Smart Dynamic Pricing System

Overview

The Smart Dynamic Pricing System is an AI-driven pricing solution designed for e-commerce businesses. It predicts optimal product prices based on real-time data, competitor prices, customer demand, stock levels, and seasonal trends. This helps businesses maximize revenue while staying competitive.

Features

• AI-Based Price Prediction: Uses machine learning to determine the best product prices.
• Real-Time Data Processing: Fetches competitor prices (Blinkit, Zepto, Instamart) and market trends.
• Stock Level Analysis: Displays stock trends and inventory fluctuations.
• User-Friendly Dashboard: Provides an intuitive interface for decision-making.
• Seamless API Integration: FastAPI-based backend for efficient data handling.
• Database Management: Uses Supabase for product and pricing data storage.
• Graphical Insights: Stock trends and pricing predictions visualized using Graph API.

Tech Stack

• Frontend: React.js
• Backend: FastAPI
• Database: Supabase
• Machine Learning: Python ( Pandas, NumPy)
• Visualization: Graph API (Matplotlib, Plotly)

Dataset

• The dataset consists of 10,000 entries with 18 unique products.

• Features include MRP, competitor prices, discount percentage, margin, customer sentiment, seasonal impact, stock levels, and delivery distance.

• Sample Output Image

Below is a sample preview of the dataset generated:

How It Works

• Fixed MRP per Product:
  Each product has a constant MRP throughout the dataset.

• Dynamic Pricing:
  Prices for Blinkit, Zepto, and Instamart are computed by applying a discount to the MRP, ensuring all platform prices remain below the MRP.

• Additional Realistic Attributes:
  The script includes fields for product margin, shelf life (derived from the product category), stock levels, and a random order timestamp to enhance the realism of the dataset.

• Randomized Data:
  Details such as location, festive impact, delivery distance, and customer sentiment are randomized to simulate real-world variability.

Prerequisites

Make sure you have the following installed:

• Python 3.x
• pandas library
  Install via:

  pip install pandas

Installation

1. Clone the repository: sh git clone https://github.com/your-repo/smart-dynamic-pricing.git cd smart-dynamic-pricing

2. Install dependencies: sh pip install -r requirements.txt # For backend npm install # For frontend

3. Run the backend: sh uvicorn main:app --reload

4. Run the frontend: sh npm start

Usage

• Navigate to the frontend dashboard.
• Upload product details and view AI-recommended pricing.
• Analyze stock level trends and make informed pricing decisions.
• Apply optimal pricing with a single click.