Research On G University Students Consumption Behavior Based On One-card Data

With the in-depth promotion of information construction in our country,the following is the vigorous development of information construction in colleges and universities all over the country.In order to better create an excellent intelligent campus environment,colleges and universities should make information better serve the work,scientific research and life of teachers and students.In recent years,the funds and efforts invested in the construction of the campus smart card system are increasing year by year,and the service functions of the campus smart card system are becoming more and more perfect.Campus smart card has been widely used in all aspects of campus life such as daily catering consumption,bank deposit,campus supermarket shopping,school bus,water opening,laundry,electricity purchase,meeting attendance,library,gymnasium,etc.With the use of campus smart card,a large number of campus smart card data will be generated every day.These data record a large amount of information about students' daily study and consumption,but the intrinsic value of the data,which is helpful to optimize the marketing and improve the service of merchants in the school,is often ignored by people.Using this information can be targeted to understand the consumption habits and shopping preferences of students in the school.This paper focuses on the study of students' daily consumption in the campus through data mining and other technical means,and makes cluster analysis and research on students' consumption in canteens and supermarkets.The purpose of the study is to further bring convenience to the daily work,study and life of teachers and students in the school,and at the same time to gradually help improve the logistics service in the school efficiently and accurately and to provide business marketing suggestions.This paper mainly collects and sorts out nearly one million pieces of consumption data of G University in the most representative week in April 2019,such as all-campus one-card canteens,business supermarkets and online payment,etc.,as the research object.In order to better explore the laws and information hidden in the data of the campus smart card management platform,the following work has been done:(1)Save and sort the data in batch in the form of Excel documents,and preprocess the data.Data cleaning,screening and desensitization are carried out to eliminate the defects,errors and redundancies in the data and provide effective data support for later data mining analysis.(2)Firstly,the overall consumption situation of G University is studied,and the data of dining hall consumption behavior,supermarket consumption behavior and other consumption behaviors of students are analyzed by multidimensional statistics,so as to comprehensively analyze the consumption behaviors of G University students and realize data visualization.After that,with the help of data mining tools,K-means clustering algorithm is used to do clustering analysis on G University student canteen consumption behavior and supermarket consumption behavior data,to study student consumption preferences,to analyze the main reasons that affect the consumption differences among different student groups,and to put forward targeted rationalization proposals.(3)Innovatively put forward reasonable countermeasures for the marketing improvement of logistics merchants,and give specific improvement measures and suggestions.Through the research work in this paper,the consumption preferences of three different types of students,undergraduate,master and doctoral,are deeply explored,and detailed and reasonable suggestions are put forward for the future marketing optimization and service improvement of school logistics merchants,which provides convenience for the future work of school merchants.