Comprehensive Evaluation Mechanism of Products Based on Data Analysis and Thinking in Time Dimension

In recent years, big data has become a popular trend, widely used in various fields to provide guidance. For selling products online, the platform provides an online review function that enables businesses to use these review data to understand the popularity of the product in the market. Many businesses intuitively get product ratings through customer ratings, while also exploring the direction of product improvement by analyzing the reviews left by customers. In this study, a comprehensive evaluation model was established to obtain a more accurate customer satisfaction evaluation by combining customer scoring and comments, quantifying reviews with the help of TextBlob, and using the entropy weight method to determine the weight of scores and reviews. This study takes the three types of products of Company S as an example, and explores different products and different types of market improvement strategies of the same product by analyzing their evaluation data, aiming to provide more valuable information for the company’s sales.