2770.CRM系統(tǒng)中商業(yè)智能模塊的設計與開發(fā) 外文翻譯

1、外 文 翻 譯畢業(yè)設計題目： crm系統(tǒng)中商業(yè)智能模塊的設計與開發(fā) 原文1：a model of customer relationship management and businessintelligence systems for catalogue and online retailers 譯文1：客戶關系管理和商業(yè)智能系統(tǒng)在商品目錄和在線零售商中的應用模型 原文2：intelligent profitable customers segmentation system based on business intelligence tools 譯文2：基于商業(yè)智能工具的智能盈利客戶細分

2、系統(tǒng) a model of customer relationship management and business intelligence systems for catalogue and online retailersas more retailers evolve into customer-centric and segment-based business, business intelligence (bi) and customer relationship management (crm) systems are playing a key role in achiev

3、ing and maintaining competitive advantage. for the past ten years, the authors have had the rare opportunity of observing and interviewing employees and managers of three different management teams at three separate fingerhut companies as they experimented with various its for their companies. when

4、the first fingerhut company peaked in 1998, as many as 200 analysts and 40 statisticians mined the database for insights that helped predict consumer shopping patterns and credit behavior. data mining and bi helped fingerhut spot shopping patterns, bring product offerings to the right customers, and

5、 nurture customer relationships. by 1998, fingerhut was the second largest catalogue retailer in the u.s. with revenues nearing $2 billion. however, after federated acquired fingerhut in 1999 and made it a subsidiary, fingerhut net, it suffered great losses and was eventually liquidated. finally, a

6、new company, fingerhut direct marketing, was resurrected in 2002 under a new management team, and it once again became successful. what went right? what went wrong? the paper concludes with crm and bi systems success factors and a discussion of lessons learned.1. introductionthe use of it has create

7、d new ways for firms to exploit vast potentials of customer relationships that have never been exploited before. with growing competition from both traditional and online businesses, keeping customers satisfied, increasing potential sales, and maintaining customer loyalty become strategically import

8、ant to business success. to improve and exploit customer relationships, business intelligence (bi) tools are used to assist crm systems focus on decision support, market research, target marketing, customer service, and customer collaboration in products and services.despite numerous crm studies, ve

9、ry little effort has been made in incorporating consumer preferences for customer satisfaction and relationships. wang and head 10 report that most research on consumer behavior addresses the acquisition stage, while research in the retention stage is still in its infancy. this paper deals with this

10、 paucity of research, and presents case studies on the success and failure of customer relationships and business potential sales, and maintaining customer loyalty become strategically important to business success. to improve and exploit customer relationships, business intelligence (bi) tools are

11、used to assist crm systems focus on decision support, market research, target marketing, intelligence. the paper identies strategies and the successes and failures at fingerhut inc, the second largest catalogue mail order company in the u.s. in 1999, and addresses the following questions:1.what are

12、the impacts of price discrimination on customer relationships?2.what are the impacts of crm and/or bi systems on catalogue and online retailing businesses?3.what are the impacts of high switching costs and/or lock-in strategies on customer relationships?4.what is a successful outcome model for catal

13、ogue and online businesses?6. lessons learned, insights, and success factorsas e-commerce evolves, new visions and paradigms emerge. how do conventional management strategies and processes compare with the experience gained from the successes and failures at fingerhut? and how do conventional manage

14、ment strategies and processes compare with the experience gained from the crm successes and failures at fingerhut? the lessons learned were:1. the use of bi and crm at fingerhut reduces the threats of price and cost transparency and disintermediation. early e-commerce visions predicted that price an

15、d cost transparency would cause customers to move to retailers who offered lowest prices, and that direct sales would eliminate intermediaries. with innovation in olap and dm, fingerhut was able to lock-in customers in the sub-prime market, predict buyer patterns, and maintain customers trust and lo

16、yalty. dm also allowed fingerhut to focus its efforts on nurturing buyer behaviors. this was a winwin strategy which resulted in customer satisfaction and trust while bringing more profits to fingerhut.2. high switching costs do not hurt customer satisfaction. because fingerhut tailored its products

17、 and credit services to its customers, customer satisfaction level and loyalty was high. it was only after federated extended credit beyond customers ability to pay that customers became dissatisfied. as we have seen in the credit market recently, sub-prime mortgage lenders who offer credit beyond c

18、ustomers ability to pay also suffer failure.3. price discrimination among sales channels hurt customer relationships when lock-in and high switching costs are removed. after federated gave former fingerhut customers credit cards, they shopped elsewhere for lower prices.4. success in the catalogue ma

19、il order business does not guarantee success in online e-commerce. pundits predicted that it would be easy for catalogue mail order companies to move into online retailing because they operated without physical stores. however, having past experience in order fulfillment and in running businesses wi

20、thout physical stores does not automatically translate into success in online business.作者：dien d. phan，doug vogel國籍：usa出處：information & management，2009，9：1-9.客戶關系管理和商業(yè)智能系統(tǒng)在商品目錄和在線零售商中的應用模型摘要：隨著越來越多的零售商發(fā)展以客戶為中心和以細分為基礎的商業(yè)，商業(yè)智能（bi）和客戶關系管理（crm）系統(tǒng)在實現(xiàn)和保持競爭優(yōu)勢中正發(fā)揮著關鍵作用。在過去的十年中，作者曾難得的機會觀察和采訪了三個不同在線家居購物公司的員工和

21、三個不同的管理團隊經(jīng)理，因為他們?yōu)樽约旱墓驹囼炛鞣N智能交通系統(tǒng)。當?shù)谝粋€芬格公司在1998年達到高峰時，有多達200名分析師和40統(tǒng)計人員采集數(shù)據(jù)庫的數(shù)據(jù)，這樣有助于預測消費者行為模式和信貸行為。數(shù)據(jù)挖掘和商業(yè)智能幫助芬格發(fā)現(xiàn)購物模式，使產(chǎn)品到正確的客戶手里，培養(yǎng)客戶關系。到1998年，在線家居購物已經(jīng)是美國第二大商品目錄零售商，收入接近20億美元。然而，聯(lián)邦于1999年收購在線家居購物并使其成為一個子公司，名叫在線家居購物網(wǎng)。但在線家居購物遭受了重大損失，并最終被清算。最后，一家名為在線家居購物直銷的新公司在新的管理團隊帶領下誕生于2002年，并再次取得了成功。哪里是對的？哪里出了問題？

22、本文總結了客戶關系管理和商業(yè)智能系統(tǒng)的成功因素并吸取了經(jīng)驗教訓。1、引言企業(yè)利用信息技術創(chuàng)造了新的途經(jīng)來利用擁有巨大潛力的客戶關系，這在以前是從來沒有被利用過的。隨著傳統(tǒng)業(yè)務和在線業(yè)務競爭的越來越激烈，讓顧客滿意，增加潛在的銷售，維護客戶忠誠度成為商業(yè)成功中重要的戰(zhàn)略意義。在改善和利用客戶關系中，商業(yè)智能（bi）工具主要在決策支持，市場調研，目標市場營銷，客戶服務，產(chǎn)品和服務上的客戶合作上面幫助客戶關系管理系統(tǒng)。盡管有關客戶關系管理的研究有很多，但很少有把消費者的喜好包含進客戶滿意度和客戶關系中。王和海德的報告主要是研究當保留期的研究仍處于初級階段時，用消費者行為解決大部分收購階段。本文解決了

23、這方面的不足，并提出了客戶關系和商業(yè)智能中成功和失敗的例子。本文論述了在1999年時作為美國第二大商業(yè)目錄郵購公司的在線家居購物公司的戰(zhàn)略決策、成功和失敗，并解決以下問題： 1、客戶關系中價格歧視會產(chǎn)生什么影響？ 2、商業(yè)目錄和網(wǎng)上零售業(yè)務中應用客戶關系管理和/或商業(yè)智能會產(chǎn)生什么影響？ 3、客戶關系中應用高轉換成本和/或固定的戰(zhàn)略決策會產(chǎn)生什么影響？4、商業(yè)目錄和在線業(yè)務的一個成功的最終模型是什么？6 經(jīng)驗教訓，見解和成功的因素隨著電子商務的發(fā)展，新的視野和范例出現(xiàn)了。如何將傳統(tǒng)的管理戰(zhàn)略和流程與在線家居購物所獲取的成功和失敗的經(jīng)驗相比較？以及如何將傳統(tǒng)的管理戰(zhàn)略和流程與在線家居購物從客戶關

24、系管理中獲得的成功和失敗的經(jīng)驗相比較？以下是所吸取的教訓：1商業(yè)智能和客戶關系管理的應用，使在線家居購物減少了來自于價格、成本透明度和中介的威脅。早期的電子商務夢想通過增加價格和成本的透明度，使消費者轉向提供最低價格的零售商，而且直銷將消除經(jīng)銷商這一環(huán)節(jié)。隨著聯(lián)機分析處理和快訊商品廣告的發(fā)展，在線家居購物能夠抓住次級市場的顧客，預測買方格局，以及維護客戶的信任和忠誠。快訊商品廣告也促使在線家居購物把努力集中在重點培育買方行為。這是一個雙贏的戰(zhàn)略，因為在獲得客戶滿意度和信任的同時，給在線家居購物帶來更多的利潤。2高轉換成本不會傷害客戶滿意度。由于在線家居購物向顧客提供產(chǎn)品定制和信貸服務，所以它的

25、客戶滿意度和忠誠度都很高。只是后來聯(lián)邦擴大信貸業(yè)務，超出了客戶的支付能力，從而導致客戶的不滿。正如我們現(xiàn)在看到的信貸市場，那些次級按揭貸款的提供信貸也遭受了損失，因為他們提供的信貸業(yè)務超出了客戶的支付能力。3當鎖定和高轉換成本被取消時，銷售渠道之間的價格歧視會傷害客戶關系。所以在聯(lián)邦把信用卡發(fā)放給在線家居購物以前的顧客后，他們卻去了其他能提供更低價格的地方購物。4.商業(yè)目錄郵購業(yè)務的成功并不能保證在線電子商務的成功。專家預言，商業(yè)目錄郵購公司進軍網(wǎng)上零售是很容易的，因為他們沒有經(jīng)營實體商店。不過，沒有實體商店而擁有履行訂單和企業(yè)經(jīng)營經(jīng)驗的企業(yè)并不會自動轉化為成功的網(wǎng)上業(yè)務。作者：dien d.

26、 phan，doug vogel國籍：usa出處：information & management，2009，9：1-9.intelligent profitable customers segmentation system based on business intelligence toolsabstractfor the success of crm, it is important to target the most profitable customers of a company. many crm researches have been performed to calcu

27、late customer profitability and develop a comprehensive model of it. most of them, however, had some limitations and accordingly the customer segmentation based on the customer profitability model is still underutilized. this paper aims at providing an easy, efficient and more practical alternative

28、approach based on the customer satisfaction survey for the profitable customers segmentation. we present a multiagent-based system, called the survey-based profitable customers segmentation system that executes the customer satisfaction survey and conducts the mining of customer satisfaction survey,

29、 socio-demographic and accounting database through the integrated uses of business intelligence tools such as dea (data envelopment analysis), self-organizing map (som) neural network and c4.5 for the profitable customers segmentation. a case study on a motor companys profitable customer segmentatio

30、n is illustrated.2. profitable customer segmentation and customer satisfaction surveytraditional customer segmentation models were based on demographic, attitudinal, and psychographic attributes of a customer (griffin, 2003). they gave too simple results and poor accuracy for todays complicated busi

31、ness environment. recently, the customer segmentation based on customer transactional and behavioral data (e.g. purchases type, volume and history, call center complaints, claims, web activity data,etc.) collected by various information systems is commonly used. however, the customer segmentation ba

32、sed on his/her profitability to a company is still underutilized.customer profitability is a customer-level measure that refers to the revenues less the costs which one particular customer generates over a given period of time and has been studied the name of customer value, customer lifetime value,

33、 ltv and customer equity. many customer profitability researches focused on the future cash flow derived from the past profit contribution and did not considered the change of profit contribution resulted from the customer defection (berger & nasr, 1998; gupta & lehmann, 2003).hwang, jung, and suh (

34、2004) suggested a new customer profitability model considering past profit contribution, potential benefit indicated cross-selling and up-selling opportunity, and defection probability of a customer measured customer loyalty and segmented customers based on their model. however, they said that it ha

35、d some limitations such as not considering the reactivation possibility of customers, attracting/servicing cost and causes of customer defection. it is difficult and complicated to develop an effective and exact customer profitability model and segment profitable customers based on that model. in th

36、is study, we provide an easy, efficient and more practical alternative approach through the customer satisfaction survey for the profitable customers segmentation instead of using that model. the typical customer satisfaction survey collects data on the causal context of satisfaction, i.e. anteceden

37、ts (e.g. perceived performance of various product attributes/service) and consequences (e.g. overall satisfaction level, repurchase intentions and word-of-mouth intentions). according to the satisfaction-profit chain principle (anderson & mittal, 2000), improving product and service attributes cause

38、s increased customer satisfaction, increased customer satisfaction leads to greater customer retention and improving customer retention greater profitability.empirical researches have shown that increasing overall satisfaction leads to greater repurchase intentions, as well as to actual repurchase b

39、ehavior and companies with high customer satisfaction and retention can expect higher profits (reichheld & frederick, 1996).in this study, we use the customers overall satisfaction level, repurchase intentions, word-of-mouth intentions obtained from the customer satisfaction survey and his/her profi

40、t/loss to a company derived from the accounting database of it for the first step of profitable customers segmentation.3. profitable customers segmentation based on customer satisfaction surveywe propose a survey-based profitable customers segmentation system (spcss) based on data mining and agent t

41、echnology that designs, executes (on-line, e-mail, etc.) customer satisfaction survey and conducts predefined mining processes for the profitable customers segmentation. spcss has a multi-agent based architecture and the integration of predefined mining processes into decision support system framewo

42、rk . there are three types of intelligent agents within the spcss architecture: survey management (sm) agent with survey knowledge base that provides system co-ordination, facilitates (mined) knowledge communication, and takes the charge of design and execution of customer satisfaction survey, profi

43、table customers segmentation (pcs) agent that segments profitable customers among all the surveyed customers through the mining of integrated data from the customer satisfaction survey and accounting database and decides the priority order for each non-profitable customer according to the size of po

44、ssibility that he/she is converted to profitable one through the mining of integrated data from the customer satisfaction survey and customer database, and user assistant agent that acts as the intelligent interface agent between the user (e.g. the engineer of customer satisfaction center) and the s

45、pcss.作者：jang hee lee, sang chan park國籍：south korea出處：expert systems with applications ，2005，29 ：145152.基于商業(yè)智能工具的智能盈利客戶細分系統(tǒng)摘要客戶關系管理的成功，很重要的就是為公司尋找盈利客戶。許多客戶關系管理的研究已經(jīng)進行客戶盈利能力的計算，并為它開發(fā)了一個全面的模型。盡管如此，他們大多有一定的局限性，基于客戶盈利能力模型的相應客戶細分仍未得到充分利用。本文旨在提供一種簡單，有效和更務實的替代方法，它是基于盈利客戶細分后的客戶滿意度調查。我們提出了一個基于多方代理的系統(tǒng)，名為基于調查后的盈利客戶細分系統(tǒng)，用來實施客戶滿意度調查，管理客戶滿意度調查的收集，社會人口統(tǒng)