關鍵字：關鍵屬性、商機演算法 ;Previous research conducted customer surveys based on questionnaires and interviews, and then used survey data to analyze product characteristics. In recent years, consumers have actively posted comments on the Internet, and the comments contained a lot of information about customer opinions and expectations. However, previous research failed to solve the problem of using term-level analysis to identify potential product features and insufficient consideration of the opportunity potential analysis of identified products. Based on this, this research proposes an opportunity mining method to find product opportunities based on the key attributes of online review data and sentiment analysis. For multi-functional products, this method can identify potential product attributes discussed by product customers on the Internet, thereby quantifying the importance of each product’s key attributes. Next, use sentiment analysis to evaluate the satisfaction of each product′s key attributes. Finally, through the importance and satisfaction of the product theme, the opportunity algorithm identifies the opportunity value and improvement direction of each key attribute of the product from a customer-centric perspective, and analyzes the ever-changing customer needs in the fast-developing product environment.
