A Proposal for a System for Extracting Factors Behind Service Recipient Dissatisfaction

In recent years, the proliferation of social networking services has enabled customers to freely express their opinions and complaints. For companies, such review information is important vis-à-vis the evaluation of products and services and establishment of points for improvement. However, systematically extracting useful information from the huge amount of data is challenging, and the current situation entails its subjective interpretation by individual analysts. Herein, using the cosmetics industry as a case study, the objective was to identify customer interests and dissatisfaction quickly and accurately. Specifically, based on review information data, a specialized dictionary for cosmetics was constructed, incorporating vocabulary specific to the cosmetics industry. It was further developed into a generic dictionary for cosmetics that classified negative emotions into “complaints” and “requests.” This made it possible to extract what customers were feeling and complaining about more quantitatively and objectively. While the contents extracted as requests were factors to be improved, it was suggested that information on complaints could also be used to extract factors for improvement. However, it became clear that expressions related to the usability of cosmetics were diverse, and further action is required for review information that includes pictograms and subtle nuances.