Research On T Company's Offline Channel Optimization Strategy

This paper takes T company of a provincial branch of a telecom operator as the research object,and conducts an in-depth study on the management optimization strategy of its offline channels.In the context of Internet transformation,how does T company's offline channels from the three dimensions of addition,operation,and exit,better use big data for channel management,getting new users,maintain old users,and improve user experience,thereby providing better management for the company? Increasing income by quality has become a topic worthy of study in management.Chinese and foreign scholars' research on channel conflict and synergy,channel effectiveness evaluation and channel site selection provides the theoretical basis for this article.Through the analysis of the status quo of T company,it shows that T company's offline channels are shrinking,and the number of active users of online channels continues to rise.Channel synergy operation is an inevitable development trend.PEST analysis and SWOT analysis discuss the overall situation of T company from the politics,economy,society and technology environment of T company,as well as T company's strengths,weaknesses,opportunities and threats.Then it focuses on the analysis of the problems of T company short of channel synergy,low efficiency of some channels and unscientific channel site selection.And then this paper gives the optimization goals and principles,and on this basis,proposes a synergy strategy,a streamlining strategy and an enhancement strategy.Synergy strategy is an all-round information sharing strategy based on the data middle office.This strategy enables online and offline channels to be organically combined,so that all channels have the ability to provide users with seamless services.In the synergy strategy,online channels have no time and space constraints,and can directly coordinate with offline channels,but offline channels must consider geographic restrictions.In response to this problem,this paper uses the AHP to establish a channel's performance evaluation system,and uses the evaluation results to streamline channels.Then it further utilizes the characteristics of operator big data that contains a large amount of geographic information,and innovatively applies the classification regression tree in machine learning to offline channel site selection.The algorithm also takes into account the user's attributes such as online business handling,display,and traffic drainage,as well as the offline store experience and delivery requirements,optimizes the offline channel layout,and achieves the goal of improving overall efficiency.