基于WEB的面向大规模定制的软家装营销系统

该文通过对大规模营销和大规模定制营销的比较,提出了一种基于WEB的面向大规模定制的软家装混合营销模式,介绍了基于WEB的软家装营销系统。     

基于移动社交群的互联网内容适配系统的搭建

基于移动社交群,提出了一种面向群体推荐互联网内容的系统。这种面向社交群体的新精确营销模式不仅能提升营销效率,也减少了客户接触频次,提升了客户感知。     

探索最佳技术路线,打造个性化客户关系

Teradata最新调查显示,营销人员努力探索最佳技术路线,打造个性化客户关系。研究报告还披露,企业在预算决策中很大程度上依靠直觉而非利用数据,……最终将在客户体验上付出代价。     

个性化决策规则获取算法及规则表示

提出了一种基于粗糙集理论的面向个性化知识的决策规则获取算法。从理论上证明了算法的正确性,给出了面向个性化的知识获取算法的描述。算法的重点在于规则合成的方法和可信度、覆盖度和规则强度计算的方法。最后通过例子说明了算法的有效性和实用性。     

程序化营销三步曲

在过去几年里,营销数据处理,营销分析以及营销决策等方面的技术已经获得飞跃式的发展。数字营销已经占有举足轻重的地位,同时,它也大大加快了营销决策的进程。     

电力营销决策系统的研究

对电力营销决策系统的系统架构了进行研究,对系统的各功能模块进行了分析,电力营销决策系统是为企业的电力营销提供决策分析,相比人工的分析更加准确,大大提高了营销决策的效率,为电力企业把握好了营销的大门,大大提高了企业的信息化决策管理。     

协作营销信息系统的研究

营销信息系统是支持企业营销管理和决策的基本工具。本文简要讨论了营销信息系统的概念和发展,认为营销信息系统在本质上是协作处理系统,在对agent属性分析的基础上,提出了协作营销信息系统的结构。     

有名字的香蕉

个性化营销并不能帮助区别开你的产品或服务．但它能让人们喜欢上他们本不想要的东西。都乐香蕉的成功告诉人们，当所有的香蕉都毫无特色的时候，被个性化的赋予名字的香蕉更容易被人记住。这便是个性化营销的最简单印证。     

市场营销闭环管理的助推器

数据挖掘是一种新的商业信息处理技术,通过对商业数据库中的大量业务数据进行抽取、转换、分析和其他模型化处理,从中提取辅助商业决策的关键性数据。闭环管理是电信企业为了应对日益激烈的市场竞争而对营销活动提出的新要求。数据挖掘技术的有效应用,将可以成为营销闭环管理的助推器。     

粒化（a，k）-匿名方法研究

针对现有个性化隐私匿名技术不能同时满足面向个体需求的个性化和面向敏感属性值的个性化两方面的要求,引入了粒计算思想。建立隐私保护决策度集合,以刻画不同个体对敏感属性同一敏感值的不同保护要求;基于决策度集合的不同取值建立顶层粒度空间;对每个顶层粒度空间中敏感值赋予不同的出现频率约束,以满足面向敏感值的个性化匿名需求。算法分析及仿真实验结果表明,粒化（a,k）-匿名模型和算法以较小的信息损失和执行时间获得更综合、更合理的个性化隐私保护的实现。     

决策树在基于消费者外表的服装营销中的应用

服装销售人员常常根据消费者的外表特征来进行快速营销活动,以提高购买率。从数据挖掘技术的角度来探讨基于消费者外表印象的快速营销技术,以帮助营销人员快速寻找外表印象营销规则。介绍了决策树算法原理;其次,讨论了消费者外表印象评价指标体系,并根据该体系由销售人员在服装店铺里进行了消费者的外表及其行为数据采集;应用了计算实例来说明服装消费者的外表营销决策树分类模型;利用工具Clementine中的决策树方法来进行营销规则的挖掘。研究表明了该应用是切实可行的。     

Decision Tree Algorithm for Precision Marketing via Network Channel

With the development of e-commerce, more and more enterprises attach importance to precision marketing for network channels. This study adopted the decision tree algorithm in data mining to achieve precision marketing. Firstly, precision marketing and C4.5 decision tree algorithm were briefly introduced. Then e-commerce enterprise A was taken as an example. The data from January to June 2018 were collected. Four attributes including age, income, occupation and educational background were selected for calculation and decision tree was established to extract classification rules.The results showed that the consumers of the products of the company were high-income young and middle-aged people, middle-income young people, middle-income middle-aged and elderly people with a college degree or above, low-income middle-aged people with a college degree or above and low-income elderly people with a state-owned enterprise. After precision marketing to these customers, it was found that the monthly sales volume of the enterprise increased by 22.82% and the marketing cost decreased by 28.21%, which verified the effectiveness and application value of precision marketing and showed that the decision tree algorithm could provide enterprises with decision support in precision marketing.     

基于云计算的营销决策支持系统

设计并实施了一种基于云计算的营销决策支持系统,和其他管理决策子系统发生交互,共同构成了完整的现代企业经营决策支持系统.系统的数据库采用分布式设计,使得系统既有独立处理本地数据库的能力,也可读取异地数据库中的数据.系统模型库包含多种营销因素的决策模型,并采用模型组合的思想,将复杂的决策问题通过模型之间的组合来实现.在流程设计上充分考虑人机交互,将用户的经验判断纳入到决策过程中.完成了系统的开发,并用仿真数据进行了系统测试,结果表明系统基本运行稳定,各子模块衔接良好,与其他子系统实现了数据共享.     

基于J2EE电力营销决策支持系统的研究与实现

综合运用了J2EE、数据仓库、联机分析处理、数据挖掘等技术,建立了一个多层次分布式电力营销决策支持系统。该文阐述了该决策支持系统的体系结构,分析了从操作型数据库到数据仓库和数据集市的数据采集模式,实现了Winters模型、一元线性回归以及二元指数平滑等预测模型的设计,从而为电力营销活动提供了重要的决策支持。     

The effects of decision timing for pricing and marketing efforts in a supply chain with competing manufacturers

This paper investigates the impact of decision timing for pricing and marketing efforts in a supply chain led by competing manufacturers. We develop and solve six games to consider the scenarios (games) where prices and marketing efforts (ME) are decided simultaneously, and when they are not (i.e., ME is set either before or after prices). We examine these three scenarios for the benchmark case of a bilateral monopolistic channel, then extend the analysis to a supply chain with competing manufacturers. We identify the optimal decision timing by comparing equilibrium profits and strategies across games in each supply chain setup. We find that a monopolistic manufacturer always prefers that prices and ME be decided simultaneously. However, this result does not hold when product competition is taken into account. The optimal decision timing for competing manufacturers depends on the retailer's and manufacturers' ME effectiveness levels as well as on competition intensity. Specifically, when ME are not very effective, a simultaneous decision scenario is preferred because it provides the advantage of higher profit margins or sales. However, for highly effective ME, manufacturers prefer to decouple ME and pricing decisions. The retailer's optimal scenario is either to make all decisions simultaneously or to choose prices prior to ME. This means that supply chain firms can face conflict due to the decision timing for prices and ME.     

以贝叶斯网络为基础的决策分析系统在电力营销中的应用研究

将贝叶斯方法应用于电力营销决策,能够取得很多其他方法无法比拟的实际效果。介绍了贝叶斯网络与数据挖掘技术的相关概念,阐述了电力营销相关理论和存在的问题,提出了适合电力营销决策的贝叶斯网络,用于客户价值评估、用电异常监测等领域,并且论述了实现的方法和可能性。     

基于C5.0决策树算法的电力营销数据挖掘

为了对电力企业中不同部门的运行数据进行有效的挖掘,提出利用C5.0决策树算法对数据进行深层次分析,为管理人员提供有价值的决策支持.首先,对数据挖掘中先进的C5.0决策树算法原理进行分析,并通过引入信息熵对原有的属性选择方式进行改进,提高了信息增益比率计算的速度.然后根据设计的售电量关系模型进行对电厂管理信息系统中的数据...     

基于数据挖掘技术的营销模式

该文运用聚类分析、关联规则和决策树等数据挖掘技术,力图创新出以消费者为导向,以交叉销售为特征的一种新的营销模式。新的营销模式分运用聚类分析建立客户细分数据库、运用关联规则提取交叉规则和运用决策树技术识别目标客户三个步骤来实施。     

商务智能在企业营销分析系统中的应用研究

从技术的角度对商务智能的的基本概念、体系架构进行了讨论,给出了一个完整的营销决策分析系统构建方案,并对ECTL过程及数据仓库的查询优化进行了研究和实现。实际应用结果表明,企业利用现有系统中的信息数据,能大大提高企业对数据查询分析和决策分析的能力。     

Providing Websites with capabilities of one–to–one marketing

A formidable synergy can be obtained by putting expert system technology into the Internet. The modern trend of embedding expert systems into Websites turns out to be very promising, in particular for the field of marketing via the Web. The last two years have seen a growing interest in providing Websites with suitable embedded expert systems for one–to–one marketing. One–to– one marketing means marketing in a personalized way, i.e. marketing in a way that is adaptive to the personal needs of the user. A basic feature of this marketing framework consists in personalized prioritizing of news, i.e. presenting information in an order that is relevant to the specific needs of the current user. If the personalized prioritizing of news is a very useful feature in wired Web, it becomes essential in wireless Web, the promising next generation of the Web.
The paper presents a general methodology for personalized prioritizing of news. The methodology integrates decision theory with a deep–knowledge–based user model (i.e. causal knowledge linking user preferences to user goals). The deep–knowledge model of the user is a source of power of the methodology because it allows the system to know (and possibly explain) why the user acts the way he/she acts. Another relevant aspect of the methodology is that the burden of personalization is not placed on the user, and in fact the user does not have to declare his/her needs or interests or goals: they are automatically inferred from his/her profile data. In order to investigate the ideas underlying the proposal, a methodology example has been implemented in a prototype and then tested on real cases in the context of a supercomputing portal.