Research On Management Of Marketing Channel Base On Data Mobile Terminal Acquisition Technology And Data Mining

Marketing Channel is an organization consists of manufacturer agency retailer involved in the process of offering customers products;It is responsible for transferring products or services those came from manufacturer to users.So management of marketing channel highly dependent on the channel members and marketing data of retail terminal.The number of retail terminals of company A which referred in this paper is more than 500 thousand.It organizes its marketing channel by area of sale,while its sales and service network has covered all regions of the country.In order to ensure the accuracy of the input and upgrade decision-making and response,company A will carry out the management of marketing channel base on data mobile terminal acquisition and data mining,using the mobile application,and betters the channel management and channel risk warning.This research aims at designing a marketing channel app for enterprise to meet the demand of its marketing channel management:portable terminal of requesting marketing channel analysis,rapid collection of retail customers' information,effective marketing channel control methods.This research also includes the data mining applications: Research solves the geographical overlapping problem in the data collectiong process,achieves target of retail customers allocation scientifically,calculates amount of individuals' work and ascertains lists of target products in various regions during data mobile terminal acquisition.According to the research objectives,the research finish the following several aspects:1)Achievements includes design and development of the marketing channel app.Through this app,users can request marketing channel analysis services from ESB by users' interactions with the mobile application,such as Clicking items,drilling up and down through the items,switching conditions.2)Optimized rules associates employees with shops.Research delineates employees moving areas in the data collectiong process through K-means clustering results,changes the relationship of employees and monitoring shops from employee associating with his all shops directly to employee associating with N areas,those represent his all monitoring shops in the acquisition-schedule tables.Finally,Research verified the clustering results by an optimization algorithm base on K-medios to reduce overlapping problem and enforce the convergence trend.3)Data mining achievement,using the factor analysis method to reduce the dimension of multidimensional space,simplified the data acquisition and assign tasks Scientifically,in data collecting process,in main sales areas,in FMCG business.Taking tobacco as an example,the method finds the local retail key-account and makes the periodical monitoring list of daily data acquisition base on the moblie app.4)The design adds a collection function to this app to collect employees' workload.The function records the task performance of the moblie app users—employees,in execution process.So far,the moblie app only collects three dimensions: coordinate points,work areas,and the time during the employee signing and submitting where in a shop.In this paper,the partial statistics shows 123 employees' work attributes,from Company A,as visiting executors.Using the Fisher classification algorithm,reasearch classificate qualitative work of old employees and fit newcomers for their positions quickly.5)Based on the results of data mining,combined with the example of A company,this paper puts forward the corresponding management and control decision of marketing channels.Including: ABC classification,80/20 rules,smoothing index method and other control methods.