Abstract: For a long time, businesses tried to understand why a person buys one thing and not another. In history, people would just watch customers and make guesses. This was not very accurate. The main problem is that it is very hard to know what a customer will do. So many things like their culture, their friends, their age and their money change their choices. This makes it difficult for companies to sell their products and they waste lots of money on advertisements that dont work. This project gives a solution using machine learning. A system is proposed that uses data about consumers to predict their buying decision. The data includes personal factors, social factors, and economic factors. The system will use a machine learning algorithm like a Decision Tree to learn from past data. This model will then predict if a new customer is likely to buy a product or not. This helps companies to focus their efforts and understand their customers in a much better way.

Keywords: Consumer Behavior, Predictive Modeling, Data Analytics, Marketing Strategy, Economic Factors, Social Factors, Psychological Factors, Customer Segmentation

Downloads: | DOI: 10.17148/IARJSET.2025.121006