In the current era of digitalisation, prosperous companies are showing great interest in their customers' feedback and perceptions regarding the products or services they provide. Customer sentiment analysis, which entails understanding and interpreting customer emotions and viewpoints, has emerged as an essential element of business tactics aimed at increasing customer satisfaction and recognising opportunities for improvement. The purpose of this research is to investigate and use ChatGPT in the realm of business customer sentiment analysis. The main focus of this research was largely qualitative in nature. The methodology for acquiring data required a rigorous approach in observing and documenting data, which was then subjected to analysis techniques such as data reduction, visualisation, and inference to extract significant findings. The findings from this study indicate that the utilisation of ChatGPT has significant potential in improving customer sentiment analysis for commercial enterprises. It can help in understanding and addressing customer requirements, tendencies, and satisfaction levels. ChatGPT's proficiency in understanding natural language, detecting customer emotions, and processing vast data instantly, can provide valuable perspectives for companies to improve their decision-making process. However, it is important to understand that ChatGPT should not be the sole source of information and the analysis results need to be interpreted judiciously by humans. This research resulted in suggestions consisting of several important points, namely collect and organise data well, train the model with appropriate data sets, validate results with other approaches, combine human and technological approaches, and use analysis results as a guide.