Degree
Master of Science in Data Science
Department
Department of Computer Science
Faculty/ School
School of Mathematics and Computer Science (SMCS)
Date of Submission
Fall 2025
Supervisor
Dr. Syed Ali Raza, Assistant Professor, Department of Computer Science, SMCS
Committee Member 1
Dr. Syed Ali Raza, Supervisor
Keywords
Clustering, Customer Segmentation, Machine Learning, E-Commerce, Email Marketing
Abstract
After the global pandemic, the e-commerce industry worldwide has seen an influx of new entrants therefore, making the market very competitive. In today’s day and era, data driven approaches are the only path towards success. This project applies machine learning and deep learning methodology of clustering for customer segmentation to a company selling packaging materials in UK’s e-commerce industry. Using the company’s historical order data, multiple clustering algorithms such as KMeans, Gaussian Mixture Model (GMM), Balanced Iterative Reducing and Clustering Hierarchies (BIRCH), Autoencoder based clustering, and Deep Embedded Clustering (DEC) will be applied to it. The findings from this project highlight that deep learning-based models specifically Autoencoder based clustering outperformed traditional machine learning clustering algorithms. Using this customer segmentation, personalized email marketing campaigns were run which surpassed the company’s usual conversion percentage of 2.1%.
Document Type
Restricted Access
Submission Type
Research Project
Recommended Citation
Fatima, F. (2025). Personalised E-Commerce Marketing Using Customer Segmentation Via Clustering (Unpublished graduate research project). Institute of Business Administration, Pakistan. Retrieved from https://ir.iba.edu.pk/research-projects-msds/63
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