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Authors

Shpolyanskaya I.

Degree
Dr of Economics, Associate Professor, Rostov State University of Economics
E-mail
irinaspol@yandex.ru
Location
Rostov-on-Don
Articles

Architecture of adaptive Web-based system of Customer Relationship Management based on Web Mining technology

The purpose of this paper is to present the architecture of the CRM system that uses Web Mining techniques and the principles of adaptive management. Adaptive model of customer relationship management in the Web CRM system based on Web Mining technologies is represented in the following form. The core of the CRM system is an adaptive website, based on dynamic analysis of the web resources information usage in order to modify the web site ontology and its personalization to improve user interaction. The system uses online methods to capture useful information from user log file data and browsing pages to analyze customers’ behavior, their preferences regarding different groups of goods and services of the company. The obtained data are structured using the cluster analysis, classification, and association rule mining in order to determine groups of customers and prospects with similar characteristics and behavior. Based on this analysis valuable consumer segments are determined according to the current customer value. For each group of customers system forms the most effective strategy for interaction. To develop adaptive strategies for interacting with customers the proposed model uses the self-organizing learning algorithms. As a result, when using an adaptive approach in Web CRM system forms a closed loop feedback, which allows in real time to adjust the strategy of interaction with customer according to his current preferences and constraints.
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