In this paper we present an application of single cluster visualization (SCV) a technique to visualize single clusters of high-dimensional data. This method maps a single cluster to the plane trying to preserve the relative distances of feature vectors to the corresponding prototype vector. Thus, fuzzy clustering results representing relative distances in the form of a partition matrix as well ...

Customer Journey Mapping (CJM), is an emerging area of research tackling issues related to customer behavior and user trajectories when consuming a service. The increasing complexity of the service industry makes this type of tools popular amongst practitioners. However, to date, it is not clear how a CJM can be used to depict hundreds or thousands of customer journeys. Inspired by process disc...

A fuzzy algorithm of web customers evaluation based on rough set is presented. Key attributes can be gotten through rough set. The evaluation from the data objects based on key attributes can reduce the data size and algorithm complexity. After Clustering analysis of customers, then the evaluation analysis will process to the clustering data. There are a lot of uncertain data in customer cluste...

The analysis of customer behavior is used to maintain good relationship with customers. It maximizes the customer satisfaction. We can also improve customer loyalty and retention. The aim of this paper is to develop a very useful trend for launching products with configurations for customers of different gender based on past transactions. Based on the previous transactions of the customers, pre...

Customer clustering is used to understand customers’ preferences and behaviors by examining the differences and similarities between customers. Kohonen vector quantization clustering technology is used in this research and is compared with Kmeans clustering. The data set consists of customer records obtained from a mobile telecommunications service provider. The customers are clustered using va...

We can have a new perspective about customer by analyzing customer shopping path data because customer should go to a specific place to buy some product in store. The analysis of path data is time-consuming work. In this way, the commonly used method is clustering algorithm in order to understand the tendency of data. But a general clustering algorithm is not suitable to identify the shopping p...

customers are the most valuable asset of an organization. due to high contest in the business field, it is necessary to regard the customer relationship management (crm) of the enterprise. data mining and machine learning methods been utilized by businesses in recent years in order to improve crm. crm is the strategy for building, managing, and strengthening loyal and long lasting customer rela...

RFM stands for Recency, Frequency and Monetary value. RFM analysis is a marketing technique used for analyzing customer behavior such as how recently a customer has purchased (recency), how often the customer purchases (frequency), and how much the customer spends (monetary). It is a useful method to improve customer segmentation by dividing customers into various groups for future personalizat...