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大数据营销全流程操作指南

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你想在大数据时代实现精准营销吗?请开始大数据营销之旅吧!
For Dummies是全世界知名的系列图书牌子,自诞生15年来受到全球数千万读者赞誉。
For Dummies系列图书的一大特色:能用通俗易懂的文字清晰阐述复杂的概念和主题。
For Dummies系列图书的优势:集结全球各领域专家,让你与智慧的头脑保持同步。
For Dummies系列图书的口号:让一切变得更简单!
前期准备——了解大数据营销的功能、开展营销活动的步骤和收集消费者数据的方法。
深度挖掘数据——了解数据分析过程中的注意事项,从而提高警惕并避免犯错。
利用数据正式开展营销活动——学会设计营销活动,使营销目标符合数据分析的结果。
吸取经验——探索如何设定测量和评估方案,以衡量营销活动的实际效果,并为未来的营销活动提供改进的建议。
Content Description

大数据时代,如果你还在传统营销的道路上缓步前行,那么你很快就会被其他企业甩在后面。为了步入新营销时代的快车道,你需要充分利用消费者数据,实现精准营销。消费者数据包含人口统计学数据、消费者行为特征数据、消费者位置数据等信息,它们是企业极具价值的资产。本书系统介绍了如何收集和分析消费者数据、如何利用已获取的数据进行营销、如何对营销活动的效果进行测量和分析,以及数据驱动营销的原则、方法和注意事项。无论你打算开拓新客户,还是提升老客户的忠诚度,这些都是你必须掌握的内容。可以说本书是一部系统、全面、实用性强的营销手册。

《大数据营销全流程操作指南》适合所有企业的营销人员、形象经理、广告策划人员、产品经理及企业的决策者阅读。翻开本书,你会看到很多新颖的例证、营销技巧和专家建议。这本书将会为你提供数据驱动营销指导,带你挖掘大数据时代潜在的市场与商机。
Author Description

大卫·塞莫尔罗斯(David Semmelroth),大数据营销顾问、数学与统计学教授。他参与了众多数据收集和处理技术的研发,这些技术可以更好地服务于商业领域。此外,在把消费者数据转化为可行的营销方案方面,大卫拥有20多年的工作及培训经验。
大卫的职业生涯开始于信息技术,他致力于研究消费者数据,试图从这些数据中洞察消费者的真实需求。他涉足的领域包括金融服务行业、旅游行业和娱乐行业,为众多企业提供消费者数据库和大数据营销方面的咨询服务。
《大数据营销全流程操作指南》是大卫对兴趣与工作经验的总结与延伸,也是将营销与技术相融合的杰作。他将通过此书为你提供大数据营销指导,带你挖掘大数据时代潜在的市场与商机。
Catalogue

第1章 大数据营销:一切为了客户 // 3
什么是大数据营销 // 4
聚焦客户 // 6
大数据营销活动 // 9
分析客户数据 // 11
测量结果 // 13
第2章 直接与客户沟通 // 15
什么是大数据营销活动 // 15
命中靶心:并不是每个人都是目标受众 // 19
定制优惠信息 // 21
直接与客户交谈:使用数据调整营销信息 // 22
找准营销时机:不要在 7 月卖雪铲 // 23
选对营销策略 // 23
精细化营销活动 // 26
第3章 以小见大:通过数据寻找客户 // 28
与消费者相关的营销数据库 // 28
建立客户记录 // 33
营销是一件家务事:从家庭开始 // 34
发展客户基础:潜在客户 // 36
尊重客户隐私 // 39
第4章 使用并管理客户联系信息 // 44
联系客户 // 44
允许客户自愿退出 // 48
了解客户偏好 // 51
第 1 部分 大数据营销入门
目 录
1
大数据营销全流程操作指南 2
第5章 获取信息:营销活动的基础 // 54
确保邮件能被有效投递 // 55
推广历史的重要性 // 59
通信管理的重要性 // 60
第6章 什么是数据分析 // 65
什么是统计 // 66
了解客户的差异性 // 67
在数据中寻找关系 // 71
营销活动本身也是实验:使用科学的方法 // 73
寻找重要的结果 // 75
结合客户特征进行多重任务处理 // 77
第7章 物以类聚:细分客户 // 79
理解人口数据 // 80
基于收入数据划分消费者 // 82
根据年龄对消费者进行分类 // 84
根据生命周期对消费者进行分类 // 86
根据地理数据对消费者进行分类 // 87
考虑法律因素能使你避免不必要的麻烦 // 90
第8章 从交易数据中获取重要信息 // 92
简化数据 // 93
来自网上的交易数据 // 96
基于交易数据划分消费者 // 98
时机就是一切:了解消费者的购买时间 // 101
RFM 模型 // 103
啤酒和尿布:购物篮分析 // 104
第 2 部分 深度挖掘数据:分析论63
目录 3
第 3 部分 让数据发挥作用
第9章 好的、坏的和丑的:了解客户盈利情况 // 106
营业额并不是净收益:要考虑成本问题 // 106
保持评估客户盈利能力的简单性 // 109
了解家庭层面的盈利能力 // 110
维系有利可图的客户 // 111
寻找新客户 // 112
应对无利可图的客户 // 112
了解客户盈利能力的变化 // 113
评估客户的终身价值 // 114
第10章 策略优势:设计营销活动 // 119
事件触发型活动 // 119
维系客户 // 123
对客户进行向上销售 // 132
对客户进行交叉销售 // 134
关注地址变更 // 136
第11章 从橱窗到柜台:变顾客为消费者 // 138
识别消费者 // 139
了解顾客的消费心理 // 143
克服购买障碍 // 145
第12章 精巧设计营销信息 // 149
让顾客听到你的声音 // 149
用技术来定制个性化邮件 // 152
在信件中使用图片 // 154
向消费者展示他们感兴趣的产品 // 156
利用消费者档案制作信息 // 156
117
大数据营销全流程操作指南 4
第 4 部分 反馈圈:从经验中学习173
第13章 在线使用顾客数据 // 159
电子邮件的诸多功能 // 160
为顾客提供优质的网上内容 // 165
在线识别顾客 // 167
顾客数据和搜索引擎 // 171
第14章 认知曲线:构建测试计划 // 175
运用统计方法 // 176
活动计划:事先决定你想学什么 // 177
采用随机样本 // 180
得到有意义的结果:样本规模取决于置信度 // 182
任务控制:使用控制组 // 185
失控:跳过控制的原因 // 187
第15章 触达底线:追踪并测量营销活动 // 189
你需要牢记的一点:明确定义回应 // 189
控制成本的一些常用指标 // 193
测量线上环境的营销效果 // 195
为营销活动设定价值 // 201
第16章 让专家开始工作吧:分析活动结果 // 204
测量和分类:数值型数据和类别数据 // 205
理解数值型变量 // 205
分析应答率的简单方法 // 207
分析回应数据的高级方法:统计模型 // 212
常用的应答模型技术 // 217
第17章 在企业内共享消费者数据 // 222
消费者数据与广告 // 223
市场调查 // 225
目录 5
237 第 5 部分 总结和建议
消费者数据与产品开发 // 227
消费者数据与定价策略 // 228
客户关系管理 // 230
消费者数据与法律 // 234
第18章 获取消费者数据的方法 // 239
通过会员卡识别消费者 // 239
优惠卡 // 240
利用优惠代码追踪交易 // 241
利用资讯手册识别潜在顾客 // 242
提供实物信息 // 242
鼓励网络注册 // 242
建立稳健的线上消费者档案 // 243
消费者数据和客服中心 // 244
销售点的消费者数据 // 244
购买消费者列表 // 244
购买人口数据 // 245
第19章 信息和协助的来源 // 246
加入美国直销协会 // 246
订阅行业刊物 // 247
使用普查数据 // 247
熟悉邮件 // 248
了解监管环境 // 248
雇用直销服务提供者 // 249
购买创意服务 // 249
整合消费者记录 // 250
第三方数据提供者 // 250
分析软件 // 251

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