A Proposed Paradigm for Enhancing Customer Retention using Web Usage Mining
Author(s) -
Merna Ashraf,
Shimaa Ouf,
Yehia Helmy
Publication year - 2020
Publication title -
international journal of computer applications
Language(s) - English
Resource type - Journals
ISSN - 0975-8887
DOI - 10.5120/ijca2020919772
Subject(s) - computer science , world wide web , data science
Due to the rapid growth of the internet and the emergence of the World Wide Web, there has been a huge amount of data stored in databases which increase the opportunities and relationships between companies and their customers. Although Companies find difficulty in satisfying customers with different backgrounds, so they find that it is important to adopt a strategy that helps them to understand and manage the needs of the organization’s current and potential customers which are called customer relationship management(CRM). The purpose of CRM is to create value for customers and help organizations to gain “competitive advantage” over competitors. Because many businesses face problems in how to benefit from this huge amount of data that come from the internet, this leads to the emergence of web mining, web mining uses data mining techniques to improve business. Because customer retention is the core of CRM. The purpose of this research is to improve customer retention by merging five data mining techniques in the pattern discovery phase of web usage mining in order to enhance the recommender system that will increase customer retention.
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