基于评论挖掘消费者偏好的蓝牙耳机设计策略

Bluetooth Headset Design Strategy Based on Mining Consumer Preferences from Reviews

目的 本研究旨在从在线评论数据中挖掘消费者偏好信息,以探索蓝牙耳机设计的改良策略。方法 使用Python爬虫抓取目标消费者评论,并通过数据挖掘和文本分析定位需求主题和关键词后,基于消费者偏好理论,对产品功能属性进行情感分析和需求描述以控制变量,运用Mixed-logit模型提取消费者偏好特征以寻求最优的设计策略。结果 通过定量的实证研究,回归分析了偏好特征参数的显著性表达,生成蓝牙耳机改良策略实例并通过满意度检测验证其可行性。结论 结合评论挖掘和Mixed-logit模型,不仅能够设计出以消费者偏好为核心的产品设计方案,还可以为相关产品的设计策略改进提供指导与建议,具有一定的创新性和实用性。

The work aims to mine consumer preference information from online review data in order to explore the improvement strategy of Bluetooth headset design. The Python crawler was used to capture target consumer reviews, and the demand topic and keywords were located through data mining and text analysis. Based on the theory of consumer preference, sentiment analysis and demand description of product functional attributes were conducted to control vari- ables, and the Mixed-logit model was used to extract consumer preference characteristics, so as to seek the optimal design strategy. Through quantitative empirical research, the significant expression of preference characteristic parameters was analyzed by regression, and an example of Bluetooth headset improvement strategy was generated, and its feasibility was verified by a satisfaction test. The combination of review mining and Mixed-logit model can not only design the product design scheme with consumer preference as the core, but also provide guidance and suggestions for the improvement of related product design strategies, which has a certain degree of innovation and practicality.