Marketing Issue 2 (2024) · pp. 70-84
COMPREHENSIVE VISUALIZATION AND STATISTICAL MACHINE LEARNING MODELING OF CUSTOMER BEHAVIOR
Karimov Botirjon Ulug‘bekovich, Sariqulova Maftuna Abdujabborovna
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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