Application Analysis of Data Visualization in Tiktok E-commerce (2024)

Yufei Guo ^{* 1}

¹ Foreign Languages Department, Business College of Shanxi University, 369 Wenhua Street, Yuci District, Jinzhong City, Shanxi Province, China, 030619

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Abstract

With the rapid development of the e-commerce field, the application of data visualization technology is more extensive. Visual development in the field of Tiktok e-commerce can improve marketing accuracy and optimize consumers' shopping experience. However, visualization development in the field of Tiktok e-commerce has been affected. Based on this, the paper proposes to optimize Tiktok e-commerce by means of data optimization and integration. This paper uses the literature research method to analyze the application of data visualization in Tiktok e-commerce. Through reading a large number of literature, it is found that data visualization is of great help to the development of e-commerce. The technical realization and function summary of data visualization in Tiktok e-commerce are studied, but there are still some problems in commodity information, commodity quality, user positioning, logistics, and other aspects. Finally, some solutions are proposed.

Keywords

Tiktok, Data visualization, E-commerce, Short video platforms

References

1. Bo Maoyuan, Dai Fuping. Research on the application of data visualisation in the field of e-commerce big data [J]. Art and Design (Theory), 2017 (3) :76-78.

2. Liu Ping. Research on the application of visualisation technology in the field of e-commerce under the background of big data [J]. Journal of Guangxi Radio and Television University, 2023(1):29-32

3. Yang Ling. Research on the Continuous Usage Behaviour and Optimization Strategies of Short Video E-commerce Live Shopping Users--Taking TiktokAPP as an Example [D]. Wuhan Institute of Physical Education and Sports, 2023.

4. Author:Haoyuan Dingsheng. https://www.bilibili.com/read/cv24196271/ Source:bilibili

5. Liu Fei, NIU Lihui, JIN Changbo. Status quo, hotspot evolution and frontier analysis of big data research [J]. Digital Library Forum, 2015 (6) :62-67.

6. Chen Si, Gan Mi, Guo Xi. Impact of online visualisation of commodity storage information on e-commerce logistics efficiency [J]. China Circulation Economy, 2017 (8) :41-48.

7. Ni Chenhao. Research on the Application Status and Development Trend of Big Data Technology [J]. China Management Informatisation, 2021 (16) :179-180.

8. Li Ruoyu. Analysis of precision marketing strategy of e-commerce under the background of big data [J]. Modern Marketing (Business Edition), 2019 (12) :83.

9. Ding, Miao Miao. Research on data visualisation design of smart home products based on user experience [D]. Jinan: Shandong University of Architecture, 2021.

10. Zhao Jing, Zhang Jie. Research on Rural E-commerce Development Issues under the Perspective of Big Data [J]. Business and Economic Research, 2018 (7) :118-120.

11. Wang Xuhui. New retail in the new era: the transformation and upgrading trend of e-commerce under the wave of digital economy [J]. Journal of Beijing Technology and Business University (Social Science Edition), 2020 (5) :38-45.

12. Xue Ruichang, Wang Qi. Research on visual marketing standard of commodity information on e-commerce platform [J]. Modern Business, 2021 (26) :36-38.

13. Chen Shanshan. Optimisation of precision marketing strategy of company A's cross-border e-commerce platform based on user profiling [D]. Hangzhou: Zhejiang University of Technology, 2021.

14. Hu Yaqi, Lin Hai. The effect of online review characteristics on the sales of fresh e-commerce agricultural products - Evidence from Taobao lamb big data [J]. Journal of China Agricultural University, 2021 (6) :206-218.

15. Qu Juan. Research on visualisation of potential needs of furniture users based on text mining [D]. Nanjing: Nanjing Forestry University, 2020.

16. Zhang Xiaoqin. E-commerce logistics service innovation based on big data [J]. China Circulation Economy, 2018 (8) :15-22.

17. Chen Xingyu. Research on supply chain cost management of e-commerce enterprises under the background of big data [D]. Nanchang: Jiangxi University of Finance and Economics, 2021.

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)

978-1-83558-239-8

ISBN (Online)

978-1-83558-240-4

Published Date

28 December 2023

Series

Advances in Economics, Management and Political Sciences

ISSN (Print)

2754-1169

ISSN (Online)

2754-1177

DOI

10.54254/2754-1169/65/20231678

Copyright

© 2023 The Author(s)

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