个性化传播中可变数据的开发和应用(英文)

Converting Relationships into Variables for Use in Personalized Communication

个性化传播包括许多因素:市场营销策略,清晰的数据库,建立客户接触点的数据分析,针对客户接触点的相关市场策略的规则,对客户隐私的保护,文件输出,衡量成功的尺度和响应客户反馈的迭代设计。近年来,利用客户数据实现个性化传播已获得越来越多的关注。然而,利用精确的数学方法从客户数据中提取关系数据,然后将其转化为抽象的规则,并融入实际的设计,这与其说是一种科学技术,不如说是一种艺术。本论文主要探讨了如何有效地将通过数据挖掘得到的重要变量转化为具体的编程规则,以准确地表示这些可变数据,并应用到个性化传播中。

Personalized communication consists of many elements;a marketing strategy,a clean database,data analysis to establish customer touch points,rules to relate market strategy with those touch points,protection of customer privacy,file output, metrics to measure success,and an iterative design to respond to customer feedback.The use of customer data to generate personalized communication has gained much attention in recent years.However,the exact methodology of extracting relationships and converting them into rules to incorporate into an actual design is still more of an art than a science.The focus of this paper is to explore methodologies to effectively translate important variables discovered through data mining into specific programming rules that correctly express those variables,and to apply those rules into personalized communications.