ShopLyft - eCommerce Personalization & High Speed Storefront
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
- Built using React + SSR to improve SEO, reduce load time, and increase PageSpeed performance.
- Instant dynamic filtering
- Autocomplete and category boosts
- Relevance-weighted ranking
- Synonym mapping
- Fuzzy search for typos
- “Recommended for You”
- “Similar Products”
- “Trending Now”
- Cart-based suggestions
- Real-time warehouse sync
- Automated SKU availability
- Order routing automation
- REST-based connections to fulfillment systems
- Campaign analytics
- Sales & SKU trends
- Funnel tracking
- Abandoned cart insights
- 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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