Diagnosis and Optimization of Marketing Strategies based on Association Rule Algorithm

In this paper, we discuss a new method for diagnosing and optimizing marketing strategies by applying association rules. The conventional approach to marketing tactics is usually deficient in its sophistication and personalization, which often ignores the complex relations between different influential factors. In order to overcome this deficiency, the research uses association rules to reveal relationships and patterns in a complex collection of sales data. This makes it possible to accurately diagnose current marketing strategies and to provide tailor-made advice on how to refine and optimize the strategy. This research stresses that it is important for individual marketing tactics to be tailored to the specific situations and needs of various companies. The efficiency of such a methodology is shown by empirical analysis which shows a high degree of support (as much as 50%), reliability (up to 87,6%) and improved (reaching 79,8%) in improving business decision making. This study offers strong data driven ideas and practical advice that will help companies to make informed marketing decisions.