Graph Database Modeling of a 360-Degree e-Customer View in B2C e-Commerce

Hristoski, Ilija and Dimovski, Tome (2020) Graph Database Modeling of a 360-Degree e-Customer View in B2C e-Commerce. Proceedings of the 2020 International May Conference on Strategic Management (IMCSM 2020), XVI (1). pp. 42-51. ISSN 2620-0597

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Abstract

For every B2C e-Commerce company, one of the major hurdles is the challenge of tracking the digital footprints of each e-Customer's activities during their online shopping sessions. As online competition becomes fiercer over time, online retailers face increasingly more sophisticated e-Customers. Knowing their buying habits and online shopping behaviors, which is a basic premise for building any strategies vis-à-vis retaining current and attracting new e-Customers, creates great opportunities for those who are capable of following and capturing relevant data about their e-Customers' digital trails. Usually part of contemporary CRM systems, the digital profile of an e-Customer, also known as 'a 360-degree e-Customer view', represents a collection of all e-Customers' data in one place. In this paper, a graph database modeling framework for constructing a 360-degree e-Customer view is proposed, with a single aim of exploring the possibilities of using NoSQL graph databases in storing highly relational data reflecting the complex interactions between e-Customers and a particular B2C e-Commerce website during online shopping sessions. The modeling framework is based on the utilization of a Customer Behavior Model Graph (CBMG) and is being implemented in Neo4j. The resulting graph database model represents a solid basis for answering a plethora of CRM-related questions.

Item Type:	Article
Subjects:	Scientific Fields (Frascati) > Natural sciences > Computer and information sciences Scientific Fields (Frascati) > Social Sciences > Economics and Business
Divisions:	Faculty of Economics Faculty of Information and Communication Technologies
Depositing User:	Prof. Dr. Ilija Hristoski
Date Deposited:	26 Dec 2022 08:45
Last Modified:	26 Dec 2022 08:45
URI:	https://eprints.uklo.edu.mk/id/eprint/7502

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