论文部分内容阅读
将客户关系管理(CRM)、数据统计分析、质量功能展开(QFD)方法相结合,系统研究了服装客户需求的有效获取、分析及映射的方法。首先,构建了服装CRM系统以获取客户信息,并利用模糊定性评价方法扩充客户需求信息;其次,利用数据统计方法对客户需求信息进行分析梳理;最后,利用QFD模型量化并层次展开客户需求,经关系矩阵构建质量屋,提出融合客户需求的服装产品设计方案。应用该系统方法对佩诺玛男式衬衫品牌的产品设计方案进行优化,其销售取得明显的市场效果。提出的服装客户需求的获取、分析及设计映射的方法,为云计算下的服装产品大数据预测开拓了有效的技术途径。
By combining customer relationship management (CRM), data statistical analysis, and quality function deployment (QFD), the methods of effective acquisition, analysis and mapping of apparel customer’s needs are systematically studied. First, the apparel CRM system is constructed to obtain customer information, and the fuzzy qualitative evaluation method is used to expand customer demand information. Secondly, the data statistical method is used to analyze customer demand information. Finally, the QFD model is used to quantify and level customer demand. Relationship matrix building quality house, put forward the integration of customer needs clothing product design. The method of this system is applied to optimize the product design of Penomon shirt, and the sales have achieved obvious market effect. The proposed method of acquiring, analyzing and designing the apparel customer’s needs opens up an effective technical approach for forecasting big data of apparel products under cloud computing.