Customer relationship management (CRM) comprises a set of processes and enabling systems supporting a business strategy to build long term, pro?table relationships with speci?c customers. Customer data and information technology (IT) tools form the foundation upon which any successful CRM strategy is built. In addition, the rapid growth of the Internet and its associated technologies has greatly increased the opportunities for marketing and has transformed the way relationships between companies and their customers are managed. Many organizations have collected and stored a wealth of data about their current customers, potential customers, suppliers and business partners. Data mining tools could help these organizations to discover the hidden knowledge in the enormous amount of data. The emerging fields of academic analytics and educational data mining are rapidly producing new possibilities for gathering, analyzing, and presenting student data. Faculty might soon be able to use these new data sources as guides for analyzing student dropout rate, student retention, course redesign and as evidence for implementing new assessments and lines of communication between instructors and students. This paper uses the college admission data with data mining techniques to objectively and methodically comment on the retention percentage in the college.

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Student Retention Classification Categorization