E-Commerce Case Study

E-commerce Rebuild

How we scaled a legacy retail platform with Next.js, Node.js, and AWS to boost transaction volumes and achieve sub-second load times.

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The Challenge

Legacy Bottlenecks & Cart Abandonment

Our client, a fast-growing retail brand, faced critical page load delays (average 4.8 seconds) and server crashes during holiday flash sales. The monolithic legacy architecture suffered from heavy query loads, causing high checkout abandonment rates and direct revenue losses.

They needed a decoupled headless architecture capable of handling traffic spikes, reducing load times to under 1.5 seconds, and providing a highly responsive web interface on all devices.

Project Metadata

Client: Retail SME (Trendify Group)
Services: Web Engineering, API Architecture, Headless E-commerce
Tech Stack: Next.js, Node.js, Express, MySQL, AWS EC2/S3
Duration: 8 Weeks (Agile Sprints)
The Solution

Headless Next.js & decopuled APIs

Headless Next.js

Rebuilt the front-end with Next.js, implementing Server-Side Rendering (SSR) and Incremental Static Regeneration (ISR) to pre-render dynamic store pages.

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Decoupled REST API

Developed a fast Node.js/Express API layer with database connection pooling and Redis caching to prevent database bottlenecks.

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AWS Autoscaling

Deployed the APIs in containerized environments (Docker) behind an AWS Elastic Load Balancer with autoscaling to accommodate massive traffic spikes.

Measurable Impact

Outcome & ROI

+40%

Conversion Rate Increase

Due to rapid checkout load times and seamless cart UI mechanics.

0.8s

Avg Page Load Speed

Upgraded from 4.8s to sub-second load, satisfying Google core web vitals.

100%

Uptime During Spikes

Zero service interruptions during peak high-volume sales events.

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