data mining is a powerful tool for firms to extract knowledge from their customers’ transaction data. one of the useful applications of data mining is segmentation. segmentation is an effective tool for managers to make right marketing strategies for right customer segments. in this study we have segmented retailers of a hygienic manufacture. nowadays all manufactures do understand that for sta...

RFM (Recency, Frequency, Monetary) analysis is a method to identify high-response customers in marketing promotions, and to improve overall response rates, which is well known and is widely applied today. Less widely understood is the value of applying RFM scoring to a customer database and measuring customer profitability. RFM analysis is considered significant also for the banks and their spe...

In this paper, we apply clustering analysis of data mining into power system. We adapt K-means clustering algorithm to analyze customer load, analyzing similar behavior between customer of electricity, and we adapt principal component analysis to get the clustering result visible, Simulation and analysis using matlab, and this well verify cluster rationality. The conclusion of this paper can pr...

An efficient customer behavior analysis is important for good Recommender System. Customer transaction clustering is usually the first step towards the analysis of customer behavior. Traditionally data mining techniques are deployed in order to provide effective recommendation based on large population of customer transactions in real time. Customer transactions are likely to be imprecise and i...

This study aimed at providing a systematic method to analyze the characteristics of customers’ purchasing behavior in order to improve the performance of customer relationship management system. For this purpose, the improved model of LRFM (including Length, Recency, Frequency, and Monetary indices) was utilized which is now a more common model than the basic RFM model apt for analyzing the cus...

Knowing about the customer behavior in a grocery has been a long-standing issue in the retailing industry. The advent of RFID has made it easier to collect moving data for an individual shopper's behavior. Most of the previous studies used the traditional statistical clustering technique to find the major characteristics of customer behavior, especially shopping path. However, in using the clus...

Data mining can be evaluated as a strategic tool to determine the customer profiles in order to learn customer expectations and requirements. Airline customers have different characteristics and if passenger reviews about their trip experiences are correctly analyzed, companies can increase customer satisfaction by improving provided services. In this study, we investigate customer review data ...