| Summary: | 碩士 === 中國文化大學 === 資訊管理研究所碩士在職專班 === 94 === In the era of great competition, the way in which companies interact with their cus-tomers have changed dramatically over the past few years. A customer's continuing business is no longer guaranteed. As a result, companies have found that they need to understand their target customers better and to quickly respond to their wants and needs. Value in companies’ mind constituted only one thing - how much the customer is will-ing to pay for the product. "What is our business is not determined by the producer but by the consumer," wrote Drucker in 1954.
Few rules are more widely quoted in marketing today than the 80/20 Rule, which states that 80% of your sales come from just 20% of your customer base. In this age of relationship marketing, this rule has become an often-heard battle cry to focus our ef-forts on maintaining the loyalty of customers belonging to the golden 20% that drive most of our business, while spending less effort on the trivial other 80%. Thus, it is very important to identify the customer(s) for your product or service and determine what they consider important; and examine how an organization determines requirements, expectations and preferences of customers and markets, and how the organization builds relationships with customers and determines the key factors that lead to customer acqui-sition, satisfaction, retention and to business expansion.
This study will modify the RFM Model (Hughes, 1994) for developing a conceptual frame work to analyze the customer preferences and behaviors in a retailer market. In addition, this study will find out the association rules with SOM(Kohonen,1982) and data mining for understanding the consuming behavior and profit contribution. As we know that the price and sales volume that impact directly upon sales revenues and prof-itability. What the customers really wants provides a business and technological over-view of data mining and outlines how, along with sound business processes and com-plementary technologies, data mining can reinforce and redefine customer relationships. From this experiment, we can find out who are our best and / or most loyal customers. Furthermore, it can help a company objectively identify, profile, model, select, promote and track "Loyal" and "Best" customers.
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