Research on Using Market Segmentation to do Recommendation in E-commerce

DOI

10.2991/aebmr.k.220307.492How to use a DOI?

Keywords

Marketing segmentation; Clustering; K-means algorithm; Recommendation; E-commerce

Abstract

In the background of the digital period, more and more e-commerce companies have emerged. However, the competition also becomes more intense than before own to a large number of rivals. In this case, it is important to offer the customers recommendation to boost their satisfaction and loyalty. This work will use marketing segmentation as a method to predict the behavior of each customer, and the recommendation system will provide personalized recommendations based on the results. This paper exhibited the process of market segmentation and the K-means algorithm is introduced as the main part to do market segmentation. And the market was segregated based on several characteristics. In addition, the author discussed how to do recommendations by using the result of market segmentation. As a result, two advantages were exhibited: one is boosting the advertising efficiency, another is improving service. Therefore, it could be emphasized that market segmentation completed the recommendation system.

Copyright

© 2022 The Authors. Published by Atlantis Press International B.V.

Open Access

This is an open access article under the CC BY-NC license.

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TY  - CONF
AU  - Bohan Zhao
PY  - 2022
DA  - 2022/03/26
TI  - Research on Using Market Segmentation to do Recommendation in E-commerce
BT  - Proceedings of the 2022 7th International Conference on Financial Innovation and Economic Development (ICFIED 2022)
PB  - Atlantis Press
SP  - 3017
EP  - 3022
SN  - 2352-5428
UR  - https://doi.org/10.2991/aebmr.k.220307.492
DO  - 10.2991/aebmr.k.220307.492
ID  - Zhao2022
ER  -