Behavioral Segmentation of Black Friday Consumers

Authors

  • Khushleen Kaur Faculty, Department of Masters of Business Administration Engineering, Khalsa College of Engineering and Technology, Amritsar
  • Nirmaljeet Singh Student, Department of Masters of Business Administration Engineering, Khalsa College of Engineering and Technology, Amritsar
  • Akshita Sharma Faculty, Department of Masters of Business Administration Engineering, Khalsa College of Engineering and Technology, Amritsar
  • Preety Kaur Faculty, Department. of Masters of Business Administration Engineering, Khalsa College of Engineering and Technology, Amritsar

Keywords:

Customer Behaviour, Black Friday Sale, Shopping

Abstract

This study explores Black Friday sales by looking at customer behaviour, store dynamics, and sales patterns, with a focus on how these factors affect international retail events both offline and online. The study reveals customer preferences impacted by marketing tactics, product availability, and discounts using statistical analysis, predictive modelling, and historical sales data. By utilising insights into consumer behaviour during high-demand times like Black Friday, the findings seek to help businesses improve marketing strategies, improve customer experiences, and increase revenue. In the end, they provide useful ideas for optimising sales performance.

References

Shashank Awasthi, et al., (2023) “Black Friday sale prediction using supervised machine learning” International Conference on Artificial Intelligence and Smart Communication (AISC).

V. Poojitha, Dr. V. S. S. S. Balaram, et al., (2024) “Machine Learning Application for Black Friday Sales Prediction Framework”. International Journal of Advanced Research in Science and Technology (IJARST) 14(5), 268

Mazhar Javed Awan, et al., (2021) “A Big Data Approach to Black Friday Sales” Intelligent Automation & Soft Computing 27(3):785–797

Published

2026-01-22

Issue

Vol. 2 No. 1 (2026): Special Issue

Section

Review Article