电商平台信息对商家营销决策优化研究——基于天猫平台数据的检验

Research on Marketing Decision Optimization of E-commerce Platform Information——Verification based on Tmall platform data

挖掘电商平台信息的效用价值对提升电商企业数字化营销水平具有重要意义,能够为电商平台商家制定高效的营销决策提供科学依据。本文采用符号回归方法,揭示产品价格、累计评价、收藏人气等信息对产品销量的影响关系。结果发现4个适应度较高的模型,电商平台商家需要结合实际情况,确定选择哪个模型。并揭示了销量与产品价格、收藏人气、累计评价密切线性相关,核心变量是累计评价。基于此,应加强在线评论管理,激发消费者撰写评论的积极性;增加产品累计评价与收藏人气,并提升转化率;根据销售目标制定相应的营销策略,提升服务质量,拉动消费者需求升级。

Mining the utility value of e-commerce platform information is of great significance to improve the digital marketing level of e-commerce enterprises,and can provide scientific basis for e-commerce platform merchants to make efficient marketing decisions.In this paper,the symbolic regression method is used to reveal the influence of product price,cumulative evaluation,collection popularity and other information on product sales.The results show that there are 4 models with high fitness.E-commerce platform merchants need to decide which model to choose based on the actual situation.It is also revealed that there is a close linear correlation between sales volume and product price,collection popularity and cumulative evaluation,and the core variable is cumulative evaluation.Therefore,the management of online reviews should be strengthened to stimulate the enthusiasm of consumers to write reviews.Increase the cumulative evaluation and collection popularity of products,and improve the conversion rate;Formulate corresponding marketing strategies according to sales targets,improve service quality,and promote consumer demand upgrading.