Ecommercetools

EcommerceTools is a Python data science toolkit for ecommerce, marketing science, and technical SEO analysis and modelling and was created by Matt Clarke.

Digital Marketing & SEOPythonMIT

Abstract

Ecommercetools is an open-source Digital Marketing & SEO project. EcommerceTools is a Python data science toolkit for ecommerce, marketing science, and technical SEO analysis and modelling and was created by Matt Clarke. EcommerceTools is a data science toolkit for those working in technical ecommerce, marketing science, and technical seo and includes a wide range of features to aid analysis and model building. The package is written in Python and is designed to be used with Pandas and works within a Jupyter notebook environment or in standalone Python projects. It is built using Python. Key capabilities include: Transactions; Products; Customers. The complete source code is publicly available on GitHub under the MIT License, making it a useful reference for students building a Digital Marketing & SEO mini project or final-year project.

1. Introduction

EcommerceTools is a data science toolkit for those working in technical ecommerce, marketing science, and technical seo and includes a wide range of features to aid analysis and model building. The package is written in Python and is designed to be used with Pandas and works within a Jupyter notebook environment or in standalone Python projects.

2. Objective

EcommerceTools is a Python data science toolkit for ecommerce, marketing science, and technical SEO analysis and modelling and was created by Matt Clarke.

This project demonstrates how Python can be applied to a real-world Digital Marketing & SEO problem.

3. Key Features / Modules

  • Transactions
  • Products
  • Customers
  • Advertising
  • Operations
  • Marketing

4. Technology Stack

Python

5. System Requirements

General requirements for this technology stack — check the README for exact versions.

  • Python 3.8 or later
  • pip / virtualenv for dependencies
  • VS Code, PyCharm or Jupyter Notebook
  • Git (to clone the repository)

6. Installation & Setup

git clone https://github.com/practical-data-science/ecommercetools.git
cd ecommercetools

Full setup instructions are in the project README.

7. Future Enhancements

Suggested extensions you can add to make this your own project.

  • Export reports to Google Sheets or PDF
  • Schedule weekly automated reports
  • Add competitor comparison

8. Viva / Review Questions

Common questions examiners ask for projects in this domain.

  1. Which marketing or SEO problem does this tool solve?
  2. Which data sources or APIs does it use (Search Console, Analytics, social platforms)?
  3. Which metrics or KPIs does it report and how are they calculated?
  4. How could the output help a business make decisions?
  5. How would you schedule it to run automatically?

9. Source Code & License

This project is developed by practical-data-science and published on GitHub under the MIT License. Please follow the license terms and credit the original author when you use or modify this code.

View Source on GitHubDownload ZIP

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