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Published on 7 February 2024
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Yan,Y. (2024). The application of backend database systems in precision marketing: A case study of Nike official online store. Applied and Computational Engineering,38,200-209.
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The application of backend database systems in precision marketing: A case study of Nike official online store

Yueqi Yan *,1,
  • 1 Communication University of China

* Author to whom correspondence should be addressed.

https://doi.org/10.54254/2755-2721/38/20230553

Abstract

In the era of big data, databases have become a powerful tool for enterprises to gain insight into consumer behavior and market dynamics. However, some enterprises, especially small and medium-sized ones, focus too much on data volume growth while ignoring the importance of data relevance, resulting in unsatisfactory marketing outcomes. Based on this, this paper provides an example of Nike official online store. With the assistance of structured query language (SQL), a backend database system is created under the Oracle11g R2 environment, and its functions are simulated and demonstrated. The system is capable of managing user, product, and order transaction information through basic functions such as adding, querying, modifying, and deleting. In addition, it serves as a foundation for Nike's precision marketing efforts through user profile construction, user behavior analysis, and demand forecasting based on basic statistical methods of counting, proportioning, and sorting.

Keywords

backend database, precision marketing, online shopping, SQL

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Cite this article

Yan,Y. (2024). The application of backend database systems in precision marketing: A case study of Nike official online store. Applied and Computational Engineering,38,200-209.

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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About volume

Volume title: Proceedings of the 2023 International Conference on Machine Learning and Automation

Conference website: https://2023.confmla.org/
ISBN:978-1-83558-301-2(Print) / 978-1-83558-302-9(Online)
Conference date: 18 October 2023
Editor:Mustafa İSTANBULLU
Series: Applied and Computational Engineering
Volume number: Vol.38
ISSN:2755-2721(Print) / 2755-273X(Online)

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