یکپارچه سازی فن آوری های داده کاوی بمنظور تجزیه و تحلیل ارزش مشتری برای صنعت تعمیر و نگهداری خودرو
|کد مقاله||سال انتشار||تعداد صفحات مقاله انگلیسی||ترجمه فارسی|
|2593||2010||8 صفحه PDF||سفارش دهید|
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Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Expert Systems with Applications, Volume 37, Issue 12, December 2010, Pages 7489–7496
Customer value refers to the potential contribution of customers to an enterprise during specific periods. When enterprises understand the value of customers, enterprises that understand customer value can provide customized service to different customers and thus achieve effective customer relationship management. This study focuses on the current automotive maintenance industry in Taiwan and systematically integrates numerous data mining technologies to analyze customer value and thus promote customer value. This investigation first applies the K-means and SOM methods to establish a customer value analysis model for analyzing customer value. By the results of the two methods, the customers are divided into high, middle and low value groups. Moreover, further analysis is conducted for clustering variables using the LSD and Turkey HSD tests. Subsequently, decision tree theory is utilized to mine the characteristics of each customer segment. Third, this study develops different strategies for customers with different values and thus promoted customer value. The analytical results in this study can provide a valuable reference with regard to customer relationship management for managers in the automotive maintenance industry.
Customer relationship management (CRM) denotes that managerial efforts to business processes and technologies that designed to understand the customers of a firm (Kim, Suh, & Hwang, 2003). Successful CRM requires enterprises to interact flexibly with their customers (Edelstein, 2000). Enterprises that succeed in correctly assessing customer value can offer customized services to diverse customers, perform effective customer relationship management and, simultaneously, also increase enterprise revenues (Berson, Smith, Smith, & Thearling, 2000). Customer value indicates the potential contribution of customers to an enterprise during specific periods. The core of CRM activities primarily involves understanding customer profitability and retaining profitable customers (Hawkes, 2000). Numerous enterprises start to measure customer value and utilize this information in management to retain customers and maximize their profit potential (Hawkes, 2000, Kim et al., 2006 and Verhoef and Donkers, 2001). Enterprises utilize market segmentation to identify customer segments that are most interested particular goods and services, and to concentrate their resources on the most efficient and effective ways (Jang, Morrison, & O’Leary, 2002). Restated, enterprises can help homogenous smaller customer cluster with similar customer value via market segmentation and thus efficiently focus their efforts, identify opportunities and develop products and services strategies in a tailor-made manner (Jang et al., 2002). Therefore, enterprises are required to evaluate the value of their customers, segment customers based on customer value and develop strategies for every customer segment to acquire and retain profitable customers.
نتیجه گیری انگلیسی
This study reaches the following conclusions: 1. Customer management: This study offer businesses a simple, effective and logical approach for obtaining accurate information regarding potential customers and assessing the value of existing customers. From the perspective of customer management, such an approach can not only assist in crisis management but also can help promote customer value and enable significant savings in customer service by enabling the utilization of data mining for automotive maintenance industry. 2. Customer value analysis model for automotive maintenance industry: This study proposes a model for customer value analysis, and adopted the K-means and SOM approaches to build the model and discover that the K-means method is superior to the SOM method when applied to the current sample factory. Notably, M and F variables are better than R variable in clustering through LSD and Turkey HSD tests. 3. The major customer value characteristics: This study employs decision tree theory to elucidate the essential characteristics for efficiently identifying the high value, medium value and low value customers. Enterprises can focus on and are on the alert for potential customers through the characteristics and therefore implement the following marketing management strategy for various value customers. According to the decision tree analysis theory result, M is the most important norm to forecast the customer value. 4. Moreover, the proposed approach advocated that the sample factory should conduct a market survey and segment marketing to develop a market strategy for dealing with customer consumption characteristics and psychological needs, in order to achieve a large profit while minimizing marketing costs.