Network Game Target Marketing Group Mining Based On Decision Tree

With the advent of network information era, network game industry arises at thehistoric moment. At the same time, the network game industry become more and moreprosperous and the market of it has further expanded. Gradually network game hasbecome the leader of the Internet economy. At present most of the game operatorshave a great degree of blindness and randomness when they do the promotion ofmarketing activities to the game players, what will not only waste the game operator’spromotion resources，but also affect the player’s gaming experience. According to theproblem mentioned above, how to accurately find the target marketing group in onlinegame is the most important step for game operator in customer relationshipmanagement (CRM) and also the most urgent step to save operating costs and providehigh quality personalized service.Among all the processes of target marketing group mining, the effective onlinegamers’ information index system is the most basic one, which plays a decisive roleon mining. At present，there are few researches of network game in customerrelationship management (CRM). Besides, there is no systematic research for onlinegamers’ information index system. In addition, the decision tree has been applied invarious industries， but hardly in the network game area. Meanwhile， the effectivemethod to resolve the game data has not yet been found.The innovations of this paper include the breakthrough of the insufficient intraditional customer segmentation based on demographic items and the network gametarget marketing mining based on decision tree. This paper proposes a game players’information index system that contains both the outside and inside game behaviorinformation. In addition, the technology of decision tree analysis was introduced intothe network game target marketing customer mining. This paper puts forward aneffective online game target marketing customer mining framework based on thetechnology of decision tree classification. Finally, through the experiment of realgame case, this paper provides a simple, strong and available application in targetcustomer mining and practical recommendations for the marketing of online game.This paper puts forward a kind of objective and feasible index system of onlinegamers’ information and a mining method for targeting marketing group (specificexample application accuracy above90%). This index system and method not onlymake contributions to the customer relationship management， but also provide a reference to the theory and practice in the network game area. Besides, they reducethe workload of customer relationship management (CRM), and improve themanagement’s efficiency. The last but not least， they save a lot of unnecessarymarketing promotion cost， which makes the enterprise increase profits.