Fashion Search & Discovery
Intelligent fashion discovery platform powered by Elasticsearch, delivering typo-tolerant search, smart ranking, and personalized recommendations for millions of shoppers.
Search Response
<100ms
Typo Correction
92%
Conversion Lift
58%
Products Indexed
500K+
Tech Stack
Business Context
Building a modern fashion e-commerce platform with intelligent search at its core
Client
Modern Fashion Retailer
Monthly Visitors
2.5M+
Product Catalog
500K+ SKUs
Categories
200+ Types
Business Goal
Build a fashion store where users can find products fast using typo-tolerant search, smart ranking based on popularity and inventory, advanced filters and faceted navigation, autosuggest for quick discovery, and personalized "similar items" recommendations.
Key User Journeys
- •Search with relevance and synonyms (e.g., "formal" → "dress", "office")
- •Typo tolerance and stemming ("sneekers" → "sneakers")
- •Real-time faceted navigation (brand, size, color, price)
Advanced Features
- •Autosuggest with brands, categories, and popular queries
- •Smart ranking (best sellers, in-stock, high-rated)
- •"More Like This" recommendations on product pages
Key Challenges
Traditional database search couldn't deliver the modern e-commerce experience users expect
Poor Search Relevance
Traditional SQL LIKE queries couldn't handle typos, synonyms, or natural language searches. Users typing 'nik shoo' or 'formal wear' got zero results.
Limited Filtering & Facets
Complex WHERE clauses for brand, size, color, price filters were slow and couldn't show real-time aggregation counts (e.g., 'Nike (120 items)').
No Intelligent Ranking
Results were sorted only by recency or price. No ability to boost trending items, in-stock products, or highly-rated merchandise.
Performance at Scale
MySQL full-text search degraded with 500K+ SKUs. Complex aggregations and multi-field searches caused timeouts during peak traffic.
No Autosuggest
Users had to type complete queries without suggestions. No typeahead for brands, categories, or popular search terms led to abandoned searches.
Poor Product Discovery
No 'similar items' or 'more like this' functionality. Users couldn't easily discover related products, reducing cross-sell opportunities.
The Solution
Elasticsearch-powered search and discovery platform built with React and Spring Boot
Full-Text Search Engine
Elasticsearch with custom analyzers for typo tolerance (fuzzy queries), stemming (jean/jeans), and synonym handling (formal/dress/office). Achieved 92% typo-correction accuracy.
Real-Time Faceted Navigation
Aggregations API for instant facet counts across brands, sizes, colors, and price ranges. Updates dynamically as users apply filters with sub-100ms response time.
Intelligent Query Processing
Multi-match queries across title, description, tags with field boosting. Edge n-grams for lightning-fast autosuggest on brands, categories, and popular queries.
Smart Business Ranking
Function score queries boosting in-stock items (+2.0), high ratings (+1.5), trending products (+1.2), and exact title matches (+3.0). Personalized by user preferences.
Product Discovery & Recommendations
'More Like This' queries using term vectors for similarity matching on style, brand, category, and tags. Achieved 58% conversion lift on recommended items.
Real-Time Sync Pipeline
MySQL → Kafka → Elasticsearch pipeline for near-real-time indexing. CDC captures product updates, inventory changes, and pricing updates with <2s latency.
Results & Impact
Measurable improvements in search performance, user engagement, and business metrics
Average query latency including aggregations and highlighting
Successful fuzzy matching on misspelled queries
On searches using intelligent ranking and recommendations
Serving millions of fashion searches with 99.9% uptime
From search results, up from 28% with SQL search
Users engaging with filters compared to previous implementation
Technical Architecture
Modern microservices architecture with real-time search and discovery
Frontend Layer
Technologies
- • React 18 with TypeScript
- • Redux for state management
- • React Query for API caching
- • Tailwind CSS for responsive UI
Key Features
- • Autosuggest with debouncing
- • Real-time facet updates
- • Infinite scroll pagination
- • Similar products carousel
Backend Services
Spring Boot Stack
- • Spring Boot 3.2 REST APIs
- • Spring Data Elasticsearch
- • Spring Security OAuth2
- • Spring Cache with Redis
Search Services
- • Query builder with DSL
- • Aggregation service
- • Suggestion engine
- • Ranking & boosting logic
Elasticsearch Cluster
Configuration
- • Elasticsearch 8.x cluster
- • 3-node setup for HA
- • 500K+ product documents
- • Custom analyzers & filters
Index Design
- • Nested variants (size/color)
- • Synonym token filters
- • Edge n-grams for suggest
- • Function score queries
Data Layer
MySQL (Source of Truth)
- • Products & variants
- • Brands & categories
- • Inventory & pricing
- • Product metrics (ratings/sales)
Caching & Session
- • Redis for query caching
- • User preference storage
- • Session management
- • Rate limiting
Real-Time Sync Pipeline
CDC & Streaming
- • Debezium CDC from MySQL
- • Kafka for event streaming
- • Kafka Connect Elasticsearch sink
- • <2s indexing latency
Monitoring
- • ELK Stack for logs
- • Prometheus metrics
- • Grafana dashboards
- • Alerting on latency/errors
Business Impact
Transforming fashion e-commerce with intelligent search and discovery
Revenue Growth
- 58% increase in search-driven conversions
- 45% higher add-to-cart rate from search
- 3.2x more facet filter interactions
- $8M additional annual revenue attributed to improved search
User Experience
- 92% typo-correction accuracy improves discovery
- <100ms search response delights users
- Zero-result searches reduced by 78%
- Autosuggest drives 40% faster product finding
Operational Excellence
- 99.9% search uptime serving 2.5M+ monthly users
- Real-time inventory sync prevents overselling
- A/B testing infrastructure for ranking experiments
- Scalable to millions of SKUs and concurrent searches
By implementing Elasticsearch with intelligent ranking, typo tolerance, and real-time faceted navigation, we transformed the fashion e-commerce experience. The platform now serves millions of searches monthly with lightning-fast responses, delivering personalized product discovery that drives measurable business growth.
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