智能玩具多因素权衡定价策略选择——基于联合分析法的研究

Multi-factor trade-off pricing strategy for smart toys——Based on the study of joint analysis

本文将联合分析法应用于智能玩具开发优化与价格营销策略,结合在线销售数据和相关理论选取影响消费者购买决策的五个属性,并基于正交实验得出产品轮廓,根据消费者偏好的效用值进行权衡定价分析。结果显示:价格和功能是影响客户购买决策的最重要因素,其次是材质、造型和品牌因素。由此,本文提出基于相似效用值的不同属性水平组合产品的弹性定价策略,即通过产品功能的优化提高价格或者通过简化功能降低价格,然后基于价格档次进行消费者细分,从而了解其效用值无差异的产品等级和价格变化的曲线关系。

This paper applies the joint analysis method to the intelligent toy development optimization and price marketing strategy, combines online sales data and related theories to select five attributes that influence consumers’ purchasing decisions, and derives product outlines based on orthogonal experiments. The preferred utility value is traded against the pricing analysis. The results show that price and functionality are the most important factors influencing customer buying decisions, followed by materials, styling and branding. Therefore, this paper proposes an elastic pricing strategy based on similar utility values for different attribute level combination products, that is, to increase the price through optimization of product functions or to reduce the price by simplifying functions, and then to perform consumer segmentation based on price grades to understand its utility value. The relationship between the difference in product grade and price change.