Turning E Commerce Personalisation Into an Automated Product Discovery Experience
A behaviour driven recommendation engine wired directly into the shopping experience, introducing personalised product discovery while keeping the store fast, responsive and simple.
- Client
- E commerce platform
- Industry
- E Commerce
- Services
- AI AutomationSmart RecommendationsUX OptimisationWeb Development
- Increase in product engagement from recommendations
- 22%Increase in product engagement from recommendations
- Page load time
- Under 2sPage load time
- Contextual suggestions across the shopping experience
- Real timeContextual suggestions across the shopping experience
- Modular recommendation architecture for later personalisation
- ML readyModular recommendation architecture for later personalisation
Where they were starting from.
The e commerce platform needed a smarter way to help customers discover relevant products without relying entirely on manual merchandising. The goal was to introduce personalised product recommendations while keeping the shopping experience fast, responsive and simple.
Four decisions that shaped the outcome.
- 01
AI Product Recommendations
Built a recommendation engine using customer behaviour, click patterns, category context and product attributes to dynamically suggest relevant products.
- 02
Smart UX Automation
Integrated recommendation logic directly into the shopping experience so product suggestions could adapt to the user's browsing context in real time.
- 03
Scalable Architecture
Designed the recommendation layer to be modular and ML ready, allowing more advanced personalisation to be introduced later.
- 04
Performance Automation
Implemented caching, progressive loading and optimised delivery through Vercel's CDN to maintain a fast experience across devices.
An automated product discovery system that uses customer behaviour and product context to deliver more relevant shopping experiences at scale.
Built with
- React.js
- Next.js
- TailwindCSS
- AI Recommendation Logic
- Vercel
- GitHub
The numbers behind it.
Screenshots taken from the tools themselves, not a summary of them. Select any one to see it full size.
The storefront homepage, built for a responsive shopping experience across devices.
Automated product discovery: the New Arrivals grid, populated from product attributes rather than manual merchandising.
Category context feeding the recommendation engine, alongside customer behaviour and click patterns.
Verified reviews and sign up, delivered through the same fast, cached front end.
Real time contextual suggestions: the assistant answers from the catalogue inside the shopping experience.
Automation & AI Workflows
AI powered workflows and smart integrations that reduce manual work and improve efficiency.
Tell us where it hurts.
If any of this sounded familiar, the call is free and the advice is honest, even when the honest advice is that you do not need us.