Case Study - Re-architecting a made-to-order commerce pipeline for scale

A high-SKU, made-to-order commerce operation was bottlenecked by a manual, sequential order pipeline. We rebuilt it on Next.js and an event-driven serverless architecture on Google Cloud.

Sector
Manufacturing & E-Commerce
Year
Service
Web, Cloud & Data Engineering
Next.js storefrontSSR + configuratorCloud FunctionsOrder orchestrationCloud StorageSpecs & assetsEvent pipelineAsync fulfilmentNoSQL storeOrder records
Reduction in order-processing time
60%
Increase in customer-satisfaction score
35%

Overview

The client operated a made-to-order commerce business with a very large, configurable product catalogue. Every order carried bespoke specifications, and the existing pipeline handled them through a chain of manual steps. As volume grew, that chain became the ceiling on the whole business: slow, error-prone, and impossible to observe.

The challenge

Orders could not be processed faster than staff could shepherd them through each stage by hand. There was no single source of truth for an order's state, no automated validation of specifications, and no way to absorb demand spikes without adding people. The storefront and the fulfilment process were tightly coupled, so neither could evolve without risking the other.

What we built

  • Next.js storefront (SSR)
  • Dynamic product configurator
  • Google Cloud Functions
  • Cloud Storage
  • Event-driven fulfilment

We rebuilt the storefront on Next.js with a dynamic configurator that validates every specification at the point of entry, before an order is ever accepted. Behind it, we decomposed the fulfilment process into an event-driven pipeline on Google Cloud: Cloud Functions orchestrate each stage, Cloud Storage holds specifications and generated assets, and a NoSQL store keeps an authoritative record of every order and its state.

Next.js storefrontSSR + configuratorCloud FunctionsOrder orchestrationCloud StorageSpecs & assetsEvent pipelineAsync fulfilmentNoSQL storeOrder records

Decoupling the storefront from fulfilment through an event pipeline meant the two could scale and change independently. Processing that previously required manual handoffs became automated, observable, and horizontally scalable — handling demand spikes without additional headcount.

The outcome

Order-processing time fell by 60%, and the customer-satisfaction score rose by 35% as turnaround times and order accuracy improved. Just as importantly, the business gained a pipeline it could actually see into and reason about.

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Our offices

  • Sydney
    U5, 37–41 Victoria St
    Epping NSW 2121, Australia
  • Remote
    Serving clients
    Australia-wide