Ing. Mark Azietaku

Master's thesis

Customers Classification using Recency Frequency, Monetary value (RFM), and K-means clustering algorithm

Customers Classification using Recency Frequency, Monetary value (RFM), and K-means clustering algorithm
Abstract:
Data mining has changed how people see data and how much knowledge and information it may provide for business decisions to enhance competitiveness and profitability. Companies use data mining techniques with Customer Relationship Management (CRM) to better understand their customers' requirements and preferences. This study suggested using K-means algorithms for consumer segmentation in a public institution …more
Abstract:
Data mining has changed how people see data and how much knowledge and information it may provide for business decisions to enhance competitiveness and profitability. Companies use data mining techniques with Customer Relationship Management (CRM) to better understand their customers' requirements and preferences. This study suggested using K-means algorithms for consumer segmentation in a public institution …more
 
 
Language used: English
Date on which the thesis was submitted / produced: 5. 1. 2024

Thesis defence

  • Date of defence: 30. 1. 2024
  • Supervisor: doc. Ahad Zareravasan, PhD
  • Reader: Ing. Michal Jirásek, Ph.D.

Citation record

Full text of thesis

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Institution archiving the thesis and making it accessible: Masarykova univerzita, Ekonomicko-správní fakulta

Masaryk University

Faculty of Economics and Administration

Master programme / field:
Business Management / Business Management

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