a refund request in your hand the same week it's spotted.

For a brand running €5M+ per year across paid channels, a single major incident has historically meant six-figure unrecovered spend. We've seen brands recover all of it. We've seen brands never look. The difference is whether anything is watching the math, every minute, in every market.

This isn't an upsell. It's how the math earns its keep.

Why this exists

Why this exists

In 1585 a Flemish mathematician named Simon Stevin wrote De Thiende. the small book that gave Europe the decimal system. His point was simple: numbers should work the same way everywhere, for everyone. No special privileges for who you are, where you live, or which guild you belong to.

That's how we think about marketing analytics.

A campaign in Breda runs on the same math as a campaign in Atlanta. A week is a week. A conversion is a conversion. The model doesn't care about the flag on the data.

We named the company after him for a reason.

Show us your markets. We'll show you the math.

30 minutes. Your data. Your channels. Live in the dashboard.

No slide deck. No procurement form. No mystery.

Plan a demo

If we can't show you something useful in the first session, you don't owe us a follow-up.

FAQ

FAQ

We have data in eight platforms across five countries. How long to onboard?

First market live in two weeks. Each additional market is two weeks. We've done five-market onboardings inside a quarter.

Our regional teams will resist losing autonomy.

They don't lose autonomy. They lose the obligation to argue for budget without numbers. Reallocations are math, not management decisions.

Where does our data sit?

In the cloud region you choose. EU, US, AU. We deploy in your AWS region or yours. GDPR-native architecture; SOC 2 path for US enterprise on request.

What if we already have an MMM?

We can run alongside it for a quarter. If our numbers don't reconcile to within rounding, that's our problem, not yours.

How is this different from a marketing dashboard?

A dashboard shows what happened. An MMM tells you what to do next, with confidence intervals. We do both. but the second one is the point.

Are you a tool or a service?

Both, neither pretending to be the other. The platform does the math. People at Stevin pick up the recommendations and own the outcome with you.