Conjoint analysis is a statistical method used to understand how consumers make decisions when choosing between product or service alternatives. It is based on consumer preferences and helps identify which attributes of a product or service are the most important. The analysis is conducted by presenting respondents with alternatives that have different combinations of attributes, allowing them to select their most preferred option. These choices reveal the importance of each attribute and its impact on the final decision. Data is typically collected through surveys, and the results are analyzed using statistical models such as regression analysis or hierarchical Bayesian methods. The findings allow for the calculation of the commercial value of each attribute and its levels. This information is used to design optimal products or services that best meet consumer needs. Furthermore, conjoint analysis helps forecast market shares by simulating various market conditions. It is applied across multiple fields, including pricing strategies, product development, and marketing decisions. The ultimate goal is to help businesses make data-driven decisions that enhance their competitive advantage.