Sales Forecasting Using ML.Net

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