The Application of Big Data Analysis in the Hierarchical Management of Automobile Customers
- DOI
- 10.2991/978-94-6463-036-7_264How to use a DOI?
- Keywords
- Automotive industry; Automobile sale; Big data; Big data analysis; Customer analytic
- Abstract
In recent years, automobiles are becoming one of the mainstream people's travel modes. The automobile industry has benefited from big data analytics to improve their sales and marketing efficiency. With the increasing popularity of network applications, the Internet is changing the business models of traditional industries. Traditional industries are undergoing online and digital transformation. This paper summarizes the importance of bigdata analysis and its application in hierarchical management of automobile customers. In general, automotive big data can be roughly divided into identity data, transaction data, and behavior data. Automobile manufactures can find out more valuable information of these research data in the automobile industry with the help of big data analysis and data mining. In addition, the classification of customers has also been discussed. It could be one of the potential solutions is customer analytics which use the lowest cost value to maintain the stickiness of customers and minimize the loss of customers.
- Copyright
- © 2022 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Haoran Wang PY - 2022 DA - 2022/12/31 TI - The Application of Big Data Analysis in the Hierarchical Management of Automobile Customers BT - Proceedings of the 2022 2nd International Conference on Economic Development and Business Culture (ICEDBC 2022) PB - Atlantis Press SP - 1770 EP - 1774 SN - 2352-5428 UR - https://doi.org/10.2991/978-94-6463-036-7_264 DO - 10.2991/978-94-6463-036-7_264 ID - Wang2022 ER -