ABSTRACT The introduction of data mining methods in the banking area due to the nature and sensitivity of bank data, can already be considered of great assistance to banks as to prediction, forecasting and decision support. Concerning decision making, it is very important a bank to have the knowledge of (a) customer profitability and their grouping according to this parameter and (b) association rules between products and services it offers in order to more sufficiently support its decisions. Object of this paper is to demonstrate that keeping track of customer groups according to their profitability and discovery of association rules between products and services it offers to those groups, is of major importance as to its decision support.

Abstract-CRM, or Customer Relationship Management, is a company-wide business strategy designed to reduce costs and increase profitability by solidifying customer satisfaction, loyalty, and advocacy. True CRM brings together information from all data sources within an organization (and where appropriate, from outside the organization) to give one, holistic view of each customer in real time. This allows customer facing employees in such areas as sales, customer support, and marketing to make quick yet informed decisions on everything from cross-selling and up selling opportunities to target marketing strategies to competitive positioning tactics.

The objective of the study is to examine how response data from direct marketing email campaigns could be utilized in measuring the development of a customer relationship in the context of an end-user loyalty program. The case analysed in the study is Club Sony Ericsson e-mail campaigns targeted at its registered members. The primary research problem covered in the study is “how can e-mail direct marketing results be measured by using Club Sony Ericsson existing campaign response and customer data? ” In order to gain understanding of the role of e-mail direct marketing campaigns in a loyalty program, a framework is created around the concept of customer relationship. As a form of interactive marketing, e-mail direct marketing contributes to relationship development by providing a channel for dialogue that consists of both communication as well as interaction. The empirical study is conducted by using a quantitative research method. Data analysis is performed in ways that could also be applied in ongoing monitoring of relationship development within the case company. The study focus is on the information that click-through data can provide when combined with variables found from the customer database. The study is conducted based on individual level secondary data available on recent Club Sony Ericsson e-mail campaigns, collected from campaign report files and Club Sony Ericsson member database. Click-through activity was found to have positive correlation with all the other behavioral variables available on

Abstract: The introduction of data mining methods in the banking area due to the nature and sensitivity of bank data can already be considered of great assistance to banks as to prediction, forecasting and decision support. Concerning decision making, it is very important a bank to have the knowledge of (a) customer profitability and customers ’ grouping according to this parameter and (b) association rules between products and services it offers in order to more sufficiently support its decisions. Object of this paper is to demonstrate that keeping track of customer groups according to their profitability and discovery of association rules between products and services is of major importance as to its decision support.

Abstract: RFM (Recency, Frequency, Monetary) analysis is a method to identify high-response customers in marketing promotions, and to improve overall response rates, which is well known and is widely applied today. Less widely understood is the value of applying RFM scoring to a customer database and measuring customer profitability. RFM analysis is considered significant also for the banks and their specific units like e-banking. A customer who has visited an e-banking site Recently (R) and Frequently (F) and created a lot of Monetary Value (M) through payment and standing orders is very likely to visit and make payments again. After evaluation of the customer’s behaviour using specific RFM criteria the RFM score is correlated to the bank interest, with a high RFM score being more beneficial to the bank currently as well as in the future. Data mining methods can be considered as tools enhancing the bank RFM analysis of the customers in total as well as specific groups like the users of e-banking.

The theory of customer relationship management has been gradually penetrated into all levels of enterprise management. As a close business with customers, travel agency should focus on customer relationship management, which is very important. This paper attempts to combine the concept of customer relationship management and the processes of traditional travel agency marketing to construct the system architecture, considering the actual situation and specific requirements of a travel agency, combining with norms and standards of the management of travel agencies industry, as well as, using the current popular system architecture B/S (Browser/Sever) Mode. By extensively studying the theory of software engineering, database theory and object-oriented languages and Web programming, management information systems analysis and design process of travel agency marketing is discussed in detail based CRM.

With all the hype over CRM, most business practitioners believed that CRM technology would be able to solve all marketing problems and automatically create profitability from the customers. However many CRM implementation plans fail or are unsatisfactory. CRM incurs expensive introduction costs of technology and organizational transformation. In addition, more resources are needed for leveraging customer value, which is an important goal of CRM activities. Researchers blame CRM failure on the use of the wrong CRM strategy and imperfect organizational transformation. Then is there any right CRM guidance to correct these problems? Almost all the guidance we investigated seems to be obscure and speculative. Existing guidance do not take account of diverse market conditions that different firms face so that one-size-fit-all recipes may confuse the practitioner because it focuses more on CRM technology itself. They all advocate a firm’s focus on retention and value leveraging of the limited number of only highly profitable customers. Then, what happens to less profitable customers? Does this cream-skimming work for every different market and firm? In order to answer these questions, we approach CRM from the economic point of view and derive the optimal strategic choices of CRM implementation pertaining to customer retention and value leveraging guidance. For different market situations, we consider network externalities. Our work provides a theoretical framework to verify the economic value of CRM. Our results show that market conditions and cost structure of CRM lead to quite different strategies in customer retention and leveraging. This may serve as a cautionary note to the hype that the CRM industry has created.