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No. 2 (2024)
Marketing

Scientific articles

COMPREHENSIVE VISUALIZATION AND STATISTICAL MACHINE LEARNING MODELING OF CUSTOMER BEHAVIOR

DOI 10.67668/mj/2024iss2/1641 Pages 70-84

Published 2024-04-30

Authors
Karimov Botirjon Ulug‘bekovich a , Sariqulova Maftuna Abdujabborovna b
Affiliations
a Tashkent State University of Economics image/svg+xml
b Tashkent State University of Economics image/svg+xml
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Abstract

The research explores how advanced data analytics can predict customer behaviors and support marketing strategies in the food industry, highlighting the struggles of a food company with ineffective past marketing efforts. By examining customer demographic and transactional data, it identifies patterns leading to predictive buying behavior. Utilizing the XGBoost algorithm, the study developed a model that accurately predicts customer responses to marketing tactics. The findings underscore the importance of targeted marketing for enhancing profitability and customer engagement, showcasing the impact of data-driven analytics in strategic marketing planning.

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