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E-Commerce Customer Shurn Prediction Based Machine Learning Algortihms
(MEF Üniversitesi, Fen Bilimleri Enstitüsü, 2018) Eser, Ahmet Yetkin; Arısoy Saraçlar, Ebru
With the development and popularization of a digital world, human behavior has changed so remarkably. A lot of sectors affected because of this change. One of the most affected areas is the retail sector. People have left their regular shopping habits and started shopping on e-commerce sites. Thanks to increasing of variety and volume of collected data and velocity of new machines, companies can use sophisticated algorithms efficiently on their data. In this paper, we discuss about how companies can predict potential churned customers with machine learning methods.

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