A Case Study of Apple’s Success in Marketing Through Big Data Analysis

Chengwei Bai; Xiangting Chen

doi:10.54254/2754-1169/33/20231647

Research Article

Open access

Published on 10 November 2023

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Bai,C.;Chen,X. (2023). A Case Study of Apple’s Success in Marketing Through Big Data Analysis. Advances in Economics, Management and Political Sciences,33,128-131.

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A Case Study of Apple’s Success in Marketing Through Big Data Analysis

Chengwei Bai *^,1, Xiangting Chen ²

¹ University of New South Wales
² Cahznghou University

* Author to whom correspondence should be addressed.

https://doi.org/10.54254/2754-1169/33/20231647

Abstract

Apple Inc. is one of the most successful technology companies in the world and has been at the forefront of the big data analytics and marketing revolution. The use of big data has become a key element in marketing, and Apple's approach is a good case study for companies seeking to use big data to enhance their marketing strategies. This paper will take it as a case study to discuss how to use big data to promote marketing. This paper will briefly introduce Apple and the concept of big data and marketing, then analyze how Apple applies big data to analyze the market, discuss Apple’s successful cases in marketing, and summarize Apple’s marketing strategies. A conclusion will be drawn at the end.

Keywords

Apple Inc., marketing, big data

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Cite this article

Bai,C.;Chen,X. (2023). A Case Study of Apple’s Success in Marketing Through Big Data Analysis. Advances in Economics, Management and Political Sciences,33,128-131.

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 7th International Conference on Economic Management and Green Development

Conference website: https://www.icemgd.org/

ISBN：978-1-83558-087-5(Print) / 978-1-83558-088-2(Online)

Conference date: 6 August 2023

Editor：Canh Thien Dang

Series: Advances in Economics, Management and Political Sciences

Volume number: Vol.33

ISSN：2754-1169(Print) / 2754-1177(Online)

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