Detect aspects affecting online customer service quality based on unstructured data mining

Abstract

Before making an online purchase, customers often tend to read comments, ratings (unstructured data) about products or services of the same type left by previous customers on e-commerce websites. Hidden inside those comments and ratings contain content of feelings related to the quality of business services of enterprises, product quality or generally called customer service quality. The content of this comment related to the quality of customer service is shown through each aspect in the sentence. This study extracts these aspects by applying the Supervised Machine Learning method (a method of mining unstructured data). Therefore, get a list of aspects reflecting customer service quality included in the collected data set. The results of the study have confirmed 33 aspects that can affect the quality of customer service in online business.