Factors affecting the increase of click-through rate and users' trust in personalized online advertisements

Data-driven marketing as a strategy for studying customer behavior based on metadata analysis will help to predict their behavior and increase the rate of return on investment. Many Iranians, especially young people, are users of various social networks and Internet sites and are exposed to advertisements on these networks. In the present study, 446 students of Tehran universities and their relatives who are users of the Instagram social network were surveyed based on the survey method and the available sampling method and snowball. For this purpose, a conceptual model based on consumer opinion has been used regarding the main factors influencing the increase of clicks in personalized online advertising. The research findings indicate that the consumer decision to click on the ad is made based on variables such as previous familiarity with the brand, visual appeal, mental engagement with the product and the quality of information for the consumer. Hence, trust in the processes of visual appeal and information quality plays a mediating role and therefore affects the will and decision of users to click on the ad. Privacy and the consumer's concern about non-compliance will increase his mental involvement about the product and reduce the consumer's confidence and decision to click. According to the research results, although accurately personalized advertising has higher goals in mind, it may negatively affect consumer privacy concerns and in fact lead to the weakening of their goals.