With the arrival of the big data era, customer relationship management, as the cutting-edge theory of enterprise management, especially data mining, has relatively few applied research literature in the retail industry, and the insight concept of "accurate data" will also be developed as a new direction in the retail industry with the arrival of the big data era.
Accurate data, also calledAccurate data, is a kind of data, which is different from rough data and statistical data. It is a specific representation of individuals at the data level. It is derived from careful observation of samples and can record every detail of the phenomenon described in detail.It no longer internally classifies the observed samples.For example, an apple can only be recorded as an apple and will not be generally attributed to a fruit. This is accurate data.
Put forward the new concept of "accurate data" from the original customer relationship theory to strengthen and improve the customer relationship management level for Changchun and domestic retail enterprisesCustomer satisfactionTo gain a competitive advantage.Through the cognitive understanding of accurate customer data to ensure customer relationship management and the analysis of the competitive environment of the retail industry in Changchun, Jilin Province, the application status of CRM in the retail industry in Changchun is explored in depth.On this basis, the author proposes to establish a set of CRM system architecture suitable for the retail industry, as well as implementation strategies, comprehensively implement customer relationship management, deepen the research on customer data through accurate analysis of customer data, hoping to make some contributions to Changchun retail enterprises to meet the arrival of the era of big data and promote their own better development.
Concept source
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award certificate
The third prize of 2013 Challenge Cup Jilin University Students' Extracurricular Academic Science and Technology Works Competition
Title:Research on the Change of Retail Customer Relationship Management in the Age of Big Data -- Taking Changchun City, Jilin Province as an Example
Liu Fucheng: Member of the Communist Party of China, Deputy Dean of the School of Management of Changchun University, Associate Professor, Master, Master Supervisor.In charge of scientific research and postgraduate work.Main research directions: enterprise management, human resource management.For many years, he has been the lecturer of management, production and operation management, strategic management and other major courses. In recent years, he has presided over and participated in the research of more than 10 provincial and horizontal topics, published more than 10 papers, participated in the compilation of three textbooks, and won four provincial and municipal awards.He has guided students to participate in national and provincial discipline competitions for many times and won prizes.Current concurrent postTumen River Society for International CooperationAcademic director.[2]
Huang Jing: graduated from Changchun University with a bachelor's degree in business administration.
Introduction in English
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With the arrival of the era of big data, the data source is the exponential growth in the amount of information and complexity of the rapid expansion of extracting information from massive data to be precise is fast becoming a mandatory requirement of the corporate strategic planning. The retail sector's strategic significance of Big Data not only lying in having huge data, but also in how to specialize processing such data, especially conducting accurate data into customer relationship management (CRM) and changing the traditional data analysis lagging and low frequency,in order to achieve customer value and create economic profit research purposes. This paper focuses on the new idea --‘accurate data’from the original customer relationship theory,which provides some help for Changchun as well as domestic retail enterprises to strengthen customer relationship management level, improve customer satisfaction, in order to gain competitive advantage. By cognitive understanding of customer relationship management and customer data analysis of Changchun, Jilin Province’s competition in the retail environment,we are exploring the CRM in the city of Changchun retail status. On this basis,I proposes that by the accurate analysis of customer data, the establishment of a retail CRM system architecture and implementation strategy and the full implementation of customer relationship management is required, in order to deepen customer data.I want to contribute to Changchun retail enterprises by meeting the arrival of the era of big data and promoting their better development.
Application in management
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With the application of data mining technology in CRM, retail enterprises have received effective technical assistance in profitability analysis, customer identification and customer acquisition, commodity sales status and other aspects, thus improving business efficiency.Data mining on accurate data can help retail enterprises provide more personalized services for customers.The specific role of accurate data in CRM can be analyzed from the following aspects.
sale
Accurate data can provide support for accurately predicting customers' psychological price, accurately knowing customers' preferences, and knowing customers' needs in advance, so as to help sales personnel provide customers with targeted, forward-looking, accurate and most easily accepted sales services.Salesmen interact with potential customers, develop them into customers by stimulating their purchase desire, and effectively maintain their loyalty, thus forming a profit model for retail enterprises.
customer service
Customer service is the most critical part of CRM. In order to attract potential customers and maintain the loyalty of existing customers, enterprise business must provide customer service superior to competitors.Analyze the customers' life and consumption habits through accurate data, recommend the products that best meet their preferences and are most likely to be accepted for customers, so as to shorten customers' consideration time, improve customer satisfaction and satisfaction.
Customer retention
Through accurate data analysis, study the number of times customers repeatedly purchase the same product in a certain period of time, so as to evaluate the popularity of the product and eliminate the unpopular product;Set the time interval between customer visits to remind, identify customers who will spend a long time in the future, and timely conduct return visits and targeted promotions to retain customers.
risk assessment
Risk is an uncertainty that deviates from the expected future results, andCommercial fraudGenerally, retail enterprises suffer huge losses.Extract customer reputation data after accurate processing of customer relationship data, which will serve as a warning for fraud identification and risk assessment.
While using regression analysis, decision tree analysis, neural network and other data mining technologies to predict and identify fraud, accurately processed customer reputation data is added to the historical database to help find similar but undetected cases.With the accumulation of knowledge in the database, the quality and credibility of the prediction system will be greatly enhanced.
Then the sales series model is established, and the components of the time series may be multiplicative or additive. Therefore, the time series can be decomposed by a variety of models, including additive model, multiplicative model, and additive multiplicative hybrid model.
Considering the change rule of the retail industry in Changchun and the characteristics of the customer data itself, if seasonal variation (S), cyclical variation (C), and irregular variation (I) depend on the change of long-term trend (T), the multiplication model or the addition and multiplication hybrid model should be used,Otherwise, the additive model can be considered.
Addition model:Yt=Tt+St+Ct+It
Multiplication model:Yt=Tt×St×Ct×It
Add multiply hybrid model:Yt=Tt×St×Ct+It
Or Yt=St+Tt×Ct×It
By measuring and analyzing the development trend of business phenomenon in Changchun retail industry in the past period, we can understand and grasp the regularity of market development and change, and analyze the long-term trend of this phenomenon, which provides necessary conditions for statistical prediction.After eliminating the impact of long-term trends in the original time series, we can better collect, sort out, analyze and mine customer relationship data on the basis of better studying seasonal changes and cyclical changes.
Retail CRM Structure
Retail CRM architecture
In view of the existing problems in the retail customer relationship management in Changchun, this paper attempts to introduce the idea of "accurate data" into the retail customer relationship management analysis based on the analysis method of data mining, and carry out quantitative and qualitative analysis from multiple perspectives using the decision tree, statistical analysis and association analysis methods of data mining.
With the exponential growth of data sources and the rapid expansion of the amount and complexity of information, the ability to extract information from massive data is rapidly becoming a strategic imperative.We can see that due to the explosive growth of data, enterprises can quickly obtain strategic decision-making information from these chaotic data, which is the key to winning the opponent.On the basis of management, through the analysis of the decision tree, we can find the factors that have a greater impact on the overall customer relationship management;On the basis of applied statistics, the regression equation in statistical analysis can be used to find out the correlation between various factors and the correlation between them;At the same time, correlation analysis can provide more internal links between hidden factors.
Specifically, through the analysis of the collected accurate data, we can understand the comprehensive situation of the market, the overall situation, the specific situationCustomer satisfaction, consumption behavior, loss status, marketing promotion effect, service and support effect, so as to generate the best decision-making scheme, provide strong technical support for decision-making, and ultimately help retail enterprises to gain absolute competitive advantage.[3]
Theoretical institution
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Greatly create provincial excellence
The Cloud Data Analysis Research Group was prepared in Shanghai on November 28, 2012. It was proposed by Song Jinbo, the director of the former Shanghai Oriental Morning Post Financial Week, and approved by Zhang Hongzhao, the former secretary of the Youth League Committee of Changchun University. Now it is composed of Liu Fucheng, the former deputy director of the Department of Business Administration, Huang Xiaohong, the associate professor of the Department of Financial Management, and Wang Liping, the former 2011 professor of Applied StatisticsFinancial ManagementLiu Yijin served as the head of the research team to prepare for the 13th Challenge Cup Chinese College Students Academic Science and Technology Works Competition, plan to seek technical guidance from Jilin Xinde Project Data Analyst Firm Co., Ltd., and analyze the integration of retail customer relationship management and big data era.At present, the research team has completed the provincial excellent project of Jilin Province College Student Innovation and Entrepreneurship Training Plan（Project name: Business Plan of China Cloud Data Analysis Services Co., Ltd）, the third prize of the 2013 Challenge Cup Jilin University Student Academic Science and Technology Works Competition, and published the management academic paper "Research on the Change of Retail Customer Relationship Management in the Age of Big Data - Taking Changchun City, Jilin Province as an Example";In 2014, he won the second prize in the 6th Challenge Cup Changchun University Undergraduate Entrepreneurship Plan Competition.
Personnel introduction
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Song JinboSenior media person, columnist.Graduated fromNortheast Forestry University, former member and civil servant of the Tibet Autonomous Region Forest Survey.He has successively served in Xiaoxiang Morning NewsChangjiang Business Daily, Oriental Morning Post and other media, famous financial commentator, once served as a macroeconomic researcher, and the weekly financial director of Oriental Morning Post.The column "Notes of the Forest Research Team" records the personnel fragments in Tibet in the past ten years.[4]
Zhang HongzhaoMember of the Communist Party of China, Master, graduated from Jilin University.He is currently the head of the Publicity Department of the Party Committee of Changchun University (at the level of the head office), and once served as the secretary of the Communist Youth League Committee of Changchun University.
Huang XiaohongTeacher, Master, Associate Professor, Department of Financial Management, School of Management, Changchun University, graduated fromNortheast Forestry University。She is the lecturer of financial management, securities investment, statistics and other courses, and the provincial excellent course lecturer of financial management.Pay attention to the cultivation of students' entrepreneurial quality, guide students to participate in the "Challenge Cup" Undergraduate Entrepreneurship Plan Contest and Science and Technology Paper Contest for many times and achieve good results. In recent years, he has presided over and participated in 10 provincial, university science, teaching and research projects;8 papers were published publicly.[5]
Wang LipingHe was the former head of the Department of Tourism Management, professor, and master's supervisor. He mainly taught statistics, tourism economics and other courses.In recent years, he has presided over and participated in 5 provincial science, teaching and research projects;Chief editor of 2 textbooks;He has published 20 papers, including 3 papers in important journals.[6]
