傳統上透過行銷研究，如設計問卷透過市場調查、問卷調查等等活動來取得消費者資訊，但在資訊化的時代，利用POS系統所收集到且存在於資料庫中的銷售資料，忠實紀錄所有消費者的消費行為，其中亦隱含著消費者對品牌忠誠度、產品偏好性、價格敏感度等等消費行為。藉由著這些基礎，可進一步探索顧客輪廓(Customer Profile)、顧客忠誠度(Customer Loyalty)及顧客保留率(Customer Retention)，同時預測未來各種行銷活動的可能結果；進而擴大其應用範圍，進行新客源、新產品的開發工作。本研究以資料庫行銷、資料探勘等等理論基礎、統計學技術等等方法，以居家用品業為例，進行資料庫行銷(Database Marketing)的實證工作。實證資料來源為「生活工場」連鎖居家用品店現有之基本資料。並以此資料為基礎，探究顧客購買的消費特性，並以其類別、系列分析其產品關聯性審視其產品組合類別。另外一方面，利用資料庫中的銷售資料及VIP基本資料，以RFM(Recency, Frequency, Monetary)顧客分群方法，分離出不同的顧客族群，並在每一個族群中作交差比對(Cross-Checking)，探究各族群的顧客輪廓及其消費特徵。利用門市基本資料、銷售明細資料等，分析出地域消費特徵。最後，再以金卡、貴賓卡、生活卡三大族群的消費特性及與RFM族群之交差比對，並計算出不同卡別的顧客終身價值(Customer Lifetime Value, CLV)，以期提供「生活工場」與國內連鎖零售體系之產業，未來在對顧客關係經營之參考。 / 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.
| Identifer | oai:union.ndltd.org:CHENGCHI/G0090932616 |
| Creators | 吳林興 |
| Publisher | 國立政治大學 |
| Source Sets | National Chengchi University Libraries |
| Language | 中文 |
| Detected Language | English |
| Type | text |
| Rights | Copyright © nccu library on behalf of the copyright holders |
Page generated in 0.1203 seconds