Design And Implementation Of A Data Analysis And Decision Support System For Cross-Selling In Retail Cosmetic Industry

As the Chinese market is opening to world, more and more multi-national retail cosmetics companies have been setting up their sub-companies or offices in China in order to gain more benefits from China market. However, along with Chinese cosmetics market being mature, each company is confronted with the embarrassment to be difficult to sell products like before; due to market competition being dramatically, it's more and more difficult for those companies keep their market share by traditional selling-pattern, nor capture more.In the situation, the trade marketing and sales staffs in those cosmetics companies constantly try to look for new marketing move or new technique to escape from this bad situation to capture more market share as soon as possible. The cross-selling is one of important and modern marketing move these days, especially proven to be successful in banking and securities industry. However, it is fresh to the retail industry. The easiest way to realize the cross-selling is to find the knowledge and the common and regular customers purchasing behaviors from the history transaction data which are sleeping in the transaction database that will help them gain the new benefit. As the retail system has been deployed in the counters at the same time, lots of transaction and customer data have been collected onto the company's retail system. However, they are just sleeping in the database but not to be used by users effectively. The mode that looks for knowledge and regular rules from history sales transaction data is bringing to retail industry to a new era in these years because data analysis and decision support techniques are becoming more mature. So, the managers of those companies are strongly interested in the data analysis and decision support system. The charter 1 of the paper bases on the features of retail cosmetic industry to introduce the background and purpose to build data analysis and decision support system for cross-selling in the retail cosmetic industry from the point of the background of the retail industry, this paper's purpose, and global and local review on research status. The charter 2 describes the modules and techniques to build the system that are data warehouse, OLAP, and data mining. In 3rd charter, it describes how to design the data warehouse of data analysis and decision support system for retail cosmetic industry with the cross-selling subject in the enterprise; meanwhile, either describes the key attributions of data warehouse such as the dimension table and measure table around the cross-selling subject. The following chart 4 and 5 show 2 kinds of data mining ways to realize cross-selling that are association mining and decision tree mining, and the concrete arithmetic that are the Microsoft Association arithmetic and Decision Tree arithmetic. The chart 6 shows the detailed approaches and steps to setup the data analysis and decision support system for cross-selling in the retail cosmetics company with the Microsoft SQL Server 2005, EXCEL2007, DBPut etc. modern information tools and techniques step by step. The system is helping company escape from the heavy manual analysis work, gets much knowledge and information from the sleeping transaction data, and makes it get more chances in the dramatic commercial war and gain more market share.