The electronic commerce market, brought about by the increasingly widespread internet usage, has been a source of opportunity for both manufacturers and consumers. As a result of the shopping opportunities offered on the internet and its reliability day by day, it causes consumers to prefer shopping on the internet more. At this point, researchers examine consumer behavior using data mining methods. Data mining is the process of discovering meaningful, hidden and unpredictable patterns and rules from large databases. In the study, decision trees were created depending on the variables of gender, age and monthly income in order to examine the factors affecting the consumer in online shopping. Decision trees are a data mining method used to classify certain patterns and make predictions from large databases. As a result of the application, using the C5.0 Algorithm for the gender variable, it was concluded that the most important factor for consumers is consumer comments. Using the C&R Tree Algorithm for age variable and monthly income variable, it was concluded that the most important factor for consumers is free shipping.