Abstract The paper focuses on approach to the research into customer satisfaction based on a detailed analysis of consumer reviews written in natural languages using Artificial Intelligence methods such as Text Mining Aspect Sentiment Analysis Data Mining and Machine Learning The results proves the efficacy of the proposed approach for decision support in product quality management and argues for using it instead of classical methods of research Introduction Historically the assurance of quality is based on a process approach of a quality management system The methodology focuses on interaction of the company and the customer in the process of product production and consumption To improve the product quality the model incorporates feedback The feedback is expressed in form of customer reviews of the product quality To gauge customer satisfaction International Quality Standard suggests some methods personal interviews phone interviews discussion groups mail surveys online research and survey These methods have extensive drawbacks like generation of humongous amount of manual work which increases the research costs and hinders the continuous monitoring of customer satisfaction which in turn influences the managerial decision making process as it is dependent on the arrival rate of up to date information about customer opinions
