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Home/Case Studies/Luxury Marketplace
✦ Case study / Luxury fashion  —  Multi-brand marketplace · Global

The best prices online. Unfindable on Google.

A global luxury marketplace carrying 400+ designer brands — Gucci, Prada, Armani, Palm Angels and hundreds more — at prices few resellers could match. Everything was in place except the one thing that mattered: shoppers searching for those exact productscouldn’t find the store. Two agencies had already tried and failed to say why. We found the cause in days — then rebuilt the engine behind it. Shared with permission; the client stays anonymous.

Client: Confidential · under NDASector: Luxury multi-brand marketplaceBased in: United States · sells globallyReferred by: a happy client
Technical SEOGoogle Merchant CenterGoogle ShoppingShopify (Dawn theme)Ecommerce developmentNext.js / NestJSMongoDB · AWS · VercelInventory automationCurrency & pricing engineReportingN8N automationAI content at scaleOngoing operations
§ 01 — Where they started

Everything right, except being found.

On paper, the store had every advantage. A catalogue of 400+ high-value designer brands, live feeds from three connected stores, baskets that ran from a $300 bag up to a $30,000 cart, and referral traffic from luxury aggregators like ModeSens and Lyst. Their real edge was price: deals with manufacturers and resellers let them beat almost everyone on the same item.

And yet organic sales barely moved. Not because the offer was wrong — because of how luxury shoppers actually search. Nobody types the store’s name. They find a piece they love on a brand’s own site, copy its SKU, and search Google for that exact code at the best price. Win that moment and you win the sale. The marketplace should have owned it — but it was nowhere to be seen on Google Search orGoogle Shopping.

01
Discover
Shopper spots a piece on a brand’s own site or a famous fashion destination.
02
Copy the SKU
They grab the product code — the exact identifier for that item.
03
Search the price
They paste the SKU into Google, hunting for the best price anywhere.
04 · the gap
Should’ve been here
Cheapest in the results — but invisible, so the sale went to someone else.
§ 02 — How they found us

A referral from a happy client.

They didn’t find us through an ad or a pitch. They asked one of our long-standing clients — the heritage couture house in our HSY case study — who they’d trust with a problem nobody else could crack. We got the introduction on the strength of work we’d already done, which is the only kind of referral that matters.

By the time they reached us they were understandably tired of it. They’d worked with an agency abroad, then another, each looking hard and coming back empty-handed. The brief to us was blunt: “Everyone says the catalogue is fine. So why can’t anyone find us?”

The buyers weren’t searching for the store. They were searching for a SKU — and the best price.

§ 03 — The diagnosis

A problem in the seam between two teams.

Our SEO team found it within days. Honestly, it was a small fix — the kind that feels obvious once you see it. The reason it had survived two agencies is that it didn’t live cleanly on either side of the usual line. The products weren’t qualifying for free listings on Google Shopping because the site wasn’t meeting the technical criteria Google needs to list them — a development problem dressed as an SEO problem.

The previous developers were looking at the website and never at theMerchant Center. The people who were in the Merchant Center never looked at the build. Each side was certain the fault was the other’s. Because our search and development people sit on the same team, they read both at once and the cause was plain. No heroics — just looking in the place no one had thought to look.

It wasn’t an SEO problem or a dev problem. It was the seam between them — where no one was looking.

Before
A multi-million catalogue invisible on Google Shopping · two agencies unable to name the cause · stock that couldn’t keep pace
After
Products qualifying & listed within days · operations rebuilt end to end · 100k+ items kept fresh, unique and in-stock automatically
Honest note

We won’t dress this up: the listing fix itself was quick and small. The value wasn’t in the size of the change — it was in being the one team that could see both the code and the search side at once. We share the work, not the client’s name or internal numbers; those stay with them.

§ 04 — Taking over operations

From one fix to the whole engine.

Solving the thing two agencies couldn’t earned a bigger remit. They asked us to take over the entire site operation, including the inventory management system behind it — the part that decides whether what shoppers see is actually true. For a marketplace pulling live feeds from multiple stores, keeping stock and pricing honest is the whole game.

We started with the shopfront itself. We redesigned and custom-built it on Shopify, on top of the Dawn theme, and dialled the whole thing up to a true high-end fashion feel — editorial fashion typography, generous space and a considered, luxury look that finally matched the calibre of the brands inside. Behind it, we built the engine that keeps a catalogue this size truthful by the minute.

Rebuilt storefront
A custom Shopify build on the Dawn theme, restyled to high-end fashion — fashion fonts, editorial layout and a premium look and feel worthy of the labels it sells.
Built on
Next.js and NestJS, with MongoDB, deployed across AWS and Vercel — fast to read, robust to run.
Live every 15–60 min
Scheduled cron jobs pull each supplier’s API on a cadence paced to that store’s demand — anywhere from every 15 minutes to hourly — so stock and prices reflect reality, not yesterday.
Pricing engine
Where a supplier prices in one currency and the store sells in another, the system converts the currency (e.g. EUR → USD), applies the margin, and auto-detects discounts and sale prices — publishing the final, correct price automatically.
Two-way sales sync
Every sale is reported back to the parent store within the same short cycle, so they never resell an item we’ve already sold. On time and accurate — efficiency was the whole point.
Onboarding new stores
As new suppliers came on, we moved them off manual handovers onto an intelligent N8N automation that ingests prices, sales, images, descriptions and every other detail — and files each item into the right category on its own.
Reporting
Each run logs how many products were added and removed, and from which store — a clear, continuous picture of what’s moving across every connected feed.
§ 05 — The content problem

100k products. No two the same.

Then a harder challenge surfaced. Because the feeds came from stores that supplied thesame products to other resellers, the marketplace’s content wasn’t unique — and duplicate copy is poison for search. At 100k+ live products, with up to20k added every week and roughly as many retired, rewriting by hand was impossible. A team big enough to keep up would cost a fortune and still be too slow — some piecessell out within minutes of going live elsewhere.

So we built the rewrite into the pipeline. We call it Ollegib — Bigello spelled backwards. As products flow in, Ollegib pulls each one’s details and instantly rewrites the description with AI, in the marketplace’s ownbrand tone, before it ever reaches the storefront. Thousands of listings a week, each one unique, fresh and on the shelf in time to actually sell.

Ollegib · in
Raw supplier copy for every incoming product — the same generic text dozens of resellers share.
Ollegib · rewrite
An embedded step in the automation rewrites each description with AI, tuned to the brand’s voice, at the speed the feed demands.
Ollegib · out
Unique, original product content published on time — so fast-moving items are live, distinct and search-friendly before they sell out.
§ 06 — What changed

Findable, honest, and fresh.

The store went from invisible to eligible and listed, exactly where its SKU-searching buyers were already looking — on a storefront that finally looks the part. The operation behind it now runs itself: prices convert and update correctly, stock stays true to the feeds, sales report back before anyone double-sells, new suppliers slot in automatically, and every product earns its own copy. The numbers below describe thescale of the work, not promises of performance — those depend on the business and the market.

Days
To find & fix what two agencies couldn’t
400+
Designer brands, now findable
100k+
Products kept fresh & unique automatically
20k/wk
New products onboarded & rewritten on time
§ 07 — Built for the markets that buy

Local stores for the buyers who count.

With search finally working, we pointed the store at the markets that actually convert: the United States, Canada, Europe and the Middle East. Instead of one generic storefront for everyone, we built localised stores tuned to each region — andtranslated the experience into Arabic for Middle-Eastern shoppers, so the store met them in their own language rather than expecting them to adapt.

The analytics held a trap, too. One source — China — was sending a flood of traffic but never a single sale, dragging the conversion rate down and muddying every decision built on it. Digging in, we found it wasn’t shoppers at all: it was bot traffic inflating the counts. We blocked it, and the numbers snapped back to reflecting real buyers — a cleaner, more honest picture to optimise against.

United StatesCanadaEuropeMiddle East · Arabic

A conversion rate is only as honest as the traffic underneath it.

§ 08 — Who & what it took

One team that reads both sides.

The whole story turns on a single fact: our search anddevelopment people work side by side, not in separate silos. That’s what let one diagnosis cross a line two agencies couldn’t — and what keeps the system honest now.

SEO expertTechnical SEO2× developersGoogle Merchant CenterShopify · DawnNext.jsNestJSMongoDBAWSVercelN8NOllegib · AI
§ 09 — Why it worked

A rare problem, for a rare fit.

Plenty of agencies do SEO. Plenty build stores. Very few do both under one roof well enough to spot a fault that hides in the gap between them — and then go on to run the whole machine. This marketplace had spent real time and money proving how rare that combination is. When they found it, they handed us everything.

Once organic search was genuinely working, we made a case they hadn’t expected from an agency: lean on organic, and let go of the paid referrers. The traffic from aggregators like ModeSens and Lyst came with commissions that ate into every sale. With buyers now finding the store directly, those middlemen were costing more than they returned — so we advised dropping them, and the client did. They kept more of what they made on every order, instead of paying for introductions they no longer needed.

The fix was small. Being the only team who could find it was the whole point.

§ The work behind it

How we’d do it for you.

One marketplace, one team — search and build working together. Each piece is a service in its own right.

§ Start a project

Got a store that should be found — and isn’t? Let’s look in the right place.

Tell us where the sales should be coming from and aren’t — the first reply comes from a partner, not a form.