面向双向O2O营销的客户行为分析
文献类型：学位论文
| 作者 | 袁双
|
| 学位类别 | 硕士 |
| 答辩日期 | 2016-05-25 |
| 授予单位 | 中国科学院沈阳自动化研究所 |
| 导师 | 吕赐兴 |
| 关键词 | 双向O2O营销模式 客户行为分析 潜在客户识别 交叉销售 |
| 其他题名 | Research of Customer Behavior Analysis Oriented Two-way O2O Marketing |
| 学位专业 | 控制工程 |
| 中文摘要 | 由于新型O2O营销模式的出现，客户的行为模式发生变化，客户行为不仅有线上行为还有线下行为。而目前的客户行为分析只注重于线上或线下的客户行为，缺乏把线上和线下的行为结合起来，刻画客户行为轨迹，用于指导线上和线下的精细化营销技术方面的研究。因此双向O2O服务模式下的客户行为分析应该结合线上行为和线下行为，盘活线下实体店客流，提高客户转化率。同时，由于家居行业的特殊性，客户当前价值保持以及增量购买等行为发生几率较小。根据双向O2O服务模式和家居行业客户生命周期特点，本文对客户的访问行为和客户交易记录行为进行分析，重点对潜在客户识别和交叉销售两方面进行深入的研究。论文的主要工作有：对面向双向O2O营销的客户行为分析的背景及其研究意义进行介绍，分析了客户行为研究及应用现状，详细介绍了家居行业的双向O2O云制造平台服务模式，并给出了客户行为分析在双向O2O模式下的应用和挑战。给出了双向O2O模式下的潜在客户识别的目标和基础，结合客户线上和线下行为，根据时间序列抽取客户访问行为数据作为潜在客户识别特征，运用改进的Adaboost算法对客户行为特征进行潜在客户识别。最后运用上述方法对某家居企业客户行为数据进行实例研究，并证明了该方法的有效性。双向O2O模式下的交叉销售实际上是发现关联产品。首先根据实际需求选取挖掘对象，并根据产品种类特点，对产品进行概念层次抽取，然后运用FP-growth算法挖掘频繁项集进而通过分析发掘关联产品。最后运用上述方法对某家居企业客户交易数据进行实例研究，并证明了该方法的有效性。根据客户行为分析需求，给出了客户行为分析系统的基本功能，并设计了系统的整体框架以及选取了开发平台和工具，最后结合上述客户行为分析模型实现了家居行业客户行为分析系统。论文最后对研究工作进行了总结并给出了下一步的研究方向。 |
| 英文摘要 | Due to the emergence of new O2O marketing mode, customer behavior patterns change and customer behavior is not only online behavior and offline behavior. And now the customer behavior analysis is only focused on online or offline customer behavior, and lacks the technology research. of combination of online and offline behavior to track customer behavior characterization, used to guide refinement of online and offline marketing. Therefore the customer behavior analysis of bidirectional O2O service mode should be combined with online and offline behavior to revitalize the offline passenger flow and improve customer conversion rate. At the same time, due to the particularity of household industry, customer current value maintaining and incremental purchase behavior are less likely to occur. Based on two-way O2O service mode and the characteristics of the household industry customer life cycle, this artcle accesses to customer behavior and customer transaction records behavior analysis, and focuses on two aspects of potential customers to identify and cross-selling. The main work has: This paper introduces background and research significance of customer behavior analysis oriented the bidirectional O2O marketing, analyzes customer behavior research and application status, introduces two-way O2O cloud manufacturing service platform model of the household industry, and gives the customer behavior analysis challenge in two-way O2O mode of application. This paper presents target and foundation of potential customers identification based bidirectional O2O mode, combines with the online and offline customer behavior, extracts client access behavior as a potential customer recognition feature according to the time sequence data, and uses the improved Adaboost algorithm to identify the potential customers for customer behavior features. Finally, this paper performs a case study with the method described above on some household enterprise customer behavior data and demonstrates the effectiveness of the method. Cross-selling of two-way O2O mode is actually to find related products. First, this paper select an mining object according to actual demand, extracts concept products according to characteristics of products, then uses FP-growth algorithm to min frequent itemsets and explores related products through analyzing. Finally, this paper performs a case study with the method described above on some household enterprise customer transaction data and demonstrates the effectiveness of the method. According to the requirements of customer behavior analysis, this paper gives the basic function of customer behavior analysis system, designes the overall framework of the system and selects the development platform and tools, finally achieves the household industry customer behavior analysis system according to the customer behavior analysis model . Finally, the paper summarizes the research work and gives the future research directions. |
| 语种 | 中文 |
| 产权排序 | 1 |
| 页码 | 62页 |
| 源URL | [http://ir.sia.cn/handle/173321/19656]  |
| 专题 | 沈阳自动化研究所_信息服务与智能控制技术研究室 |
| 推荐引用方式 GB/T 7714 | 袁双. 面向双向O2O营销的客户行为分析[D]. 中国科学院沈阳自动化研究所. 2016. |
入库方式： OAI收割
来源：沈阳自动化研究所
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