Smart Property Price Predictor
On Medha IT Works' Retail Basic – Our B2C Retail Store Platform
At Medha IT Works, we offer learners the opportunity to go beyond classroom theory by solving real-world business problems using production-grade systems. As part of our ML.NET learning track, learners will take on an ongoing Product:
Sales Forecasting Using ML.NET
This project will be implemented on Retail Basic, our all-in-one B2C retail store management platform, built for managing front-end to back-end retail operations.
Project Overview for Learners
In this hands-on project, learners will build a machine learning model using ML.NET to forecast product-level or category-level sales based on historical sales patterns, seasonal trends, promotions, and store-level demand variability.
The project aims to help businesses:
Predict future sales with better accuracy
Plan inventory and restocking efficiently
Align promotions and pricing strategies with forecasted demand
Minimize revenue loss due to stockouts or overstocking
Retail Basic: The Learning Ground for Smart Retail
Retail Basic is a complete B2C retail management solution that empowers businesses to manage their day-to-day store operations — from product handling and inventory to billing and accounting — through a single platform. Whether for standalone stores or growing chains, Retail Basic ensures real-time visibility, smooth operations, and customer-driven insights.
Key Modules that Power Your Retail B2C Success
Product Management
Easily manage your entire product lineup with SKUs, variants, barcodes, pricing, offers, and tax settings. Categorize and update items in bulk to ensure consistent product information across channels.
Inventory Management
Real-time inventory visibility across your stores and warehouses. Track stock movement, manage stock aging, set minimum stock levels, and eliminate stockouts or overstocking with automated alerts.
Warehouse Management
Organize your backend operations with structured warehouse management. Track goods inward/outward, monitor stock positions across bins and racks, and enable seamless transfers between warehouses and stores.
Store Management
Monitor and manage all your physical stores from a centralized system. Enable POS integration, set store-specific pricing, and analyze store-wise performance, billing, and customer traffic in real time.
Sales Management
From billing counters to backend dashboards, manage the full sales lifecycle. Generate invoices, apply discounts, handle returns, and ensure fast, frictionless checkout experiences that keep customers coming back.
Accounts Management
Integrated financial management to track sales revenue, expenses, vendor payments, taxes, and daily cash flow. Maintain accurate records and generate actionable financial reports effortlessly.
ML Use Case Benefits: What Learners Will Achieve
By completing the Sales Forecasting project on Retail Basic, learners will:
Access structured, real-world retail data
Build and train regression/time-series models in ML.NET
Use sales and inventory data to predict future sales volumes
Learn how to embed ML logic into an operational retail platform
Deliver actionable outputs that support retail decision-making
Final Outcome:
A working ML.NET forecasting model that helps store managers predict what products will sell, when, and how much — driving smarter replenishment, pricing, and promotions inside the Retail Basic system
Business to Customer
- Product-to-Customer
- Shelf-to-Counter
- Billing-to-Books