A Conceptual Framework Of E-Commerce User’s Segmentation Using Big Data Analytics On Using Big Data Analytics

Abstract

In today’s competitive business environment, more and more organizations lead to move or extent their business e-commerce. Thus, there is an increasing need for organizations to build concrete e-commerce strategies in order to engage with their users. One basic step towards achieving the objectives related to e-commerce is the segmentation of e-commerce user’s, based on the user’s data gathered e-commerce. Since there is an onslaught of user’s information collected from e-commerce sources, new techniques are required for managing and analyzing thehuge amount of data; and this is where the concept of “Big Data” can play an essential role. This research sheds light on three fields: e-commerce marketing, user’s segmentation, and big data analytics. The three terms are combined into one framework, which attempts to show how e-commerce marketing objectives can be supported by an effective e-commerce user’s segmentation that can be implemented by techniques and tools applicable to extremely large datasets. For the creation of the framework the following steps are followed: a set of main e-commerce marketing objectives is defined; the differences among user’s attributes gathered from offline and e-commerce channels are discussed and e-commerce user’s segmentation categories are identified; the concept of big data is introduced and relevant techniques and tools suitable for analyzing user’s segmentation categories and segmenting users effectively are described.