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. 69 , 08 January 2024
Open
Access | Article
Implementation of Bigdata Analysis in Consumer Behavior
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Abstract
Nowadays, as the way of bigdata analysis become more and more diverse and specific, some people have already turned their eyes to the implementation of these analysis in consumer behavior. Since the markets are more competitive, it would save time and money that the companies produce what the consumers like. In addition, many markets exist for a long time and companies collect a plenty of consumers’ data, when they use bigdata analysis on the data collected, they can clear make accurate prediction about future products. In this study, we split the implementation of bigdata analysis in consumer behavior into several parts, including the history of the research, the specific analyzing methods, the realistic applications and limitations. In each part, we combine the facts and the understanding to write the analysis by the reference of some authoritative documentations. As a matter of fact, there are two significances of research, first is to have a comprehensive understanding of the current situation about topic from by-parts investigation; second is to have a future imagination based on both the advantages and disadvantages have now.
Keywords
Consumer behavior, big data, data anaylsis
References
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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)
- 978-1-83558-269-5
- ISBN (Online)
- 978-1-83558-270-1
- Published Date
- 08 January 2024
- Series
- Advances in Economics, Management and Political Sciences
- ISSN (Print)
- 2754-1169
- ISSN (Online)
- 2754-1177
- DOI
- 10.54254/2754-1169/69/20231289
- Copyright
- 08 January 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