The Revolution of Retail Enterprise Network Marketing in Big Data Era

The Revolution of Retail Enterprise Network Marketing in Big Data Era WANG Dan 1, LIU Teng 2 1. The School of Business, Beijing Wuzi University, 101149 2. The Graduate School, Beijing Wuzi University, 101149 wangdan9080@sohu.com Abstract: The arrival of the big data era not only subvert the traditional media habits, but also conduct a comprehensive reform on marketing concepts and methods of marketing, big data marketing will become the future trend. This paper analyzes the relationship between data mining and consumer in network marketing, shows the processes and results of data mining, and then proposes a new model of network marketing of retail enterprises in big data era, that is precise network marketing, network marketing of associated recommendations and pioneering network marketing, and finally come to the conclusion that the technology of data mining provide critical information and decision support for precision marketing and efficient marketing, only companies conduct the big data technology-based network marketing reform, can they build the core competitiveness. Keywords: Big data, Data mining, Consumer, Model of network marketing 1 Introduction Today, we are in the world of explosion of data, Facebook has a daily diffusion of information about 4,000,000,000, Google has to process more than 24 petabytes of data every day, YouTube received 800 million visitors every month, the growth rate of the data processing capabilities of the computer is 9 times of the rate of economic growth, such rapid data growth brings about global expansion of social networks, and it is rewriting the rules of marketing. Judy Strauss (2004) pointed out that the flow of goods, information flow and capital flow in the network marketing channels compose a system of interdependence, whose common action is to create value in the process of passing products to consumers through network channels; Edward J.Deak (2006) pointed out the strength of network channels is open and interactive nature of information, other features play a role only under the use of information flow. Viktor Mayer-Schonberger (2012) pointed out that the storm brought about by big data is bringing the way of we live, work and think into revolution, big data opens a major transformation, and he described thinking revolution, business transformation and the change of management with three parts. Zhuang Guijun (2006) definited the concept of network marketing channels, and made a preliminary theoretical study on each step of the establishment of network marketing channels; Huang Minxue (2007) described a series of conflicts that we may encounter when we build network marketing channels, meanwhile he took corresponding theoretical research on how to coordinate and manage the construction of network marketing channels. 2 The Analysis of Relationship Between Data Mining and Consumer Behavior in Network Marketing 2.1 The docking of data mining and network marketing We should utilize techniques of data mining to analyze data about browsing, social intercourse, consumption on consumer web, and then we can provide statistics and associated mining-based feedback data including network users service quality evaluation, evaluation of marketing effectiveness, satisfaction evaluation. Network marketing is already no stranger in traditional Internet era, and the application of data mining make it rebirth in data-driven fields. 12

2.2 The analysis of relationship between data mining and consumer (AISAS) Consumer is the actions that consumers want to obtain, use, and dispose consumer goods, as well as the decision process taken before the actions. In the big data era, the feedback after purchasing should be added to al analysis, as to consumer is increasingly influenced by other consumers, AISAS is a bran-new consumer al model that aiming to the change of consumer lifestyles in the Internet age. If data mining and retail consumer can be docked and be able to maintain real-time updates, network marketing approach will change accordingly. On consumer insight and analysis of data mining is the most important areas of the retail enterprise network marketing, it will receive unprecedented value excavations, and it is mainly in the aspects of consumer's attention on retail goods, the degree of demand, degree of correlation, degree of consumption, the degree of feedback (Figure 1). Emphasis of data mining attention demand correlation consumption feedback Process of consumer Attention Interest Search Action Figure 1 The diagram of relationship between data mining and retail consumer 3 The Processes and Effects of Data Mining in Retail Business Based on the Analysis of Consumer Behavior Retail businesses can make use of techniques of data mining to identify, receive, analyze and process massive data involved in the network marketing, so it can extract valuable information which is helpful to analyze consumer to be the basis for network marketing decision (Figure 2). The arrival of the big data era has changed marketing environment, we need to establish a new consumer-driven marketing model: Share focus demand Select the data target data Analysis of consumer Analysis of customer base positioning Design of products receiving analyzing integrating applicating Choosing the right marketing model consumption feedback Figure 2 The data mining process of retail business based on consumer 3.1 A more complete description of consumer Currently, retail e-commerce sites, microblog, video sites, and social networking sites all generate billions of data. This includes features of the number of Internet users log, online time, keyword search, browsing preferences and so on, with that we can dig out customers preferences, consumer trends and distribution of consumer groups, thereby use the appropriate marketing model. 3.2 A finer consumer subdivision This feature is based on the one above. We must achieve consumer segmentation in diverse dimensionalities and truly make it personalized. For example, on top of the existing traditional market 13

research data and shopping history data, you can also track and use more data, such as clicking on a network, reviews, browsing history, etc. to better segment consumers and serve in various aspects of design about goods and marketing. 4 The New Model of Network Marketing of Retail Business in Big Data Era 4.1 The precise network marketing based on the analysis of consumer 4.1.1 The concept of precise network marketing The precise network marketing is aiming to achieve a road of low-cost expansion on the basis of the precise positioning, relying on modern information technology to build a system of personalized customer communication and service. Due to the increasingly diverse needs of consumers, the market continues to segment and the arrival rate of mass communication are getting lower, so precision marketing should transform traditional mass media into small minority and lock the target market in the most valuable customer groups. 4.1.2 The applications of precise network marketing in retail enterprises 1 Conducting precise network of retail business under the use of the Internet Community. Network users share shopping experience in microblog, forums and other social networking sites, and it will affect consumers choices and guide others. Most of the forums will be divided into different communities based on user preferences, these communities are market segments. Retail businesses can take the community as a target market whose positioning is consistent with the goods of business, so that they can make the limited marketing resources on high-value customers, and transform the asymmetric customer value into symmetric value. Meanwhile, you can understand the market trends in a timely manner, and quickly adjust the positioning of products and services. 2 Achieving precise network marketing of retail enterprises under the use of narrow informing. Narrow informing is the targeted advertising of network, which is setting advertising as required through analyzing the user s browser preferences, habits, access history and other information. Retail businesses can set keywords according to the characteristics of the products, so the promoting goods related to keywords will appear around webs as long as the network users browse the product information pages, it will make the accurate delivery of network marketing promotion come true. This new model of web promotion greatly saves network marketing costs and enhances the efficiency. 4.2 The associational recommended network marketing based on the analysis of consumer 4.2.1 The concept of associational recommended network marketing Founding rules of association through correlating analysis on data is the most potential mining in the analysis of consumer. Associational recommended network marketing is divided into two categories up-marketing and cross-marketing. Up-marketing is based on the upgrade of similar goods line or recommendation of optimized products. Cross-marketing refers to discovering various needs from customers buying, and selling related merchandises, it is based on the recommendation of similar but different types of commodities. 4.2.2 The applications of associational recommended network marketing in retail enterprises 1 Improving sales management in order to promote cross-selling. Customer s shopping baskets should be correlational analyzed, and the connotative rules among goods should be excavated, they are helpful to businesses to conduct decisions. We must make comprehensive analysis of the direct and indirect profitability of the products in order to determine the optimal product mix, as well as goods orders, reasonable inventory control. 2 Optimizing configuration of promotional merchandises achieves targeted promotions. We can know at what time, what place, in what way and to what kind of customer for promotional activities at application of data mining technology and cluster analysis, this can greatly improve the effectiveness of promotional activities. 14

4.3 The pioneering network marketing based on the analysis of consumer The pioneering network marketing is that forecasting and guiding consumer demand through analysis of massive data. Said the secretary-general Xu Dongsheng of the Chinese electrical appliances association, in the big data era, not only the application of big data analysis mode can defuse the crisis in the market, but also can help companies seize consumer demand ahead. Every users action, every words, even every expression are the data that worthy of our study. Users are data, and data is value. 4.3.1 Users generate content Consumer database is more than the database that just holds the basic consumer information; it should be transformed into consumer database in order to analyze the potential demand. The activity of Be friends with Tyrants launched in 2013 on the microblog turns the word of tyrant which is a disdain before into a commendatory one, not only it subvert the values of the consumer-oriented, but also manufacture Apple 5S s Tyrant gold effect. 4.3.2 Users generate media Manufacturing news does not just appear in the newsroom in big data era, but appear anywhere in the news site. Enterprises should stand on the living persons point to observe their lifestyles, attitudes and taste, and to study what the times are creating for them, and then how the markets release their diversity. 4.3.3 Cross-media integration Cross-media integration is a new operational mode of integration under the cross-border of international media, in short, it is the job that effectively combines the newspapers, radio, television and the Internet to derive different forms of information products, and spread them to audience through diverse platforms. It is Johnson & Johnson s brand called Hanhoo that scheme the media convergence case of advertising serial about little three wars wife at August 2013, it lead the controversial paper media content to social media, and create an atmosphere by engage in a practice topic, meanwhile it broadcast television media advertising to attract consumers and even the media s attention. 5 Conclusions In the big data era, not only continuous improvement of information technology has brought huge amounts of data for the retail industry, but also make it possible for the effective application of data. The huge potential of the Internet economy bring marketing into the era of network marketing, and network marketing architectures on the basis of data, finally turn the capabilities of data mining, processing and analysis into business value. Retail industry must change its traditional product strategy, pricing strategy, distribution strategy and marketing strategy, so that it can transform the traditional marketing model into a precise marketing model. Data mining technology should be applied in the formulation of marketing strategy to deeply excavate the value of market information and rationally allocate the marketing resources, then we can reduce marketing costs, improve marketing ROI, achieve intelligent marketing, and enhance customers value, satisfaction and loyalty, so there is no need to struggle in disorderly commodity fight and price competition, so that we can really build the core competitiveness of the retail industry. Acknowledgement: This paper is subsidized by the Beijing Municipal Education Commission Business and Enterprise Service Innovation Research (science and technology innovation platform, 0351407800). References [1]. Viktor Mayer-Schonberger. Big Data: A Revolution That Will Transform how we Live, Work, and Think. Zhejiang People s Publishing House. 2012, 12: 167-173 [2]. Peter S.H. Leeflang, Peter C. Verhoef. Challenges and Solutions for Marketing in a Digital Era, 15

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