消費者消費行為研究-以生活工場為例

碩士 === 國立政治大學 === 經營管理碩士學程 === 93 === In tradition, marketing research acquires the information of consumers through questionnaire design, marketing survey, etc. However, in the information age, the POS system is capable to collect the sales information and record them in the data base. It precisely...

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Bibliographic Details
Main Author: 吳林興
Other Authors: 周宣光
Format: Others
Language:zh-TW
Published: 2005
Online Access:http://ndltd.ncl.edu.tw/handle/60251818022989635700
Description
Summary:碩士 === 國立政治大學 === 經營管理碩士學程 === 93 === In tradition, marketing research acquires the information of consumers through questionnaire design, marketing survey, etc. However, in the information age, the POS system is capable to collect the sales information and record them in the data base. It precisely records the consumer behaviors which include the brand loyalty, product preference and price sensitivity. Based on the information, it could more deeply discover the customer profile, customer loyalty and customer retention. It can also forecast the possibility of marketing event for the future and expand to other applications such as new customer creation and new product development. This research, based on the theory of database marketing, data mining methodology and statistic technology, substantiates database marketing in a case study of a home center. Actual data are provided by Working House, a home center chain store. Those data bases establish a foundation of exploring the consumer purchasing characteristic, analyzing series of product classifications and examining the product association and combination. On the other hand, based on the sales information and VIP database, RFM (Recency, Frequency, and Monetary) is utilized to cluster customer segments and research the customer profiling and shopping characteristic by cross checking each shopping group. Data from store locations and sales information are thus employed to explore the geographic characteristic of shoppers. In conclusion, based on the usage data of Gold Card, VIP Card, and Working House Card and cross checks with RFM clustering groups, the Customer Lifetime Value (CLV) of each card will be calculated and accumulated to provide Working House and other retailers the reference for managing customer relationship in the future.