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Customer Segmentation Analysis of E-Commerce Big Data
Indivar Shaik1, Tryambak Hiwarkar2, Srinivas Nalla3

1Indivar Shaik, Research Scholar, Department of Computer Science and Engineering, SSSUTMS, Sehore (Madhya Pradesh), India.
2Dr. Tryambak Hiwarkar, Professor, Department of Computer Science and Engineering, SSSUTMS, Sehore (Madhya Pradesh), India.
3Dr. Srinivas Nalla, Principal, Sahaja Institute of Technology & Science for Women, Karim Nagar (Telangana), India.

Manuscript received on 18 June 2019 | Revised Manuscript received on 25 June 2019 | Manuscript published on 30 June 2019 | PP: 582-587 | Volume-8 Issue-5, June 2019 | Retrieval Number: E7156068519/19©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: E-Commerce is a major area of application for generating Big Data and the data generated by E-Commerce is increasing rapidly. Now a days, almost all companies selling their products on E-Commerce platforms. The objective of every company is to improve their business and maximize their profits. As tough competition has become the norm of the day, every company works relentlessly to sustain their existing customer base and to acquire new customers, which intern increases their sales volume. To do so, each transaction generated by the company should be recorded so that the data can be further user for analysis. Analyzing such data has become a primary resource for organizations to improve upon their business. The current study analyzes the Customer Segmentation on a sample of Big Data generated by an E-Commerce firm. Customer Segmentation is performed based on the revenue and number of invoices generated on monthly, weekly and on a particular point of time in a day basis. Further this paper focuses on different Segmentation approaches proposed by different researches by analyzing the sample of an E-Commerce Big Data.
Keywords: E-Commerce, Segmentation, Big Data, Transaction.

Scope of the Article: E-Commerce