目的 现有新能源汽车移动端APP设计普遍以统一需求为导向,忽视了不同年龄段用户的差异化需求。为提升用户满意度,需构建更具针对性的个性化设计机制。方法 提出考虑不同年龄用户偏好差异的Kmeans-KANO需求分析模型。首先提取用户自然语言需求并编码为特征向量,其次通过Kmeans聚类识别不同年龄段用户的需求差异,结合KANO模型分析青年与中年群体的功能偏好。结果 形成差异化的APP优化方案,明确青年与中年用户的关键诉求,设计匹配其需求的功能模块与交互界面,显著提升用户满意度。结论 定量揭示了年龄差异对用户需求的影响,所提设计框架增强了APP的个性化服务能力,并为产品优化提供了理论支持与实践参考。
Abstract
Most current mobile APPs for new energy vehicles are designed based on generalized user needs, failing to address the diverse preferences of users at different ages. The work aims to establish a more targeted personalized design mechanism to improve user satisfaction. A Kmeans-KANO-based need analysis model based on references of users at different ages was proposed. Firstly, Natural-language user needs were collected and transformed into quantitative feature vectors via encoding. Then, Kmeans clustering was applied to identify distinct need patterns across user groups. In combination with the KANO model, functional preferences of the youth and middle-aged users were analyzed. Accordingly, differentiated APP optimization plans were formed, the key needs of young and middle-aged users were clearly identified, and functional modules and interactive interfaces that matched their needs were designed, significantly enhancing user satisfaction. It quantitatively reveals the influence of age differences on user needs. The proposed design framework enhances the personalized service capability of APPs and provides theoretical support and practical reference for product optimization.
关键词
新能源汽车 /
移动端APP /
差异化设计 /
KANO模型 /
特征聚类
Key words
new energy vehicles (NEVs) /
mobile APPs /
differentiated design /
KANO analysis /
cluster features
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