Μέθοδοι τμηματοποίησης πελατών με χρήση αλγορίθμων μηχανικής μάθησης
Customer segmentation methods with machine learning algorithms
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Keywords
RFM Μοντέλο ; Τμηματοποίηση πελατών ; Αλγόριθμοι μηχανικής μάθησης ; Customer segmentation ; Customer Lifetime Value (CLV)Abstract
Today, increased competition between organizations has led them to seek a better understanding of their business. In this way they will be able to estimate and make right decisions according to dynamic changes. Better understanding of a business is a procedure where strong and analytical skills are essential. Innovative ways of storing and analysing data are required. The Data Science has a major development on this field. Purpose of the thesis is to apply Machine Learning Methods on Implementation of Customer Segmentation. Customer satisfaction is one of the most important organizational goals. Since all customers do not represent the same profitability to an organization, understanding and identifying the valuable customers is considered crucial. Thus, understanding customers’ behavioural variables and categorizing customers based on these characteristics could provide better insight that will help business owners and industries to adopt appropriate marketing strategies such as up-selling and cross-selling. The current thesis presents a research on customer segmentation through Machine Learning Algorithms based on classic RFM Model. They are performed experiments on how a classic model behaves in a Machine Learning Environment. The results ensure and enhance the RFM model, providing the ability for future research.
Postgraduate Studies Programme
Ψηφιακά Συστήματα και ΥπηρεσίεςDepartment
Σχολή Τεχνολογιών Πληροφορικής και Επικοινωνιών. Τμήμα Ψηφιακών ΣυστημάτωνNumber of pages
64Language
GreekCollections
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Attribution-NonCommercial-NoDerivatives 4.0 Διεθνές
Attribution-NonCommercial-NoDerivatives 4.0 Διεθνές