Study On The Marketing Decision Model Based On The Supermarket Scanner Data

The development of the modern information technology with computer, network and communication as core, on the one side accelerate the transformation of the economy so much as the whole society, on the other side bring about the fire-new challenge. The crucial problem is how to rapidly and accurately find the available information from a great deal of data which look like irrelative but actually correlative with the topic. Because of its powerful function, the data-digging in which data base, statistics, artificial intelligence and other theory and technology is applied, is more and more popular in the business management, government office, science research and engineering exploitation etc. Since the spread of the story of "Diaper and Beer", more and more people are convinced of the tremendous potential value of the supermarket scanner data. With the extensive application of the POS in retailing, how to make use of the data-digging technology, how to exert the support use of the supermarket scanner data on the marketing decision-making, and how to innovate the pattern of the marketing decision-making, have become the hot topic in both computer and marketing area. Adopting the pattern of the marketing decision-making based on supermarket scanner data, people adequately find the information with latent value from the data of the POS by data-digging, and make use of the known market law and data resources, avoid the personal error of the "flap-head", and make the decision more scientific, impersonal and effective, also find some problems which are not realized by decision-makers in everyday, but have a remarkable effect on supermarket marketing. Nowadays, many national and oversea retail enterprises including Wal*Mart are exploring how to make use of the supermarket scanner data effectively. But most of the existing supermarket data base consists of EDI and some simple data statistic software, in fact they are not the real supermarket data base. Under most circumstances, scanner data are only used in data exchange by supplier. Therefore, it is not the real data-digging, and it also has not support the data resources for marketing decision-making. In this article, the author perfectly combine the data-digging technology with the supermarket marketing decision-making, discuss the efficiency and availability of using scanner data on marketing decision-making, then put forward a new impersonal and effective decision-making pattern of marketing. In the course of the decision making concerning the commodities in the supermarket, we can get the answer about the introducing and taking-out of the good or bad production, display position and numbers of production, and the price-making of the production from the scanner data. When we assess the quality by means of category management, we must adequately consider the expansibility, frivolousness, productiveness of the commodity in the first, and persist in the fundamental standard of the importance of production, then we are able to make the quality arrangement of commodities accord with practicality of the supermarket. Usually, by means of the information of distribution quantities, distribution price, and stock cost etc. of each sort of article in the scanner data, we can figure out the distribution quantities, profit margin, profit quantities and market posses ratio etc. then, according to the facts of the supermarket, we can work out the degree of importance of each sort of article. After summing up the past distribution data, if the importance degree of one sort article is under the determinate numerical valued, it is considered to be not fit to sell in this supermarket, and should be eliminated from the supermarket. On the contrary, the article with high degree of importance should be highly regarded, displayed in the "Gold Position", and occupy large area. Moreover, in terms of the ever distribution and text data, we can analyze which sort the given article belongs to, and confirm the appropriate. In the course of delivering cargo, according to analyzing the ever distribution data, we can scientifically foresee the future distribution quantities, and accurately ascertain the time, amount and breed of ordering goods. Especially, the EDI system can ensure the daily exchange of the scanner data; make the work of the ordering goods in fixed formality and mode. It not only can decrease the buyers'workdifficulty and time, but also can increase the work efficiency, decrease work cost, avoid loss because of OOS(out of stock) or overstock. During the process of supermarket's customers'relationship management, by analyzing the distribution data and the saved clients'data, we can find golden customers by classifying all the customers into different types. Added with the method of, we can reasonably conclude the characteristics of the golden customers and adapt those marketing plans in accordance with their habits in consumption. In this way, we can attract those potential customers sharing the common characteristics with the golden customers. In addition, we can know their appetite by analyzing the saved clients'data and apply different marketing plans. By this means, we can make the marketing plans more effective and give the clients the feeling of being much more valued to make them more faithful (to our supermarket.) The marketing-decision-making model based on the supermarkets'scanner data is one depending on the newer information-management system in which the data-tapping technology is applied. By saving the scanner data and the text data on the marketing and market survey to the data base and supported by the information base and the model base, it can get the supporting data helpful to the scientific and precise decision through data-tapping. New feedback data and experience summary during and after the implementing the decision will go to the information base of the data base for the next decision-making. Compared with the traditional decision-making model, the marketing-decision-making model based on the supermarkets'scanner data is distinguished by its reversibility, which emphasizes the experience from the previous decision process to the extent as new knowledge which is fed back to the he information base of the supermarkets'data base to be helpful to the next decision-making process. In demonstration study, the author gives an example of pure fresh milk in Yatai supermarket. According to a lot of scanner data, the author make the analysis of the category management for each sort of article, then get the importance degree of each brand of article. On basis of this estimation, I analyze the quality of the...