資料庫行銷之應用--以百貨業為例

The Application of Database Marketing in Retailing Industry

廖怡芳(Yi-Fang Liao)

指導教授 ： 任立中

國立臺灣大學/管理學院/國際企業學研究所/碩士(2004年)

https://doi.org/10.6342/NTU.2004.01464

摘要

商品種類繁雜、顧客眾多是百貨公司產業特性，也由於這樣的產業特性，使得百貨公司業者很難一對一的與顧客溝通，真正了解每位顧客的需求，並滿足之。現今大多數的百貨公司多採用傳統的顧客關係管理方式，並以價格做為吸引顧客主要因素。此種方式並沒有考慮到消費者之間所存在的異質性，對所有顧客都採用相同的促銷手法，並沒有嘗試去了解顧客內心真正的需求及其偏好結構。

本研究嘗試將資料庫行銷運用於百貨公司的的業態中，以顧客過去的購買紀錄及其基本資料，來進行多種不同的分析，希望能為該業者規劃出合適的資料庫行銷模式，幫助業者與消費進行一對一的溝通，提升行銷方案的效益並改善其賣場的櫃位規劃，使每位顧客都能發揮其最大效益並獲得最大滿足。

本研究進行的分析共有三大項，顧客購買行為分析、專櫃關聯性分析及專櫃推薦系統。在顧客購買行為分析的部分，我們利用多種不同的分析方式包括購買日期特性分析、平均購買期間分析、顧客活躍性及價值分析、顧客平均單日消費專櫃數分析希望能藉此找出每位顧客的輪廓，了解其獨特的購買行為特性，並輔以人口統計變數的資料，以更具體的形式來呈現分析的結果。

在專櫃關聯性分析中包括顧客併買分析，可以協助業者進行交叉銷售(Cross-Selling)；二是顧客回購分析，幫助業者進行持續性銷售(Continuous-Selling)及向上銷售(Up-Selling)。

專櫃推薦系統，依顧客過去的購買組合，找出個人對各種專櫃屬性的偏好係數，進而以預估之總購買金額來衡量對各專櫃之整體評價。業者可依此分析結果，產生特定專櫃之推薦名單，更有效率的進行折價卷之發行及其他促銷組合之規劃。

關鍵字

資料庫行銷 ； 百貨業

並列摘要

Retailing is an industry involves in facing numerous customers and selling plenty of products in different categories. Such trait made companies in this industry hard to communicate with their customer individually. As a result, department stores often neglected the heterogeneity between customers, and provided them with the same kind of services and similar promotion plans, where sales promotion is most common used to attract customers. However, these activities lack of uniqueness and easily imitated, hence, difficult to establish a sustainable competitive advantage.

The main purpose of this research is to help the company establish a better understanding of its customers, comprehend the heterogeneity of each one, then serve the customers with services and marketing activities according to their specific needs. However, identifying each of their needs is not easy to obtain, especially in this industry. Therefore, we use customers’ pass transaction data and utilize database marketing techniques to find out the purchasing pattern of each customer. The result of this research will help company to do their promotion more efficiently and increase the customer satisfaction and loyalty.

The three main analyses of this research are as follow, and each of them has its own strategic suggestions:

I. Customer purchasing behavior analysis
Identify the specific characteristics of customer purchasing behavior, and implement different ways to increase the value of each one.
II. Shop counter assortment analysis
The result will help the company to improve the counter exhibition and traffic design as well as implement of cross-selling and up-selling.
III. Shop counter recommendation system
Produce the recommendation list based on the characteristics of each counter and customer; help the company give individual sales suggestions to customer and enlarge efficiency.

並列關鍵字

Database Marketing ； Retailing Industry

參考文獻

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