基于大数据技术的客户需求分析可视化平台构建研究

Shengping Yan, Hongbang Su, Guisheng Ma, Xiaoxuan Qi, Yuling Li, Liang Cheng
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引用次数: 0

摘要

摘要本文从面向客户需求的MC优化出发,利用大数据技术对模型进行优化,并借助模糊聚类分析方法,将不同类型的客户需求指标转化为不同的聚类效果。采用模糊聚类分析法建立客户需求、产品功能需求与设计参数之间的映射关系。运用客户需求分析与转化的思想和模块划分的方法,构建了产品配置设计的框架体系,完成了面向客户需求的产品配置可视化平台的构建。通过对不同的客户需求进行划分,得到客户需求的最佳分类,并以洗衣机产品的技术优化设计为例,分析本文构建的平台的实用性。在洗衣机的12个技术特性中,EG11的重要性为0.1395,EG1的重要性为0.1116,EG5的重要性为0.1017,这表明客户最关心的是产品的节能功能,因此企业应该根据客户的需求来设计产品,以满足客户的需求。
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Research on the construction of a visualization platform for customer demand analysis based on big data technology
Abstract In this paper, from the MC optimization oriented to customer demand, we use big data technology to optimize the model, and with the help of the fuzzy cluster analysis method, we convert the variable types of customer demand indexes into different clustering effects. Fuzzy cluster analysis is used to establish the mapping relationship between customer demand, functional requirements of the product, and design parameters. Use the idea of customer demand analysis and transformation and the module division method to build the framework system of product configuration design and complete the construction of a customer demand-oriented product configuration visualization platform. By dividing different customer requirements, the best classification of customer requirements is obtained, and the technical optimization design of washing machine products is taken as an example to analyze the practicability of the platform constructed in this paper. Among the 12 technical characteristics of the washing machine, the importance of EG11 is 0.1395, the importance of EG1 is 0.1116, and the importance of EG5 is 0.1017, which indicates that customers are most concerned about the energy-saving function of the product, and thus the enterprise should design the product based on the customer needs to satisfy the customer’s demands.
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来源期刊
Applied Mathematics and Nonlinear Sciences
Applied Mathematics and Nonlinear Sciences Engineering-Engineering (miscellaneous)
CiteScore
2.90
自引率
25.80%
发文量
203
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