APPLICATION OF DATA ANALYSIS FOR PREDICTING CONSUMER BEHAVIOR

Abstract

This article explores the importance of analyzing consumer behavior in the context of the digital economy and increasing market competition. It highlights the role of data analysis and modern Data Science technologies in shaping personalized marketing strategies, predicting customer behavior, and making well-informed managerial decisions. Special attention is given to the practical application of analytical methods such as clustering, association rule analysis, logistic regression, decision trees, machine learning methods, and time series analysis. The article provides successful examples of how these approaches are used by major international companies such as Spotify, Walmart, Netflix, Uber, and others. The advantages and limitations of each method are outlined, enabling a reasoned selection of analytical tools to solve specific business challenges.