Issue |
E3S Web Conf.
Volume 275, 2021
2021 International Conference on Economic Innovation and Low-carbon Development (EILCD 2021)
|
|
---|---|---|
Article Number | 01062 | |
Number of page(s) | 5 | |
Section | Energy Application and Ecological Resource Sustainability | |
DOI | https://doi.org/10.1051/e3sconf/202127501062 | |
Published online | 21 June 2021 |
Research on the Relationship between Marketing Strategy and Brand Development of Apparel Companies Based on Data Mining Technology
DUFE, Surrey International Institute, 116025, Dalian, China
* Corresponding author: sunyinan1314@icloud.com
The apparel industry is an important part of China’s economy and an important industry that drives the continuous improvement of national living standards. As the size of China’s internal market continues to expand, competition in the apparel industry has become increasingly fierce, making the development of apparel companies face huge challenges. For apparel companies, establishing a brand style that is unique and effective in attracting consumers, along with a sound brand marketing strategy, is a must for apparel companies to survive. This paper takes Company X, which is engaged in the apparel industry, as an example, and firstly analyses Company X’s brand marketing, then introduces data mining technology to analyse the relationship between Company X’s marketing strategy and brand development in view of the shortcomings of Company X’s brand marketing, and finally proposes a corresponding brand marketing strategy in order to provide a reference for the formulation of Company X’s brand marketing plan and promote the development of the apparel industry.
© The Authors, published by EDP Sciences, 2021
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.