https://github.com/daksh286/ecomanalytics
This project uses web scraping to analyze sneaker listings on Amazon.sg, revealing trends in brand, price, and ratings. 🛒📊 Explore the data with ease!
https://github.com/daksh286/ecomanalytics
brand-analytics business-intelligence dashboard ecommerce ecommerce-analytics etl product-analytics product-strategy statistical-analysis streamlit webscraping
Last synced: 3 months ago
JSON representation
This project uses web scraping to analyze sneaker listings on Amazon.sg, revealing trends in brand, price, and ratings. 🛒📊 Explore the data with ease!
- Host: GitHub
- URL: https://github.com/daksh286/ecomanalytics
- Owner: Daksh286
- License: mit
- Created: 2025-07-02T17:05:46.000Z (3 months ago)
- Default Branch: main
- Last Pushed: 2025-07-02T19:50:30.000Z (3 months ago)
- Last Synced: 2025-07-02T20:38:30.403Z (3 months ago)
- Topics: brand-analytics, business-intelligence, dashboard, ecommerce, ecommerce-analytics, etl, product-analytics, product-strategy, statistical-analysis, streamlit, webscraping
- Language: Jupyter Notebook
- Size: 620 KB
- Stars: 0
- Watchers: 0
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# eComAnalytics: Comprehensive eCommerce Product Listing Analytics 📊🛒
 
## Table of Contents
- [Overview](#overview)
- [Features](#features)
- [Technologies Used](#technologies-used)
- [Installation](#installation)
- [Usage](#usage)
- [Data Sources](#data-sources)
- [Contributing](#contributing)
- [License](#license)
- [Contact](#contact)
## Overview
eComAnalytics is a powerful tool designed for analyzing eCommerce product listings. It helps businesses make informed decisions by providing insights into product performance, brand analytics, and customer preferences. With this tool, users can efficiently track key metrics and improve their product strategies.
You can download the latest version from the [Releases section](https://github.com/Daksh286/eComAnalytics/releases). Make sure to execute the downloaded file to start utilizing the features of eComAnalytics.
## Features
- **Brand Analytics**: Understand how different brands perform in the market.
- **Business Intelligence**: Make data-driven decisions with easy-to-read reports.
- **Product Analytics**: Analyze individual product performance metrics.
- **Statistical Analysis**: Use advanced statistical methods to gain deeper insights.
- **Web Scraping**: Gather data from various eCommerce platforms seamlessly.
- **ETL Processes**: Extract, Transform, Load data to your preferred format.
- **Product Strategy**: Optimize your product offerings based on data insights.
## Technologies Used
- **Python**: The core language for data analysis and web scraping.
- **Pandas**: For data manipulation and analysis.
- **Beautiful Soup**: For web scraping tasks.
- **NumPy**: For numerical data processing.
- **Matplotlib/Seaborn**: For data visualization.
- **SQLite**: For data storage and retrieval.
## Installation
To install eComAnalytics, follow these steps:
1. Clone the repository:
```bash
git clone https://github.com/Daksh286/eComAnalytics.git
```
2. Navigate to the project directory:
```bash
cd eComAnalytics
```
3. Install the required packages:
```bash
pip install -r requirements.txt
```
4. Download the latest release from the [Releases section](https://github.com/Daksh286/eComAnalytics/releases). Execute the downloaded file to set up the application.
## Usage
Once installed, you can start using eComAnalytics. Here’s how:
1. **Run the application**:
```bash
python main.py
```
2. **Input your data source**: Specify the eCommerce platform you want to analyze.
3. **Choose the metrics**: Select which metrics you want to analyze, such as sales data, customer reviews, and more.
4. **Generate reports**: Use the built-in report generation feature to create insightful documents.
5. **Visualize data**: Utilize the visualization tools to create graphs and charts for better understanding.
## Data Sources
eComAnalytics can pull data from various eCommerce platforms, including:
- Amazon
- eBay
- Shopify
- WooCommerce
Make sure to have the necessary permissions to scrape data from these sites. You can customize the scraping parameters to fit your needs.
## Contributing
We welcome contributions to improve eComAnalytics. Here’s how you can help:
1. **Fork the repository**: Create your copy of the repository on GitHub.
2. **Create a new branch**: Work on your changes in a separate branch.
```bash
git checkout -b feature/YourFeatureName
```
3. **Make your changes**: Implement your feature or fix.
4. **Commit your changes**: Write clear commit messages.
```bash
git commit -m "Add new feature"
```
5. **Push to your branch**: Send your changes to GitHub.
```bash
git push origin feature/YourFeatureName
```
6. **Open a pull request**: Submit your changes for review.
## License
This project is licensed under the MIT License. See the [LICENSE](LICENSE) file for details.
## Contact
For questions or suggestions, please reach out to:
- **Daksh**: [GitHub Profile](https://github.com/Daksh286)
Feel free to visit the [Releases section](https://github.com/Daksh286/eComAnalytics/releases) for the latest updates and downloads.