Contemporary companies try to build customer relationship management systems based on the customer social relations and behavioral patterns. This is in correspondence with the current trend in marketing that is to move from broadcast marketing operation to a one-to-one marketing. The key issue in this activity is predicting to which products or services a particular customer was likely to respo...

Customer Relationship Management (CRM) is increasingly found at the top of corporate agendas. Online companies in particular are embracing CRM as a major element of corporate strategy, because online technological applications permit a precise segmentation, profiling and targeting of customers, and the competitive pressures of the digital markets require a customer-centric corporate culture. Th...

We show genetic programming (GP) populations can evolve under the influence of a Pareto multi-objective fitness and program size selection scheme, from “perfect” programs which match the training material to general solutions. The technique is demonstrated with programmatic image compression, two machine learning benchmark problems (Pima Diabetes and Wisconsin Breast Cancer) and an insurance cu...

Supply-Demand mismatch is a continuous challenge among suppliers creating poor customer service levels and often leading to higher costs the entire supply chain, meet demands of customer. This paper will highlight demand-supply issues between steel supplier having with one its premier automobile customers due difficulties in forecasting appropriate demand from The outcome original research was ...

This report examines the problems of customer relationship management (CRM) particularly customer segmentation and customer profiling, and how data mining tools are used to support the decision making. We first describe the steps towards predicting customer’s behavior, such as collecting and preparing data, segmentation and profile modeling. Then, we present a general overview of most used data...

Scoring models yield continuous predictions instead of sharp classifications. Scoring customers for profitability, loyalty, or product affinity corresponds to an inductive fuzzy classification: The model represents a continuous membership function mapping the set of customers into the fuzzy set of interesting customers – the fuzzy target group. This chapter presents a method for membership func...

a r t i c l e i n f o Keywords: Customer response predictive model Knowledge-based marketing RFM Neural networks Decision tree models Logistic regression Decision support techniques and models for marketing decisions are critical to retail success. Among different marketing domains, customer segmentation or profiling is recognized as an important area in research and industry practice. Various ...