A Multidimensional Analysis of the Impact of Smartphone Technical Specifications on Sales Performance: An Analysis Based on Consumer Purchasing Behavior

By analyzing the relationship between smartphone technical specifications and sales performance, this study explores the influence mechanism of product parameters on consumer purchasing behavior. The study is based on a data set of 130 smartphone sales records covering product numbers, prices, sales volumes and 12 core technical specifications. Three models, linear regression, random forest and gradient lift regression, were used to quantify the relative importance of each technical parameter to sales combined with feature engineering techniques. The results show that price, camera comprehensive function, weight, front camera specifications and thickness are the five main factors that affect sales performance. It is found that the price of mobile phones has a nonlinear relationship with the sales volume. The interaction between memory and Random Access Memory (RAM) confirms the combined influence of technical specifications. Camera features have a greater impact on sales of high-end models, revealing the difference in consumer focus on products at different prices. This study provides optimization directions for smartphone manufacturers, emphasizing that priority should be given to improving camera functions, reducing product weight and thickness, and developing differentiated technical parameters and price strategies according to target groups. The results of this study provide effective empirical support for mobile phone product development, price decision and market optimization.