Decision tree based targeting model of customer interaction with business page

Abstract

: Company branding through social networks is most effective if it reaches the right customers. This study explores how to improve business page targeting on Facebook by customer behavior targeting, age and gender to form a more comprehensive contextual advertising strategy. Paper focuses on empirical modeling of targeting based on decision trees. The general practice of such models developing does not take into account business goals sufficiently. To correct this, we propose to create an algorithm for customer interaction simulating with a business page on Facebook based on decision trees within the control and optimization of a company's marketing strategy. The resulting algorithm combines statistical training principles and business goals in the form of cam-paign income maximizing. The basic approach to the marketing strategy formation is considered, the parameters of the algorithm and the algorithm of forming the client interaction targeting with the business page on the basis of decision tree are established. Based on the above algorithm, we build a model of customer interaction targeting with a business page based on the decision tree us-ing the data of contextual advertising campaign on Facebook. Based on the simulation results, a re-formation of the advertising campaign and analysis with the input data were performed. The results of the study confirm the value of the proposed method, since the targeting model of customer interaction with a business page based on decision trees recommends significantly more profitable target groups than a few benchmarks.