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A global e-commerce website prototype, supporting sellers, customers and delivery person. A price predictor using machine learning is made and embeded with every page to know if the product is costly or cheap. This project was in Top 20 of Self-Reliance Based Intelligent India Hackathon (SRIIH). Technologies Used : Django, scikit-learn

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🛒 Smart Product Sale WebApp with Price Prediction

Project Overview

This project was originally built during the lockdown for a hackathon to help local businesses sell their products online and connect with delivery personnel efficiently. While it was designed to address immediate challenges, the platform has broader applications beyond the hackathon, making it adaptable for various business models.


Problem Statement

During the lockdown, many business owners struggled to sell their products, and many people lost jobs. There was a need for a platform that could:

  • Enable businesses to reach local customers online
  • Connect delivery personnel for timely order fulfillment
  • Help startups and businesses optimize pricing

Our Solution

Our web application empowers businesses to sell online while integrating smart pricing and analytics:

  • Business-to-Customer Sales – Businesses can list products online for local customers.
  • Delivery Notifications – Registered delivery personnel are notified whenever a purchase occurs.
  • ML Price Predictor – Each product page includes a predictive model that estimates prices based on features.
  • User Feature Collection – Collects user input to understand product preferences and pricing trends.
  • Startup Advantage – Enables startups to create products with optimized features and competitive pricing.

Features

  • Online product listing for local businesses
  • Real-time delivery personnel notifications
  • Machine learning-based price estimation per product
  • Data collection for user preferences and feature trends
  • API service for businesses to reduce backend overhead

Business Model

  • Market Insights – Aggregate user preferences to sell datasets to companies and startups, helping them design popular products at optimized prices.
  • API Subscription – Offer API access to businesses to integrate the platform into their systems without heavy backend investment.

Achievements

  • Ranked Top 20 in the Self-Reliance Based Intelligent India Hackathon (SRIIH)

Potential Use Cases

  1. Wholesale Distribution – Manage bulk sales and inventory across multiple retailers.
  2. Dropshipping – Seamlessly connect businesses with delivery personnel for on-demand fulfillment.
  3. Large Retail Chains – Coordinate multiple stores under one system with analytics.
  4. Shopping Mall Management – Aggregate multiple stores and monitor sales performance.

Future Opportunities

  • Advanced ML for price optimization strategies
  • Enhanced inventory and order management
  • Integration with payment gateways and real-time logistics tracking
  • Expansion to a multi-city platform connecting businesses, customers, and delivery personnel

This project demonstrates how a hackathon idea can evolve into a scalable business solution with multiple real-world applications.

Achievement

  • Top 20 of Self-Reliance Based Intelligent India Hackathon (SRIIH).

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A global e-commerce website prototype, supporting sellers, customers and delivery person. A price predictor using machine learning is made and embeded with every page to know if the product is costly or cheap. This project was in Top 20 of Self-Reliance Based Intelligent India Hackathon (SRIIH). Technologies Used : Django, scikit-learn

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