Επιχειρηματική αναλυτική στην πράξη : τμηματοποίηση πελατειακής βάσης και ανάλυση καλαθιού αγορών για ένα ηλεκτρονικό κατάστημα μίας αλυσίδας στο χώρο του λιανεμπορίου
Customer analytics in practice : customer segmentation and e-shop market basket analysis
View/
Keywords
Market basket analysis ; RFM ; Business analytics ; Customer segmentationAbstract
This paper aims to explore ways to enhance business operations and decision-making processes through the use of Big Data and Artificial Intelligence. The paper also focuses on the application of the RFM model as a business analytics method, used for customer segmentation and for predicting customers’ future behavior. Finally, the paper discusses the Market Basket Analysis (MBA) method, which generates association rules between purchased products by consumers, using historical purchase data. For the application of the RFM model, the MBA method and the extraction of the corresponding results and conclusions, SAS software is used as well as historical data of the Greek supermarket chain "Atlantic", which is no longer active. In the first chapter, the potential applications of Business Intelligence and Business Analytics in various areas of economic life are explored, with an emphasis on Artificial Intelligence (AI). In the second chapter, the applications of AI in the areas of Customer Analytics, such as visual analytics, predictive modelling and customer segmentation, are examined. The RFM (Recency, Frequency and Monetary) model and its key elements, such as its scoring model, its purpose and its potential combination with other techniques to improve results, are described in detail. The MBA method in terms of its purpose, the algorithms used and the concepts of support and trust, which play a central role in it, are also described. In the last chapter, a case study is presented to demonstrate how the techniques described can be practically applied to Customer Value analysis using the RFM model, as well as to market basket analysis using the MBA method. Before applying the techniques, a basic exploration of the company’s data is attempted, with the aim of demonstrating the value of visual analysis as a simple yet powerful tool in the field of business analytics. The paper concludes through the analysis to numerous useful results and provides potential recommendations for their use. In the appendix of the paper, the code used within the SAS application for data processing and various analyses is included.
Postgraduate Studies Programme
Κυβερνοασφάλεια και Επιστήμη ΔεδομένωνDepartment
Σχολή Τεχνολογιών Πληροφορικής και Επικοινωνιών. Τμήμα ΠληροφορικήςNumber of pages
68Language
GreekCollections
Except where otherwise noted, this item's license is described as
Αναφορά Δημιουργού-Μη Εμπορική Χρήση-Όχι Παράγωγα Έργα 3.0 Ελλάδα
Αναφορά Δημιουργού-Μη Εμπορική Χρήση-Όχι Παράγωγα Έργα 3.0 Ελλάδα