Customer Segmentation is the process of grouping the customers based on their purchase habit. Data mining is useful in finding knowledge from huge amounts of data. The clustering techniques in data mining can be used for the customer segmentation process so that it clusters the customers in such a way that the customers in one group behave similar when compared to the customers in the other gro...

Due to an ever increasing complexity, modern supply chains have to make use of Decision Support Systems to focus on the one hand on cost savings and on the other hand on a high customer orientation. This is especially difficult due to different service and costs expectations that have to be taken into account jointly to fulfill the customer expectations more precisely. While the need for a diff...

Data mining is a well-known technique, which can be used to extract hidden information about customers’ behaviors. It is used to improve the customer relationship management processes by various Organizations. Previous researches in constraint based pattern mining emphasis only on the concept of frequency.But the changes in the environment may occur frequently, so the frequently occuring patter...

What will your customer do next? Customers behave differently; they are not all average. Can you simultaneously meet your customers’ needs and improve profitability? You can by communicating and providing better offers to customers based on their behavior and demographics. Segmentation gives you the ability to group customers in many ways: 1) Business rules; 2) Supervised clustering – decision ...

Market segmentation is critical for a good marketing and customer relationship management program. Traditionally, a marketer segments a market using general variables such as customer demographics and lifestyle. However, several problems have been identified and make the segmentation result unreliable. This paper develops a novel market segmentation methodology based on product specific variabl...

Customer classification is an area of utmost interest for all businesses. For any organization retaining customer is more important than making new customers. In this paper, a simple idea based on Hopfield Neural Network (HNN) is proposed for multiclass classification of customer loyalty. Initially, transformation and k-medoid clustering algorithm preprocesses the training example dataset. Then...

Web services are published by the service providers through the internet as independent software components by fulfilling the requirements of the customer requests. As the customer requests are not always satisfied by a single service, the methods of services composition were evolved in which a chain of services are composed together. However the longer search time for the discovery of composed...

With the electricity market liberalization, the distribution and retail companies are looking for better market strategies based on adequate information upon the consumption patterns of its electricity customers. A fair insight on the customers’ behavior will permit the definition of specific contract aspects based on the different consumption patterns. The knowledge about how and when consumer...

In several empirical applications analyzing customer-by-product choice data, it may be relevant to partition individuals having similar purchase behavior in homogeneous segments. Moreover, should individualand/or product-specific covariates be available, their potential effects on the probability to choose certain products may be also investigated. A model for joint clustering of statistical un...

Data clustering is a common technique for data analysis, which is used in many fields, including machine learning, data mining, customer segmentation, trend analysis, pattern recognition and image analysis. Although many clustering algorithms have been proposed, most of them deal with clustering of one data type (numerical or nominal) or with mix data type (numerical and nominal) and only few o...