Cluster-based Customer satisfaction analysis

This study introduces a new and innovative approach to evaluate the customer satisfaction. Understanding customer satisfaction is crucial for companies that want to success in nowadays highly competitive markets. The use of tools such as Big Data Analytics and Machine Learning can help companies to identify key drivers of satisfaction and predict the impact of potential improvements. Traditional methods of gathering customer satisfaction data, such as questionnaires and online reviews, offer valuable insights, but analyzing this data comprehensively poses challenges such as understanding the impact of several different variables related to the same product or service aspect. Therefore, innovative approaches like clustering analysis are proposed. Our study proposes a novel machine learning-based tool for studying customer satisfaction, enabling the identification of impactful drivers, facilitating product comparisons, and providing insights into areas for improvement. In summary, unders...