WHERE FUTURE BEGINS
  • ṢELF ḌEEP ḶEARNING
  • LSE MBA Essentials - The London School of Economics
    • Leading with influence
    • Economics for managers
    • Competitive strategy
    • Corporate strategy
    • Financial accounting
    • Management accounting
    • Analysing financial statements
    • In the mind of the manager
    • Nudging behaviour
    • Organisational culture as a leadership tool
  • Business Foundations Specialization - Wharton Online
    • Introduction to Marketing
      • BRANDING: Marketing Strategy and Brand Positioning
      • Marketing 101: Building Strong Brands Part I
      • Marketing 101: Building Strong Brands Part II
      • Strategic Marketing
      • Segmentation and Targeting
      • Brand Positioning
      • Brand Mantra: The Elevator Speech
      • Experiential Branding
      • CUSTOMER CENTRICITY: The Limits of Product-Centric Thinking
      • Cracks in the Product-Centric Approach
      • Data-Driven Business Models
      • Three Cheers for Direct Marketing
      • Which Firms Are Customer Centric?
      • What is Customer Centricity?
      • Living in a Customer-Centric World
      • More Reflections on Customer CentricityPrev
      • Questions on Customer Centricity
      • GO TO MARKET STRATEGIES: Online-Offline Interaction
      • Online/Offline Competition
      • Friction
      • The Long Tail Theory
      • Preference Isolation
      • How Internet Retailing Startups Grow
      • Customers and Digital Marketing
      • Influence and How Information Spreads
      • Pricing Strategies
      • The 7M
      • BRANDING: Effective Brand Communications Strategies and Repositioning Strategies
      • Brand Messaging & Communication
      • Brand Elements: Choosing a Brand Name
      • Brand Elements: Color & Taglines
      • Brand Elements: Packaging
      • Brand Elements: Persuasion
      • Repositioning a Brand
    • Introduction to Financial Accounting
      • 1.1.1: Financial Reporting Overview
      • 1.1.2: Financial Reporting Example
    • Managing Social and Human Capital
      • Professor Cappelli and Professor Useem Introductions
    • Introduction to Corporate Finance
      • Time Value of Money
      • Intuition and Discounting
      • Compounding
      • Useful Shortcuts
      • Taxes
      • Inflation
      • APR and EAR
      • Term Structure
      • Discounted Cash Flow: Decision Making
      • Discounted Cash Flow Analysis
      • Forecast Drivers
      • Forecasting Free Cash Flow
      • Decision Criteria
      • Sensitivity Analysis
      • Return on Investment
    • Introduction to Operations Management
    • Wharton Business Foundations Capstone
  • Artificial Intelligence Career Program - deeplearning.ai
    • Machine Learning
      • Introduction to Machine Learning
      • Supervised Learning
      • Unsupervised Learning
      • Model Representation - Linear Regression
      • Cost Function
      • Gradient Descent
      • Gradient Descent For Linear Regression
      • Linear Algebra
    • Deep Learning
    • Neutral Networks and Deep Learning
      • Introduction to Deep Learning
      • What is a neural network?
      • Supervised Learning with Neural Networks
      • Why is Deep Learning taking off?
      • About this Course
      • Binary Classification
      • Logistic Regression
      • Gradient Descent
      • Derivatives
      • Computation graph
      • Derivatives with a Computation Graph
      • Logistic Regression Gradient Descent
      • Vectorization
      • Vectorizing Logistic Regression
      • Vectorizing Logistic Regression's Gradient Output
      • Broadcasting in Python
      • A note on python/numpy vectors
      • Explanation of logistic regression cost function (optional)
      • Neural Networks Overview
      • Neural Network Representation
      • Computing a Neural Network's Output
      • Vectorizing across multiple examples
      • Activation functions
      • Derivatives of activation functions
      • Gradient descent for Neural Networks
      • Backpropagation intuition (optional)
      • Random Initialization
      • Deep L-layer neural network
      • Forward Propagation in a Deep Network
      • Getting your matrix dimensions right
      • Why deep representations?
      • Building blocks of deep neural networks
      • Forward and Backward Propagation
      • Parameters vs Hyperparameters
      • What does this have to do with the brain?
    • Convolutional Neural Networks
      • Computer Vision
      • Edge Detection Example
      • Padding
      • Strided Convolutions
      • Convolutions Over Volume
      • One Layer of a Convolutional Network
      • Simple Convolutional Network Example
      • Pooling Layers
      • CNN Example - Fully Connected Layers
      • Why Convolutions?
    • Neural Network Theory [ETH]
    • Natural Language Processing
    • Computer Vision
  • IBM Data Science Professional Certificate
    • What is Data Science?
    • Open Source tools for Data Science
    • Data Science Methodology
    • Python for Data Science and AI
    • Databases and SQL for Data Science
    • Data Analysis with Python
    • Data Visualization with Python
    • Machine Learning with Python
    • Applied Data Science Capstone
  • Data Analytics
    • Python for Data Analysis
    • Data Structure and Algorithms
  • Programming Language
    • Python
    • R
    • SQL
    • C++
    • C
    • Java
    • HTML
  • 机器学习工程师
  • 商业数据分析
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  1. Business Foundations Specialization - Wharton Online
  2. Introduction to Marketing

Data-Driven Business Models

数据驱动的商业模式

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Last updated 5 years ago

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我想介绍几个利用了 信息技术和 顾客数据的公司 （这些公司）产生了与以产品为中心截然不同的商业模式 我想和你们分享的两个案例分别是Harrah's 美国的连锁赌场 以及Tesco 英国的连锁食品杂货零售商 在许多方面 这些案例都非常相似 尽管事实上这些公司 不同的地域经营不同的业务 这两个案例的企业 都曾在竞争中受挫 他们并没有像其竞争对手那样规模庞大 而且没有足够的资源 去进行以产品为中心的肉搏战 因此它们转向研究数据 它们通过深入了解消费者从而得出洞察 并使自己的商业模式配合作出改变 这实际上帮助他们爬升到行业的顶端 首先让我们谈谈美国的Harrah's连锁赌场 它面对其他财宏势大的连锁竞争者时 曾经处境艰难 对harrah's而言 要开发有竞争力 的肉搏战产品和服务是困难的 因此 Harrah's 转向了数据 专门开发了 一套神奇的忠诚计划 现在许多公司都有忠诚计划 但是 但他们没几个能够 得到Harrah's那样可行的洞察 客户在干什么的颗粒度 不仅了解他们在玩哪个博彩游戏 还包括他们在吃什么 偏爱何种风格的房间 在找什么样的娱乐项目 并能理解顾客何时可能改变他的行为 何时他可能会离开赌桌 改变哪些方面从而改善情况 在何时通过何种渠道提供什么样的信息和提议 来为顾客创造和获得更大的价值 Harrah's只是极为擅长挖掘这些洞察 例如某个顾客的消费临界值是多少 如果这个顾客下了150刀的注 就是时候进行干预了 是时候向他提供一顿饭或者 其他活动来使他们感觉很棒 但同样重要的是要清零他们的心理账户 当他们再次回到位置上时 他们的心理账户重新清零 Harrah's 十分精明地理解这类信息 而Tesco的故事十分相似 又一次

在英国Tesco曾与其他连锁食品杂货商陷入激烈竞争 Sansbury Morrisons 等等 他们转而研究数据 并开发了OLC项目 他们通过一些非常聪明的方式 了解其客户 他们 哪些家庭会从Tesco购买大量食材和其他产品 而哪些家庭不会 具体到哪一类产品小型家庭 是不会在Tesco购买的 因此Tesco知道哪些优惠券应该何时送给哪些家庭 使得他们在Tesco购买更多的东西 这不仅帮助它依靠这些家庭获得业务增长 同时帮助它更有效地竞争 因此当沃尔玛买入一条小连锁线进入英国时 Tesco知道哪些客户是最容易受到影响从而转投沃尔玛 并且有哪些产品他们可能会从沃尔玛买 因此Tesco再次懂得哪些优惠券在什么时间应该发送到哪些家庭 以此来抓住这些客户 巩固业务 因此通过了解其消费者 Tesco成功地防御了沃尔玛的入侵 稳坐英国的食品杂货行业龙头 这两个案例只是 数据转型企业中的沧海一粟 他们转向通过数据来提供优质产品和服务 真正地通过大量的数据 和对顾客的深刻理解 为了将他们的商业模式转化为一种 仅仅通过商品和服务永远不能达成的形式 [背景音乐] 翻译: RyukaSuu |审阅: 19waa Coursera Global Translator Community