Using AI and Machine Learning to Predict Consumer Buying Behavior: Insights from Behavioral Economics in Case of Alcoholic Beverages

In recent times, the intersect between the emergent capabilities of Artificial Intelligence (AI) and traditional fields of study has led to unprecedented insights and advancements. The current study is situated at the confluence of AI, machine learning, and behavioral economics - a juncture that has not been extensively explored in the context of predicting consumer buying behavior. The research embarked on a journey to understand the multifaceted intricacies of consumer buying decisions, specifically focusing on the consumption of alcoholic beverages. The decision to hone in on this particular area was motivated by the unique blend of social, emotional, and cognitive factors that come into play when individuals choose to consume, or abstain from, alcoholic beverages. Utilizing a sample size of 384 respondents, all aged between 20–40 years in the city of Tashkent, Uzbekistan, the study ensured a mix of diverse perspectives, ranging from students to employed individuals and entrepreneurs. This age bracket, representing both the youth and early middle-age demographic, offered an optimal blend of stability and impulsiveness, factors often considered pivotal in buying decisions. The study concludes that bounded rationality, cognitive factors such as concentration and stress, social and emotional pressures and varied physical challenges are prime in influencing the decision of buying and consuming the said product category.