Τμηματοποίηση πελατών και πρόβλεψη πωλήσεων για μια ηλεκτρονική πλατφόρμα πωλήσεων
Customer segmentation and sales forecast for e-shop
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Keywords
Big data ; RFM analysis ; Forecasting ; Holt WintersAbstract
This thesis aims to leverage Big Data technologies to achieve data analysis, customer segmentation, and sales forecasting for an e-commerce sales platform. Customer segmentation is performed using the RFM (Recency, Frequency, Monetary) method, where customers are grouped based on their recent activity on the platform, the frequency of their purchases, and their monetary value, providing significant insights into their behavior. For sales forecasting, the Holt-Winters model is used, which considers seasonal trends and data fluctuations. This model, through exponential smoothing, offers reliable forecasts that help businesses create more efficient strategies and manage their inventory and resources more effectively. The forecasting results are evaluated and compared with actual sales to verify the model's accuracy. The overall analysis results show that the use of RFM analysis and the Holt-Winters forecasting model can significantly improve decision-making in businesses by providing a more comprehensive view of customer behavior and future sales trends.
Postgraduate Studies Programme
Κυβερνοασφάλεια και Επιστήμη ΔεδομένωνDepartment
Σχολή Τεχνολογιών Πληροφορικής και Επικοινωνιών. Τμήμα ΠληροφορικήςNumber of pages
96Language
GreekCollections
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Αναφορά Δημιουργού-Μη Εμπορική Χρήση-Όχι Παράγωγα Έργα 3.0 Ελλάδα
Αναφορά Δημιουργού-Μη Εμπορική Χρήση-Όχι Παράγωγα Έργα 3.0 Ελλάδα