随着中国改革开放，我国民航产业发展迅猛，民航战略地位愈发重要。民航基础 设施建设进一步完善，各地通航能力进一步增强，我国民航年旅客运输量持续以两位 数增量形式高速发展。作为民航产业的核心，我国各航空公司的利润近年却出现断崖 式下滑。A公司是我国一家地方性航空公司，在我国属于中型航空公司规模。A公司 在日常生产经营中面临两大营销难题：产品及服务同质化严重；销售成本高。要解决 这两大营销难题，就必须推行精准营销。 科学合理的客户细分，是认识客户的核心，是A公司实施精准营销的基础。本文 充分调研客户细分及精准营销理论，结合民航业及A公司实际情况及特点，对RFM模 型进行改进；优选k-means聚类算法，对A公司客户进行细分；基于客户细分结果， 最终为A公司制定一套精准营销策略，从而帮助A公司控制销售成本，优化营销资源 配置，提高营销效率，解决其生产经营难题。 本文的主要创新在于提出了一种适用于民航业的改进的RFMD模型，是民航业对 客户价值认识的一种尝试，也为后续研究提供了新的思路。 关键词：RFM模型；客户价值；客户细分；精准营销 Abstract III Abstract With China's reform and opening up, China's civil aviation industry is developing rapidly, and the strategic position of civil aviation is becoming more and more important. The construction of civil aviation infrastructure has been further improved, and the capacity of navigation has been further enhanced. The annual passenger traffic of civil aviation in China continues to develop at a high speed in the form of double-digit increment. As the core of the civil aviation industry, the profits of our airlines have declined in recent years. Company A is a local airline in China, which belongs to the scale of medium-sized airlines. A company faces two major marketing problems in its daily production and operation: serious homogenization of products and services and high cost of sales. To solve these two marketing problems, we must carry out precision marketing. This paper sufficiently investigates customer segmentation and precision marketing theory, combines the actual situation and characteristics of civil aviation industry and A company, improves RFM model, and optimizes K-means clustering algorithm for subdivision, and ultimately formulates a set of precise marketing strategy for A company, so as to help A company control sales costs, optimize marketing resource allocation, improve marketing efficiency, and solve its production and operation problems. The main innovation of this paper is to propose an improved RFMD model suitable for civil aviation industry, which is an attempt of civil aviation industry to understand customer value, and also provides a new idea for subsequent research. Key words: RFM Model；Customer Value；Customer Segmentation；Precision Marketing 西南科技大学硕士学位论文 IV 目 录 摘要 .......................................................................................................................................... 1 Abstract .................................................................................................................................III 目 录 ................................................................................................................................ IV 1绪论 ....................................................................................................................................... 1 1.1 研究背景 ................................................................................................................... 1 1.2 研究目的及意义 ....................................................................................................... 3 1.3 文献综述 ................................................................................................................... 3 1.3.1 客户关系管理理论 ........................................................................................ 3 1.3.2 客户细分理论 ................................................................................................ 4 1.3.3 客户价值 ........................................................................................................ 5 1.3.4 精准营销 ........................................................................................................ 8 1.4 研究内容及结构安排 ............................................................................................... 9 1.5 研究方法 ................................................................................................................. 10 1.6 研究创新点 ............................................................................................................. 10 2 第二章 A公司常旅客精准营销问题 .............................................................................. 11 2.1 模糊粗放的客户细分模式 ..................................................................................... 11 2.2 技术支撑薄弱 ......................................................................................................... 12 2.3 精准营销理念及体系问题 ..................................................................................... 13 2.4 核心竞争力匮乏 ..................................................................................................... 13 3改进的RFMD模型 ........................................................................................................... 15 3.1 RFMD模型 .............................................................................................................. 15 3.2 RFMD指标权重分析 .............................................................................................. 16 3.2.1 构造判断矩阵 .............................................................................................. 17 3.2.2 计算RFMD权重 ......................................................................................... 18 3.2.3 一致性检验 .................................................................................................. 19 4 A公司常旅客客户细分 ..................................................................................................... 20 4.1 数据准备 ................................................................................................................. 20 4.2 数据预处理 ............................................................................................................. 20 4.3 客户价值计算 ......................................................................................................... 21 4.3.1 RFMD模型赋权 ........................................................................................... 21 4.3.2 RFMD指标原始值计算 ............................................................................... 21 4.3.3 RFMD指标标准值计算 ............................................................................... 22 4.3.4 A公司常旅客客户价值计算结果 ............................................................... 23 4.4 K-MEANS聚类算法实施 ....................................................................................... 23 4.4.1 聚类算法理论基础 ...................................................................................... 23 目录 V 4.4.2 K-MEANS聚类算法优缺点 ........................................................................ 25 4.4.3 相似性度量 .................................................................................................. 25 4.4.4 聚类完成条件 .............................................................................................. 26 4.4.5 A公司常旅客客户聚类实施 ....................................................................... 26 4.4.6 客户细分结果及细分客户特征 .................................................................. 27 5基于客户细分的精准营销策略 ......................................................................................... 30 5.1关联策略 .................................................................................................................. 30 5.2客户关系策略 .......................................................................................................... 31 5.3快速反应策略研究结论 .................................................................................