About

Online marketplace platform connecting buyers and sellers across multiple product categories. Provides trusted marketplace with seller verification, ratings, and secure transactions for diverse products from electronics to handmade crafts.

Features

1. Multi-Category Marketplace

Browse products across 10+ categories (Electronics, Fashion, Home & Garden, Handmade, Books). Provides one-stop shopping experience for diverse consumer needs.

2. Seller Profiles with Verification

Verified seller badges, ratings, and response times build buyer trust. Increases transaction confidence and reduces fraud.

3. Product Listings with Reviews

Detailed product cards with images, pricing, seller info, and customer ratings. Helps buyers make informed purchasing decisions.

4. Search and Filtering

Category-based filtering, price ranges, and seller ratings. Enables quick product discovery in large inventory.

5. Trust and Safety System

Seller verification, buyer protection, and review authenticity checks. Creates safe marketplace environment for transactions.

Technical Development

Stack:

• Next.js (React framework)
• Node.js/Express
• Elasticsearch
• PostgreSQL
• Stripe
• Redis

Product Catalog System

Frontend Implementation: Built using Next.js with server-side rendering and static site generation for optimal SEO performance. Product cards display seller badges, star ratings (4.8 average), pricing, and category tags with colored borders (purple for Electronics, yellow for Fashion, green for Home & Garden, pink for Handmade, orange for Books, blue for other categories). Implemented lazy loading for product images to improve page load times.

Backend Implementation: Node.js REST API handles product CRUD operations with pagination support for large catalogs. Products are organized in a hierarchical category structure with parent-child relationships. Database includes products table with seller relationships, category assignments, and inventory tracking.

Database Design: Products table stores product details including title, description, price, images array, seller reference, category reference, and status. Indexed on category and seller IDs for fast queries. Supports multiple images per product stored as JSON array.

Category System

Frontend Implementation: Category cards feature custom icons, product counts, and colored borders matching brand colors. Each category shows live product count and links to filtered product pages. Subcategory navigation uses breadcrumb trails for easy navigation back to parent categories.

Backend Implementation: Hierarchical category structure supports unlimited nesting levels. Categories include Electronics (500+ products), Fashion (800+ products), Home & Garden (300+ products), Handmade (200+ products), and Books (150+ products). Product counts are cached and updated hourly for performance.

Seller Profile System

Frontend Implementation: Seller cards display verification badge, star rating, response time in hours, join date, and total sales count. Seller pages show full product catalog, reviews, and business information. Verification badge is prominently displayed to build trust.

Backend Implementation: Comprehensive seller verification process includes identity verification through ID upload, business registration check for commercial sellers, bank account verification for payments, and phone number confirmation. Sellers table tracks verification status, rating aggregation, total sales, and response time metrics.

Verification Process: Four-step verification ensures seller authenticity: identity document upload and verification, business registration validation, bank account linking for secure payments, and phone number SMS confirmation.

Rating and Review System

Frontend Implementation: Star ratings use half-star precision for accurate representation. Review cards show buyer information, purchase verification badge, review text, uploaded photos, and helpful vote counts. Reviews can be sorted by most recent, highest rated, or most helpful.

Backend Implementation: Review system includes fraud detection algorithms to identify fake reviews. Rating aggregation runs in real-time to update product and seller ratings immediately after new reviews. Each review is linked to verified purchases to prevent fake reviews. Buyers can only review products they’ve purchased.

Aggregation Logic: Average ratings are calculated automatically when new reviews are submitted. Product rating and review count fields are updated in real-time. Seller ratings aggregate all reviews across their products weighted by recency.

Search and Filtering

Frontend Implementation: Search bar features autocomplete with product suggestions appearing as user types. Filter sidebar allows filtering by category, price range (min/max), seller rating, and seller verification status. Search results update dynamically without page reload.

Backend Implementation: Elasticsearch serves as the primary search engine providing full-text search across product titles and descriptions. Supports fuzzy matching for typo tolerance and synonym handling. Faceted filtering allows multiple filter combinations. Search results are ranked by relevance score combining text match, rating, and sales velocity.

Search Features: Full-text search with typo tolerance, category filtering with multiple selection, price range slider with min/max values, seller rating filter (4+ stars, 3+ stars), and verification status filter (verified sellers only).

Shopping Cart and Checkout

Frontend Implementation: Cart icon displays item count badge. Cart page shows product thumbnails, quantity controls with increment/decrement buttons, individual item prices, and total calculation. Stripe checkout integration provides secure payment processing with card details never touching the server.

Backend Implementation: Cart data is stored in Redis for guest users (session-based) and PostgreSQL for logged-in users (persistent). Order creation process validates inventory, calculates totals, applies promo codes, and creates Stripe payment intent. After successful payment, order confirmation emails are sent to buyer and seller.

Checkout Workflow: Users add products to cart which persists across sessions. Cart review page allows quantity changes and promo code application. Stripe checkout collects payment information securely. Payment confirmation triggers order creation and inventory deduction. Both buyer and seller receive email notifications with order details.

Seller Dashboard

Frontend Implementation: Dashboard displays sales analytics with charts showing revenue trends, order management interface with status filters, product listing tools for adding/editing products, and messaging inbox for buyer inquiries. Analytics include total sales, pending orders, average rating, and response time metrics.

Backend Implementation: Analytics API provides time-series data for revenue tracking, order volume, and conversion rates. Order management allows status updates (pending, processing, shipped, delivered, cancelled). Product management includes bulk upload capabilities and inventory tracking.

Key Metrics: Total sales revenue, pending order count requiring action, average product rating across catalog, average response time to buyer messages, and conversion rate from views to purchases.

Messaging System

Frontend Implementation: Real-time chat interface between buyers and sellers with message bubbles, typing indicators, and read receipts. Message notifications appear in header bell icon. Chat supports image sharing for product inquiries and order issues.

Backend Implementation: WebSocket implementation using Socket.io enables real-time bidirectional communication. Message history is stored in PostgreSQL for retrieval. Automated responses can be configured for common questions. Offline messages are queued and delivered when recipient comes online.

Features: Real-time message delivery, typing indicators showing when other party is typing, image attachment support for product questions, message history retrieval, and automated away messages during offline hours.

Trust and Safety

Frontend Implementation: Report listing button on every product page allows users to flag suspicious content. Dispute resolution center provides interface for buyers and sellers to resolve issues with order mediation. Safety guidelines are prominently displayed during listing creation.

Backend Implementation: Machine learning fraud detection model analyzes listings for suspicious patterns including duplicate content detection, price anomaly identification (too good to be true pricing), fake review detection through pattern analysis, and seller behavior monitoring for policy violations. Flagged items go to manual review queue for human verification.

Anti-Fraud Measures: Duplicate listing detection prevents same item posted multiple times, price anomaly detection flags unrealistic pricing, fake review identification uses ML patterns, and seller behavior monitoring tracks policy violations for suspension decisions.

Deployment: Next.js hosted on Vercel or AWS with automatic scaling, Node.js backend on AWS ECS with Docker containers, Elasticsearch cluster for search infrastructure, RDS PostgreSQL with read replicas for database scaling, ElastiCache Redis for session and cache management, S3 and CloudFront for image delivery, Stripe webhooks for payment processing automation.