Client
Mid-Size D2C Brand
ShopLyft - eCommerce Personalization & High Speed Storefront
ShopLyft is a modern eCommerce platform engineered with a high-performance storefront, dynamic product search, and personalized recommendation widgets. Inexture optimized the entire experience from backend logic and catalog filtering to user behavior–driven product discovery resulting in higher engagement and increased conversions.
Project Snapshot
Service Categories
Web Development · Backend Engineering · Recommendation Systems · Search Engineering
Platform
Web Storefront · Mobile Responsive
Duration
3.5 Months
Technologies
React, Node.js, MongoDB, Redis, Elasticsearch, AWS
Status
Live, powering 2M+ monthly visitors
About The Project
ShopLyft aimed to upgrade from a basic online store into a personalized, high-speed eCommerce experience, as their old setup suffered from performance bottlenecks and limited personalization capabilities. In response, Inexture delivered a fully rebuilt, scalable personalization platform designed to support rapid growth and deliver a modern, dynamic user experience.
Their old setup suffered from
- slow product filtering
- irrelevant search results
- low conversion rates
- no personalization
- rigid CMS with scaling issues
Their new setup we delivered
- strong product discoverability
- dynamic recommendations
- lightning-fast search and filtering
- optimized add-to-cart and checkout UX
Client Requirements
- Handle 100k+ SKUs efficiently
- Deliver instant product search & dynamic filtering
- Personalize recommendations for each user
- Improve add-to-cart and checkout conversions
- Sync inventory automatically with warehouses
- Support marketing campaigns, coupons & dynamic banners
- Provide analytics dashboards for product & sales performance
Key Challenges
- Slow filtering across large catalogs
- High campaign traffic causing performance dips
- No recommendation engine available
- Checkout abandonment was high
- Search lacked ranking, synonyms, and relevance logic
- CMS structure couldn’t support rapid content updates
Our Solution Architecture
High-Performance Storefront
- Built using React + SSR to improve SEO, reduce load time, and increase PageSpeed performance.
Elasticsearch-Powered Product Search
- Instant dynamic filtering
- Autocomplete and category boosts
- Relevance-weighted ranking
- Synonym mapping
- Fuzzy search for typos
Personalized Product Recommendations
- “Recommended for You”
- “Similar Products”
- “Trending Now”
- Cart-based suggestions
Inventory, SKUs & Order Automation
- Real-time warehouse sync
- Automated SKU availability
- Order routing automation
- REST-based connections to fulfillment systems
Admin Dashboard for Business Teams
- Campaign analytics
- Sales & SKU trends
- Funnel tracking
- Abandoned cart insights
Cloud-Native AWS Architecture
- Load balancers
- Auto-scaling groups
- CDN via CloudFront
- Multi-zone DB replication for reliability
Personalization Platform High-Level Architecture
The architecture showcases how data ingestion, analytics, personalization logic, and eCommerce systems integrate to power a scalable, enterprise-grade personalization platform.
Recommendation Engine Data Flow Diagram
This diagram illustrates how customer behavior, product data, and real-time interactions are processed to deliver personalized product recommendations and shopping experiences.
Technology Stack
A robust and scalable technology foundation powering seamless performance and future-ready growth
- Redis
- React.js
- Next.js
- Node.js
- Payment gateways
- Java Spring Boot
- Elasticsearch
- CRM tools
- MongoDB
- AWS ECS
- Lambda
Shoplyft Scalable Cloud Architecture
This cloud architecture demonstrates how Shoplyft delivers personalized shopping experiences at scale by combining real-time data processing, intelligent recommendation logic, and a resilient cloud infrastructure. The platform is built to support high traffic volumes, fast response times, and continuous optimization of customer journeys.
Results & Impact
- +37% boost in product-to-cart conversions
- Page load time improved from 4.2s → 1.1s
- 70% faster search results
- +29% increase in repeat purchases
- 22% faster order fulfillment via automation
- Real-time dashboards improved decision-making across teams
Industries We Serve
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