大数据时代消费者行为与精确营销研究

发布时间：2018-03-27 09:09

本文选题：大数据　切入点：数据挖掘　出处：《上海工程技术大学》2015年硕士论文

【摘要】：云计算、物联网、社交网络等新兴服务和技术的出现促使人类社会的数据种类和规模正以前所未有的速度增加和扩大,数据从简单的处理对象开始转变为一种基础性资源,如何更好地管理和利用大数据已经成为普遍关注的话题。同时,随着人们生活水平的提高,消费规模不断扩大,消费者个性化需求越来越明显。这就要求企业要制定新的营销策略来满足消费者需求。因此,本文以消费者行为研究为基础,探讨企业如何在当前的大数据时代,合理利用现代信息技术,重新审视消费者行为特征,制定出更为高效的精确营销策略。本文运用理论分析与实证研究相结合的方法,在精确营销理念的指导下,针对现代消费者特征选取消费者行为指标,进而利用数据挖掘技术探求基于消费者行为的精确营销策略。主要研究内容如下:第一,探讨了大数据对消费者行为和精确营销带来的影响。首先从宏观层面进行分析,说明大数据开启了时代转型,阐述了大数据给现代商业和管理带来的深刻影响和变革。在此基础上,分别分析了大数据对消费者行为和精确营销带来的影响,提出精确营销面临的机遇和挑战。第二,在对消费者行为与精确营销关系研究的基础上,构建基于消费者行为挖掘的精确营销理论模型,提出理论假设,并进行实证分析。这是本研究的核心部分,从消费者决策行为、购买行为和忠诚行为三方面进行分析,创造性的提出了消费者行为测度指标体系。并通过对多种数据挖掘方法的比较研究,最终选取了调查问卷、相关分析、回归分析等方法对模型进行假设检验,运用交叉分析的研究方法分析消费者特征对精确营销的影响。第三,在研究模型的基础上,从消费者决策行为、购买行为和忠诚行为三个方面进行分析,分别提出了不同的精确营销策略。本文综合考虑零售商、产品和消费者三个方面,对于传统型、复合型、现代型这三种不同类型的消费者,制定有针对性的精确营销策略。并在深入了解消费者需求的基础上,结合消费者特征对精确营销的影响研究,制定出基于消费者行为特征的精确营销策略。
[Abstract]:The emergence of new services and technologies, such as cloud computing, the Internet of things, and social networks, has led to an unprecedented increase and expansion of data types and scales in human society, from simple processing objects to a basic resource. How to better manage and utilize big data has become a topic of universal concern. At the same time, with the improvement of people's living standards, the scale of consumption continues to expand. The individualized demand of consumers is becoming more and more obvious. This requires enterprises to formulate new marketing strategies to meet the needs of consumers. Therefore, based on the study of consumer behavior, this paper discusses how enterprises can meet their needs in the current era of big data. Rational use of modern information technology, re-examine the characteristics of consumer behavior, formulate a more efficient and accurate marketing strategy. This paper uses the combination of theoretical analysis and empirical research, under the guidance of the concept of accurate marketing, According to the characteristics of modern consumers, select consumer behavior indicators, and then use data mining technology to explore the accurate marketing strategy based on consumer behavior. The main research contents are as follows: first, This paper discusses the influence of big data on consumer behavior and accurate marketing. First of all, it is analyzed from the macro level to show that big data has opened the transformation of the times. This paper expounds the profound influence and reform that big data has brought to modern business and management. On this basis, the paper analyzes respectively the influence of big data on consumer behavior and accurate marketing, and puts forward the opportunities and challenges that accurate marketing faces. On the basis of the research on the relationship between consumer behavior and accurate marketing, this paper constructs a theoretical model of accurate marketing based on consumer behavior mining, puts forward theoretical assumptions and carries out empirical analysis. This is the core part of this study, which is based on consumer decision-making behavior. This paper analyzes the purchase behavior and loyalty behavior, creatively puts forward the index system of consumer behavior measurement, and through the comparative study of various data mining methods, finally selects the questionnaire, correlation analysis, Regression analysis and other methods are used to test the hypothesis of the model, and the cross-analysis method is used to analyze the impact of consumer characteristics on accurate marketing. Thirdly, on the basis of the model, consumer decision-making behavior is analyzed. Three aspects of purchase behavior and loyalty behavior are analyzed, and different precise marketing strategies are put forward. Three different types of consumers, modern type, formulate targeted and accurate marketing strategies. On the basis of in-depth understanding of consumer needs, the impact of consumer characteristics on accurate marketing is studied. Make accurate marketing strategy based on consumer behavior characteristics.
【学位授予单位】：上海工程技术大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：F274;F713.55

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