The Effect of Product Personalization on Consumer Purchasing Intention, Customer Satisfaction, Brand Loyalty and Artificial Intelligence Applications with Machine Learning

Personalization is the ability of a company to evaluate its customer base as individual entities and achieve customized interactions and transactions based on this evaluation. Advances in information and communication technologies offer new opportunities in collecting and analyzing customer data and carrying out personalized marketing activities. In this context, the use of strategies such as special messages, targeted advertising campaigns, and special offers based on individual customer profiles allows companies to manage customer relations in a more effective and customized way. These developments play an important role in increasing customer satisfaction and loyalty of businesses, optimizing marketing strategies and gaining competitive advantage. The most important of these applications are machine learning and artificial intelligence. Therefore, within the scope of the study, it is aimed to measure the effect of product personalization on consumer purchasing intention, customer satisfaction and the resulting brand loyalty and to present an approach for processing the obtained information with machine learning and artificial intelligence applications. Within the scope of the research, data obtained from questions asked to consumers through digital survey forms with product personalization, purchase intention, customer satisfaction and brand loyalty scales are used. Data were analyzed using IBM SPSS 25.0 and IBM AMOS 26.0 software packages. As a result of the research, it was seen that product personalization has a positive and significant effect on consumer purchase intention and customer satisfaction, and purchase intention and customer satisfaction also have a positive and significant effect on brand loyalty. According to the findings, it was aimed to propose an artificial intelligence-based model that could be useful on consumer behavior and decision-making processes.