Enumstudio — Martin Brummerstedt

Somewhere in your business, prices are set by hand, three reports disagree, and nobody is certain which SKUs lose money.

I work with ecommerce and marketplace businesses. The data goes in order first. Then the manual work comes out of the process. Then I build the specialised systems that either cut the cost or lift the revenue.

What you end up with is not a dashboard. It is a business your team and your AI read the same way. I work alone and I build it myself, so you get the person doing the work.

Email me →What I do

Three moves, in that order.

Services in full →
01

Make the AI understand your business

One definition per number, one place it is computed, and a layer that carries the words your team uses. Skip it and an assistant pointed at your data will answer confidently and be wrong.

02

Work out what is worth doing

Once the numbers agree, the list of things worth building gets short. What is reachable this quarter, and what to drop.

03

Build it, and the ability to keep building

Pricing that sets itself, forecasts finance can plan on, reports the team runs without asking anyone. And your own developers made faster, so the next one does not need me.

Selected work

Miinto

Head of Business Intelligence

An online fashion marketplace selling in twelve European countries, where I lead business intelligence. The tools below are ones I built and run in house: pricing, forecasting, reporting, and the definitions layer every one of them reads from.

Eight tools in daily use, each built end to end and still running. Five of them are below.

8
tools live
4
teams served
12
markets
01
Pricing and ad bidding, both aimed at gross profit
Prices used to be worked out by hand in spreadsheets. Now they are set automatically for every partner and market to optimise gross profit, and Google Ads bids on the expected gross profit of an order rather than its revenue. Two levers, one objective.
02
Forecasts finance and the board plan on
A model forecasts orders in every market and turns that into budgets and marketing targets aimed at gross profit rather than revenue, with the uncertainty shown instead of hidden.
03
An assistant that watches the ad spend
It checks what each market earns per marketing euro against the target for the month and suggests where the spend should move. It recommends, a person decides.
04
The layer that lets AI answer business questions
Every number has one definition, one owner, and one place to look it up, with the words people actually use mapped onto it. Ask in plain language and the right number comes back, whether the one asking is a person or an assistant.
05
Partner feeds checked before they cause damage
Product feeds are checked against one standard before anything reaches the catalogue, so a partner can be told exactly what to fix.
Background

Data first, then AI.

Six years inside online fashion and marketplaces. Data scientist at Stylepit, head of BI and data science at The Vintage Bar, head of business intelligence at Miinto since 2023. All of it on the same problem, which is why I start where these projects go wrong: the data underneath.

Enumstudio is my own practice. The full history is on LinkedIn.

I also build and run my own products under Enumlabs. The AI tools I set up for clients are ones I use on myself first.

dbt · BigQuery · Power BI · Python · PyMC · Postgres · MCP · TypeScript

Tell me what is slow, done by hand, or nobody trusts.

Either a project with a clear goal and an end, or a monthly arrangement where I am the head of data you have not hired yet. Bring the process that is costing you and you get a straight answer on whether software fixes it, including when it does not.

martin@enumstudio.com