salesolution
Anonymized · NDA

Cited in AI Overviews 12 weeks after launch.On a domain with zero history.

A fluid power manufacturer opening a direct commerce channel had no storefront, no organic history, and one hard requirement: the Acumatica PIM stays the source of truth. Five months later a 22k-SKU Next.js + Saleor build was live — AIO-ready from the first deploy, and earning its first AI Overview citations within 12 weeks of launch.

Client
Fluid power manufacturer · OEM channel
Scale
22k SKUs
Engagement
2025 · 5 months
  • 22k

    SKUs on a greenfield Next.js + Saleor build

  • 5 mo

    Kickoff to launch

  • 12 wk

    To first AI Overview citation after launch

  • 1

    Source of truth — the Acumatica PIM, wired straight through

The situation

Where they started.

A manufacturer selling through an OEM channel decided to open a direct commerce channel — net-new, with no existing storefront and no organic history to inherit. The catalog was 22k SKUs, the pricing was multi-currency across multiple tax regions, and the product data lived where it belonged: in the Acumatica PIM, which was not going to be replaced.

The constraint

What made it hard.

Greenfield domains start with nothing engines trust. Every citation heuristic that favors incumbents — history, links, behavioral signals — worked against this launch. And the PIM-as-source-of-truth requirement meant no copy-paste catalog: if product data forked from Acumatica, the project failed on its own terms regardless of traffic.

What we ran

The work, phase by phase. What shipped, and when.

  1. Saleor backend wired to Acumatica

    The PIM stays canonical. Product data flows from Acumatica into Saleor, so the catalog never forks — 22k SKUs with one source of truth.

  2. Next.js storefront on Vercel Edge

    Server-rendered storefront with multi-currency and multi-tax-region handling from day one.

  3. AIO-ready at launch, not retrofitted

    Schema graph, direct-answer category structure, and machine-parseable spec tables shipped with the first deploy.

This is what a Website Development engagement at this scale looks like in practice.

Why it worked

The mechanism, not the magic.

A greenfield domain can’t win citations on authority, so it has to win on legibility. The engines’ first crawl saw the catalog exactly the way they want it: structured specs, answer-shaped category pages, a complete schema graph. That is why the first citations arrived in weeks, not quarters — there was no remediation phase, because nothing shipped broken.

What happened

The results. As measured, dips included.

The build went live at month five, 22k SKUs, PIM wired straight through.

The first AI Overview citations on tracked category queries arrived inside 12 weeks of launch — on a domain that had existed for less than half a year and had no link history to lean on.

The number that mattered

0 wk

Time to first AI Overview citation, post-launch

Greenfield build · zero pre-launch organic history

Measurement notes

How these numbers were measured.

A metric without a source is an assertion. Every number on this page is listed below with how it was counted.

Time to first AIO citation
First observed AI Overview citation of the new domain on tracked category queries, measured from launch day via the Salesolution citation tracker.
Scope & stack
Verbatim from the launch retro: greenfield build, 22k SKUs, 5 months, Next.js + Saleor on Vercel Edge, Acumatica PIM integration, multi-currency / multi-tax-region.

Anonymity. Client name withheld under NDA — most industrial distributors prefer the case study without the logo. The vertical, scale, timeline, and every number are as measured; only identifying details are removed. Reference calls available on request.

More case studies

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    Anonymized · NDA

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    Anonymized · NDA

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    Website DevelopmentAI Search & GEO2024

Your catalog, same standard

Want a number like these for your catalog?

Held to the same standard as the studies above: we measure where you stand today — organic and AI-search visibility across your top categories — and show you the baseline before we propose a thing.