A case study of predicting banking customers behaviour by using data mining

Data Mining (DM) is a technique that examines information stored in large database or data warehouse and find the patterns or trends in the data that are not yet known or suspected. DM techniques have been applied to a variety of different domains including Customer Relationship Management CRM). In this research, a new Customer Knowledge Management (CKM) framework based on data mining is proposed. The proposed data mining framework in this study manages relationships between banking organizations and their customers. Two typical data mining techniques - Neural Network and Association Rules - are applied to predict the behavior of customers and to increase the decision-making processes for recalling valued customers in banking industries. The experiments on the real world dataset are conducted and the different metrics are used to evaluate the performances of the two data mining models. The results indicate that the Neural Network model achieves better accuracy but takes longer time to train the model

Rural consumers' adoption of CRM in a developing country context

This paper illustrates how understanding consumer preferences through market research may enhance CRM adoption among the rural customers of a developing country like Bangladesh. It presents the case of Community Information Centre (CIC) established by Grameenphone, a company owned by Telenor, the Norwegian telecommunications company and Grameen Bank, the Nobel prize winning micro credit organisation in the rural settings of Bangladesh. The paper shows that CIC is an innovative way of building and maintaining customer relationships and technological interface with the financially constrained consumers in a poor developing economy like Bangladesh

Creating learning solutions for executive education programs

Executive education is both a growing and increasingly competitive industry. The traditional business school, once a dominant player in this space, now faces competition from sophisticated and focused consultants and for-profit training specialists offering a variety of face-to-face and on-line instructional vehicles. An abiding question has become ever more prevalent for business schools – are executive education clients getting meaningful, long-term value for their significant investments? Demonstrating value and building capabilities is different for a generic, open enrolment course than for a custom program. This paper proposes a solutions-based approach to the development and implementation of customized executive programs, arguing that the tailored customer focus and the operational rigor of a solutions perspective leads to sustainable and measurable client value both at the individual and corporate level. A case study involving a global high technology company is used to demonstrate the steps required to apply a solutions roadmap. The results show that a solutions approach – carefully and collaboratively undertaken in selected settings – can provide considerable benefits to both client and provider. Further research is proposed to validate and develop the learning points

Improving customer churn prediction by data augmentation using pictorial stimulus-choice data

The purpose of this paper is to determine the added value of pictorial stimulus-choice data in customer churn prediction. Using Random Forests and 5 times 2 fold cross-validation, this study analyzes how much pictorial stimulus choice data and survey data increase the AUC of a churn model over and above administrative, operational and complaints data. The finding is that pictorial-stimulus choice data significantly increases AUC of models with administrative and operational data. The practical implication of this finding is that companies should start considering mining pictorial data from social media sites (e.g. Pinterest), in order to augment their internal customer database. This study is original in that it is the first that assesses the added value of pictorial stimulus-choice data in predictive models. This is important because more and more social media websites are focusing on pictures

Building an IT Taxonomy with Co-occurrence Analysis, Hierarchical Clustering, and Multidimensional Scaling

Different information technologies (ITs) are related in complex ways. How can the relationships among a large number of ITs be described and analyzed in a representative, dynamic, and scalable way? In this study, we employed co-occurrence analysis to explore the relationships among 50 information technologies discussed in six magazines over ten years (1998-2007). Using hierarchical clustering and multidimensional scaling, we have found that the similarities of the technologies can be depicted in hierarchies and two-dimensional plots, and that similar technologies can be classified into meaningful categories. The results imply reasonable validity of our approach for understanding technology relationships and building an IT taxonomy. The methodology that we offer not only helps IT practitioners and researchers make sense of numerous technologies in the iField but also bridges two related but thus far largely separate research streams in iSchools - information management and IT management

Integrating Organisational Change Management and Customer Relationship Management in a Casino

This research aims to solve the problem: how can casinos manage organizational change programs, and internal and external customer relationship management (CRM) programs? To find a solution, it uses two stages of qualitative methods: convergent interviewing and case research about four departments of a casino in Australia. After a thorough data analysis of documents and interview data, 12 themes were identified and they led to the development of a model of how organizational change management and CRM can be integrated to improve initiatives in organisations such as casinos. The model has seven core elements: vision, key challenge, objective, measure, strategy, initiative and outcome. A contribution is the development of this evidence-based model of links between the both types of CRM and organisational change management, with an action checklist for managers. Analytic generalisation beyond the research setting was done in this research, but more external validation could be done in future research. Managers could use the checklist of actions about this research\u27s integrated model, to reduce the high failure rate of change initiatives