B2B Wholesale E-Commerce Platform
Full-stack B2B e-commerce platform with AI-powered inventory management, personalized pricing, and seamless ERP integration
Overview
Metro Cash & Carry serves millions of HoReCa (Hotels, Restaurants, Catering) and small business customers across India. We built a comprehensive B2B e-commerce platform enabling digital ordering with complex pricing rules, real-time inventory sync across 50+ warehouses, and AI-powered demand forecasting that transformed their wholesale operations.
The Problem
B2B wholesale is fundamentally different from B2C e-commerce. Customers have negotiated pricing, credit terms, and bulk ordering needs. Metro's wholesale customers—restaurants, kirana stores, offices—relied on physical store visits and phone orders, missing the convenience of digital while Metro missed the efficiency of automation.
Key Challenges
Complex Pricing Logic
Each customer has unique negotiated prices based on purchase volume, payment terms, and relationship tenure. A single product might have 50+ different prices across customer segments. Pricing rules were managed in spreadsheets and manually applied.
Inventory Fragmentation
50+ warehouse locations with independent inventory systems. No real-time visibility into stock across network. Orders frequently failed due to out-of-stock items discovered only at fulfillment. No intelligent routing to nearest warehouse with stock.
Sales Team Inefficiency
Field sales representatives visited customers with paper catalogs and manually entered orders. Order entry was error-prone and time-consuming. No mobile tools for on-the-spot ordering. Customer history and preferences weren't accessible in the field.
Demand Unpredictability
Seasonal demand spikes (festivals, holidays) caught inventory off-guard. Popular items stocked out while slow movers occupied warehouse space. No systematic approach to demand forecasting or inventory optimization.
How We Built It
Core Platform & Pricing Engine
Built flexible e-commerce platform with rule-based pricing engine supporting customer-specific rates, volume discounts, and promotional pricing. Integrated with SAP for customer master data and pricing rules synchronization.
Inventory & Fulfillment
Created real-time inventory service aggregating stock across all warehouses. Built intelligent order routing selecting optimal fulfillment location based on stock availability, delivery distance, and warehouse capacity. Implemented safety stock and reorder point automation.
Mobile Sales Enablement
Developed React Native app for field sales team with full catalog, customer history, and on-the-spot ordering capability. Offline mode for areas with poor connectivity. GPS-based visit tracking and route optimization.
AI-Powered Forecasting
Implemented demand forecasting models predicting SKU-level demand by warehouse. Built reorder recommendation engine suggesting optimal purchase quantities. Created customer-specific replenishment suggestions based on order history patterns.
Solution Highlights
Dynamic Pricing Engine
Rule-based system handling customer-specific pricing, volume tiers, promotional offers, and credit terms. Prices sync from SAP in real-time. Supports complex B2B scenarios like contract pricing and quantity breaks.
Real-Time Inventory Network
50+ warehouses connected with live stock visibility. Intelligent order routing minimizes delivery time and cost. Automatic backorder handling with customer notification.
Mobile Sales Platform
Field sales app with full catalog, customer history, and ordering capability. Works offline in low-connectivity areas. Reduces order entry time from 30 minutes to 5 minutes.
AI Demand Forecasting
ML models predicting demand by SKU, warehouse, and time period. Accounts for seasonality, festivals, and promotional impacts. Generates automated reorder recommendations.
Technical Deep Dive
The platform uses Next.js for the customer-facing web application with server-side rendering for SEO and performance. The pricing engine is a rules-based system built with Node.js, supporting complex conditional logic (if customer tier = gold AND order quantity > 100 AND payment term = prepaid, apply 12% discount). Real-time inventory is maintained in Redis with eventual consistency from SAP via Apache Kafka. The demand forecasting system uses Facebook Prophet for time-series prediction with holiday and promotion effects, running nightly batch predictions that inform the reorder recommendation engine.
AI Capabilities
Demand Forecasting
SKU-level predictions accounting for seasonality and promotions
Reorder Optimization
Automated purchase recommendations balancing stock and carrying costs
Customer Replenishment
Predicting when customers will need to reorder based on consumption patterns
Search Relevance
Learning from purchase history to improve product search results
Technology Stack
Frontend
Mobile
Backend
Integration
ML/Analytics
Infrastructure
Results & Outcomes
3x
Digital order volume
Year-over-year growth in online ordering
-50%
Order processing time
Automated workflows replacing manual entry
50K+
SKUs online
Full catalog with real-time availability
Real-time
Inventory sync
Across 50+ warehouse locations
85%
Forecast accuracy
Demand predictions for top-moving SKUs
-30%
Stockout rate
Improved availability through better forecasting
Services Used for the Client Product
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