Customer Segmentation of Third Party Review Website Based on Cluster Analysis

DOI

10.2991/seiem-17.2018.5How to use a DOI?

Keywords

cluster analysis, discriminant analysis, customer segmentation, Dianping Holdings website

Abstract

This paper made segmentation of customers on the website of Dianping Holdings and identified the characteristics of different types of customers, so as to give recommendations to different clients. The paper used locomotive collector to grasp the customer information on the website of Dianping Holdings. After processing the original data, 38791 pieces of final data were got. Then, SPSS software was used in cluster analysis and discriminant analysis. In the end, the paper subdivides the customers on the Dianping Holdings website into six categories: hyperactive customers, active customers, moderately active customers, low-value customers, potentially high-value customers and high-value customers. It also finds that the number of female customers is more than male customers in six categories.

Copyright

© 2018, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Shan Gao
AU  - Changbin Jiang
PY  - 2017/12
DA  - 2017/12
TI  - Customer Segmentation of Third Party Review Website Based on Cluster Analysis
BT  - Proceedings of the 2017 2nd International Seminar on Education Innovation and Economic Management (SEIEM 2017)
PB  - Atlantis Press
SP  - 17
EP  - 20
SN  - 2352-5398
UR  - https://doi.org/10.2991/seiem-17.2018.5
DO  - 10.2991/seiem-17.2018.5
ID  - Gao2017/12
ER  -