Modeling and predicting customer purchase behavior in the grocery retail industry

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Tezin Türü: Doktora

Tezin Yürütüldüğü Kurum: Orta Doğu Teknik Üniversitesi, Enformatik Enstitüsü, Bilişim Sistemleri Anabilim Dalı, Türkiye

Tezin Onay Tarihi: 2017

Öğrenci: SERHAT PEKER

Danışman: ALTAN KOÇYİĞİT

Özet:

In today’s business, grocery retail industry companies operate in highly competitive environment. Such an intense competition have compelled companies to develop close and long-term relationships with their customers by implementing more targeted marketing strategies and personalized services. To implement such customized services, modelling and predicting customer purchase behaviors are essential. Accordingly, this thesis mainly aims to model and predict the customers’ purchasing behavior in the grocery retail industry using machine learning techniques on past customer purchase logs. To this end, customer segmentation, product segmentation, prediction of customers’ individual purchase behaviors, and shopping list prediction are studied and a novel evaluation metric and an approach for determining recommendation list size are proposed. This thesis may serve as a valuable reference for academics and researchers who are willing to investigate customer purchase behavior and identify hidden patterns in their transactional data, and also promises substantial benefits to marketers and decision makers of grocery retailing industry in developing customized services and marketing activities.