Title: Identifying customer satisfaction estimators using review mining
Authors: Takayuki Suzuki; Kiminori Gemba; Atsushi Aoyama
Addresses: Graduate School of Technology Management, Ritsumeikan University, Biwako Kusatsu Campus, 1-1-1 Noji-higashi, Kusatsu City, Shiga Prefecyure, 525-8577, Japan ' Graduate School of Technology Management, Ritsumeikan University, Biwako Kusatsu Campus, 1-1-1 Noji-higashi, Kusatsu City, Shiga Prefecyure, 525-8577, Japan ' Graduate School of Technology Management, Ritsumeikan University, Biwako Kusatsu Campus, 1-1-1 Noji-higashi, Kusatsu City, Shiga Prefecyure, 525-8577, Japan
Abstract: In recent years, various methods have been developed which enable organisations to collect information on customer sentiments, perceptions, and demands. However, these methods do not provide practical guidance for utilising this information to offer superior products and services to their customers. Given this oversight, the current study proposes a new method for identifying the strengths and weaknesses of products or services by using language-processing software on product reviews. We use an online review site, Skytrax, to collect user reviews related to economy class flights for four airlines. We then analyse the language inherent in these reviews to identify the strengths and weaknesses of each airline. The results of the analyses may assist in reconciling discrepancies between customer expectations and their perceptions of products or services.
Keywords: natural language processing; NLP; customer satisfaction; customer needs; customer assessment; multiple regression analysis; quantitative analysis; word-of-mouth communication; WoM; airline industry; marketing; strategic planning; review mining; product reviews; user reviews; economy class flights; airline strengths; airline weaknesses; customer expectations; customer perceptions.
DOI: 10.1504/IJTMKT.2014.060100
International Journal of Technology Marketing, 2014 Vol.9 No.2, pp.187 - 210
Received: 16 Feb 2013
Accepted: 04 Sep 2013
Published online: 30 May 2014 *