Cases · Matraws · E-commerce · Full-service partnership
13x revenueFrom a single Odense store to seven-figure revenue — over a five-year partnership.
7 figures
revenue in euros this year — up from €300–400K
The whole flow
intake → valuation → payout → posted record, self-running
Own platform
trade-in system built from scratch
5+ years
partnership — and still going
Revenue over time
Five-year partnership
“We thought we were buying a good service, but we've gotten far more than we feel we've paid for.”

01The starting point
When the partnership began, Matraws was a small shop in Odense doing €300–400K in revenue — run by two founders who are among the strongest content creators in the country, with 70,000+ subscribers on YouTube. The potential was obvious. The time wasn't: operations, admin and manual processes ate the hours that should have gone into building the business.
02The growth engine
We ran our framework end to end, with Meta and Google as the acquisition layer and Klaviyo to pick up the low-hanging fruit and build loyalty. The organic content strength they already had was repurposed as paid distribution — and budgets were steered on profit via Profitmetrics rather than the platforms' own numbers. The business stayed profitable the whole way through.
03Under the hood
Alongside it we built their platform from scratch — it runs today at portal.matraws.dk. Customers hand in collections straight from the site: fill in the form, pay the shipping, and the label lands automatically in your inbox — or drop the collection off in one of the stores. Every collection gets its own journey: intake with shelf location, line-by-line valuation with market prices as reference, and a digital offer the customer accepts in one click — with a free choice between cash payout and store credit at a higher rate. Messages go out automatically at every step, by email and SMS, with reminders for anyone who hasn't replied. Several hundred collections have been handled through the system.
04Bookkeeping without hands
Used goods are taxed on the margin, not the sale price — and with thousands of used single cards, that is impossible to bookkeep by hand. The platform generates one VAT document per order, split into margin-scheme and standard VAT, ready for the VAT return with bulk exports for the accountant. The purchase record attaches automatically when an offer is accepted; if anything is edited after posting, a credit note and a new record are created on their own. Cost prices are searchable across every collection ever bought, so the margin can always be documented.
05The automation web
Around the platform grew a web of tools: a notification and dispatch system on an SMS gateway and Resend, a bookkeeping flow running directly over REST to e-conomic and coupled with Storebuddy — purchase records, sales invoices, VAT and cost prices in one place. A custom returns flow built for the EU right-of-withdrawal rules effective 18 June, with no fixed app costs. Order consolidation for customers, a demand tool for purchasing and the hot-buy list, ongoing price checks against the market, and in-house replacements for the apps they used to pay a fixed fee for. The gain isn’t a number of hours on a spreadsheet — it’s capacity: new products go online in bulk because weights, VAT and prices correct themselves, and every step from intake to posted record runs without hands.
06The customer layer
The newest layer faces the customers: a binder system where collectors build their collection set by set and stamp the cards they own — every missing card mapped against live inventory, so the wishlist goes into the cart in one click. The binders feed demand data back to purchasing and trigger automatic alerts when a wanted card is back in stock. On top of that: a free price-check tool with live market prices, self-service for cancellations, returns and order merging — and an SMS queue system for physical events where customers follow their place in line live.
07The partnership
Along the way we've sat at the table for the strategic decisions and taken on the business administration, so the founders could focus on what they do best. Today: a store in Odense, a store in Copenhagen, an office and a warehouse — and seven-figure revenue (in euros) this year. Five years in, we're still going.
A look inside the portal
Built to run on, not to show off.
Collections
Trade-in
Store credit
Automation
Messaging
Notifications
Broadcasts
Documents
Purchase docs
Sales invoices
VAT records
Shop
Returns
Price checks
Demand
System
Statistics
Settings
Samlinger
Fiktive data
Automation — latest events
Gengivelse med fiktive data — ikke et screenshot. Portalens indhold, priser og logik forbliver Matraws' konkurrencefordel.
The collection layer — stylised, fictional data
Binders that sell.
Customers build their collection card by card — and every missing card is mapped against live inventory. A wishlist that adds itself to the cart.
Binder: latest set7 of 18 cards
39 %
8 of your missing cards are in stock right now
Add all to cartEvery binder feeds demand data back to purchasing — and restock alerts go to everyone missing the card.
The credit engine — stylised, fictional data
Store credit as a growth loop.
Sellers choose: cash — or store credit at a higher rate. The credit lives natively in Shopify, is spendable at checkout, and every balance is reconciled against the ledger.
Payout
Cash
60–70 %
Store credit
80–90 %
The higher rate keeps the value inside the shop — the payout becomes the next order.
Balances
reconciled against live Shopify
Issue, deduct and audit per customer — no subscription app in the checkout.
The automation layer — stylised, fictional events
Rules that never sleep.
Webhooks catch every product and order the second it changes; a nightly job is the safety net. Margin-scheme VAT, weights, prices and warehouse routing — corrected before anyone notices.
Rules
Live log
running
Margin-scheme VAT split per order, documented per line — bookkeeping-ready without a bookkeeper touching it.
Physical events — stylised, fictional data
A queue that texts you.
At card shows, collections get a numbered box and the customer gets an SMS — with a live link to their place in line. No one stands waiting at a booth; the system calls them when it's their turn.
Live status
live
Your place in line
2
Box no. 14 · started as no. 7
One hour before closing, anyone not reached gets a message — collect your collection at the booth.
The messages
Collection received — you're no. 7 in the queue. Follow along live: mtrw.dk/q/…
11.02
You're up soon — no. 2 in the queue. Head towards the booth.
12.41
It's your turn! Come to the booth — your valuation is ready.
12.58
Built on the same platform as everything else — the box number follows the collection all the way to valuation and payout.
For the technically mindedThe architecture behind it — expand and dig in
01Trade-in orchestration
Intake of collections runs as API orchestration across Shopify (products and orders), Stripe (payouts) and Shipmondo (labels and shipping). Store credit is implemented on Shopify's native gift-card primitives — a deliberate rejection of the app route: no subscription, no third-party data, no extra point of failure in the checkout.
02The webhook automation
A dedicated server with scoped API access to Shopify runs real-time webhooks on product and order events. The layer is built for bulk events — mass updates that used to require manual review now execute as automated jobs with full traceability.
03The bookkeeping web
Purchase records, sales invoices, VAT records and cost prices flow directly over REST to e-conomic, coupled with Storebuddy on the sales side. The books reconcile themselves continuously instead of piling up at month's end.
04The notification pipeline
Event-driven dispatch with SMS over a gateway API and transactional email through Resend — order status, trade-in confirmations and operational alerts go out automatically, without anyone pressing a button.
05Returns flow & compliance
The returns flow is custom-built for the EU right-of-withdrawal rules effective 18 June — customers can actively withdraw orders through self-service. No fixed app costs, and the rules are implemented precisely rather than approximated.
06In-house tools
A demand tool for purchasing and the hot-buy list, ongoing price checks against market movements, CSV conversion that shapes data to internal systems, order consolidation for customers — plus rebuilds of the apps that used to cost fixed subscriptions. LLM automation ties the tasks together wherever pattern recognition beats rules.
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