Advances in Economics, Management and Political Sciences
- The Open Access Proceedings Series for Conferences
Proceedings of the 2nd International Conference on Financial Technology and Business Analysis
Series Vol. 97 , 02 July 2024
Open
Access | Article
Review on the Use of Data Analysis for Customer Segmentation and Personalization in Marketing
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Abstract
Marketing is a part of business that requires considering countless variables and making accurate decisions. With the development of computer science and algorithms, the advancement of data analysis methods can be applied in this field to bring great convenience. Despite a large number of data analysis models being constructed, there is a lack of review articles that need to summarize algorithms created by previous generations. This paper starts with a lookback to the basic descriptive and predictive data analysis methods following with the introduction and further explanation of customer segmentation and personalization. Combined with the basic marketing methods, we studied the application of data analytics to business industry. Moreover, this paper presents case study that highlight the application of data analysis in different areas: online retail, e-commerce and transportation. Finally we use each case to find utilization of data analytics to derive meaningful insights and facilitation decision-making.
Keywords
Data analysis, Customer Segmentation, Personalization, K-means, Regression
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Data Availability
The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.
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- Volume Title
- Proceedings of the 2nd International Conference on Financial Technology and Business Analysis
- ISBN (Print)
- 978-1-83558-505-4
- ISBN (Online)
- 978-1-83558-506-1
- Published Date
- 02 July 2024
- Series
- Advances in Economics, Management and Political Sciences
- ISSN (Print)
- 2754-1169
- ISSN (Online)
- 2754-1177
- DOI
- 10.54254/2754-1169/97/20231519
- Copyright
- 02 July 2024
- Open Access
- This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited