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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.
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Project Snapshot

Client

Mid-Size D2C Brand

Industry

Retail · eCommerce

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

Shoplyft eCommerce Personalization Platform Architecture

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

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

Recommendation Engine Data Flow Diagram

Shoplyft-—-Personalization-Recommendation-Flow

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Build a High Performance eCommerce Platform with Inexture

From lightning-fast storefronts to backend automation and personalized discovery experiences, Inexture helps brands scale their eCommerce operations with enterprise-grade engineering.
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