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E-Commerce-Logistics-Minimizing-Shipping-Delays

Project Overview

This project aims to analyze and improve e-commerce logistics by minimizing shipping delays and optimizing supply chain efficiency. Given the increasing demand for fast and reliable delivery, predicting delays and identifying key factors affecting shipping performance is crucial for customer satisfaction and operational success.

Objective

  • Identify the major causes of shipping delays in e-commerce.
  • Develop predictive models to anticipate delays and enhance supply chain efficiency.
  • Provide actionable insights to improve delivery performance and customer experience.

Data Source

https://www.kaggle.com/datasets

Presentation

https://docs.google.com/presentation/d/10GSx_eEFKBDrTDhWAY8UX0XbmGg7LiVszFlhIABEiXU/edit#slide=id.g33ac9d23d16_1_1678

Data Selection and Preparation

  • Handling Missing Values – Dropped incomplete records.
  • Standardizing Column Names – Ensured consistency for easier analysis.
  • Dropping Redundant Features – Removed unnecessary variables (e.g., order_region).
  • Separating Date and Time Features – Enhanced temporal analysis.

Exploratory Data Analysis (EDA)

  • The United States has the highest total sales, followed by France and Mexico.
  • The Fan Shop generates the highest revenue, while smaller departments like Book Shop and Pet Shop have minimal sales.
  • Standard Class shipping experiences the highest delays, while Same-Day shipping performs best for on-time deliveries.
  • High discount levels do not necessarily lead to early delivery, and larger orders tend to face more delays.

Key Findings and Insights

  • Delayed deliveries are common across all order statuses.
  • Standard Class shipping has the highest delayed deliveries
  • Orders marked as "Complete" have the highest number of delays.

Conclusion

This project provides valuable insights into e-commerce logistics, highlighting key factors contributing to shipping delays. The predictive models developed can help businesses proactively address delays and enhance supply chain performance.

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