The application of customer segmentation is very vital in the world marketing, a manager determining marketing strategy, knowing target must, otherwise it will potentially waste resources to pursue wrong target. Customer aims create relationship with most profitable customers by designing appropriate strategy. Many statistical techniques have been applied segment market but large data are influ...

This article addresses the challenge of determining optimal product family architectures with customer preference data. The proposed model, predictive data-driven product family design (PDPFD), expands clusteringbased approaches to incorporate a market-driven approach. The market-driven approach provides a profit model in the near future to determine the optimal position and number of product a...

Sales and marketing is the indispensable department of an organization which leads to generation revenue building customer relationship. Marketing process finding potential customers sales converting those into real customers. Hence, it imperative that go hand in hand. Developing strategies needs proper market research can cover relevant pointers like demographics, culture, spending power, inco...

Abstract Customer segmentation and key account management are important use cases for clustering algorithms. Here, a data set of Portuguese wholesaler food household supplies is used as an exemplary application. To increase the quality analysis, two-stage approach proposed. First, accounts filtered by density-based outlier detection. Second, Gaussian Mixture Model (GMM) applied to cluster small...

With the fast development of digital systems and concomitant information technologies, there is certainly an incipient spirit in the extensive overall economy to put together digital Customer Relationship Management (CRM) systems. This slanting is further more palpable in the telecommunications industry, in which businesses turn out to be increasingly digitalized. Customer churn prediction is a...

This chapter describes a practical area of application of decision reducts to a real-life business problem. It presents a feature selection (attribute reduction) methodology based on the decision reducts theory, which is supported by a designed and developed visualization system. The chapter overviews an application area Customer Loyalty Improvement Recommendation, which has become a very popul...

This paper aimed to build unified pattern per customer not only represent normal behavior but also Fraud pattern that’s represented previously and confirmed as fraud transactions that’s facilitate studding fraudsters behavior. An enhancement for the proposed algorithm of Fraud Miner has been proposed. This enhancement involves introducing LINGO clustering Data mining algorithm by replacing Apri...

This study proposes a model that utilizes soft computing and Markov Chains within a data mining framework to observe the stability of customer segments. The segmentation process in this study includes clustering of existing consumers and classification-prediction of segments for existing and new customers. Both a combination and an integration of soft computing techniques were used in the propo...

Identifying a customer profile of interest is a challenging task for sellers. Preferences and profile features can range during the time in accordance with current trends. In this paper we investigate the application of different model-based Collaborative Filtering (CF) techniques and in particular propose a trusted approach to user-based clustering CF. We propose a Trust-aware Clustering Colla...