E-commerce Product Delivery Analysis

• Author(s): Jayesh Patil ; Yash Deshmukh ; Prafulla Pawar ; Prachi Pardeshi ; Prof. Harshal Patil
• Paper ID: 1705925
• Page: 177-181
• Published Date: 11-06-2024
• Published In: Iconic Research And Engineering Journals
• Publisher: IRE Journals
• e-ISSN: 2456-8880
• Volume/Issue: Volume 7 Issue 12 June-2024

Abstract

This research investigates the delivery mechanisms within e-commerce, particularly concerning the sales and shipment of electronic products. By examining different phases of the e-commerce product lifecycle, the study employs data analysis and machine learning techniques to gain insights into delivery efficiency and effectiveness. Data was sourced from a prominent e-commerce platform and subjected to exploratory data analysis (EDA) to uncover patterns and trends. Subsequently, machine learning algorithms were used to forecast delivery outcomes, with their performance assessed through various metrics. The results reveal significant factors affecting delivery efficiency and offer practical recommendations for enhancing e-commerce logistics.

Keywords

E-commerce, Data Analysis, Product Sales, Shipment, Machine Learning.

Citations

IRE Journals:
Jayesh Patil , Yash Deshmukh , Prafulla Pawar , Prachi Pardeshi , Prof. Harshal Patil "E-commerce Product Delivery Analysis" Iconic Research And Engineering Journals Volume 7 Issue 12 2024 Page 177-181

IEEE:
Jayesh Patil , Yash Deshmukh , Prafulla Pawar , Prachi Pardeshi , Prof. Harshal Patil "E-commerce Product Delivery Analysis" Iconic Research And Engineering Journals, 7(12)