課程資訊
課程名稱
 大數據行銷
Big Data Marketing 
開課學期
 104-2 
授課對象
 共同教育中心  統計碩士學位學程  
授課教師
 任立中 
課號
 IB5082 
課程識別碼
 724 U4610 
班次
  
學分
 3 
全/半年
 半年 
必/選修
 選修 
上課時間
 星期一A,B,C(18:25~21:05) 
上課地點
 管一B01 
備註
 本課程為學程丙組(管理社會組)選修課程之一。與陳瑀屏合開
限學士班三年級以上
總人數上限：60人 
Ceiba 課程網頁
 http://ceiba.ntu.edu.tw/1042IB5082_ 
課程簡介影片
 
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課程概述

Database Marketing is a study of recent data/model-driven research in the academic marketing literature and in the practice of e-commerce. The perspective developed in Marketing Management, Statistical Decision Science, and Computer Science (esp. in Web Warehousing) provides a useful base for the investigation of research literature.  

課程目標
 The objectives of this course are the following:
1. Develop an awareness of the current level of understanding and state of research in several areas of database marketing study. It is hoped that pursuit of this goal will provide the student with a greater understanding of database marketing itself, as new questions are posed from the practice perspective.
2. Develop the ability to read and understand the current research literature. Pursuit of this goal will provide a familiarity with research procedure as it is applied to database marketing. This background should be very useful as the student begins to design and execute research program in the content of e-commerce.
 
課程要求
 CLASS SESSIONS
In each week, the class will be divided into two sessions. A Lecture Session will be given so that the students will get familiar with the ideas and methods related to the certain topics. A Panel Session will be followed and it will be discussion oriented with each student exploring ideas and questions proposed by others and exposing his/her own ideas and questions for investigation by others. Each session will focus on one topic area as indicated in the following class schedule. Discussion will center on the reading assignments, computer programming, and practice simulation. Each student is expected to have thought seriously about both the modeling and the marketing issues relevant to each piece. Every student is expected to participate in the discussion of all materials, and not just a "show and tell" for the article you reviewed.

LITERATURE PRESENTATION/DISCUSSION:
Great emphases will be placed on literature reviews in terms of grading. For the literature reviews grade, students will be evaluated at both group and individual level. In addition to oral presentation/discussion, each group is subject to submit a written report summarizing the discussion of the literature review. At the group level, the group’s performance will be evaluated based on the submitted written report. At the individual level, each student will peer-evaluate other group members’ performance based on his/her i) attendance in paper discussion; ii) preparation for paper preview and review; and iii) contributions to the discussions. The given group grade will be weighted based on individual grade. In other words, individual grade is the weighted group grade using peer-assessment as the weighting factor. This part of excise will count as 30% of the final mark. Students who voluntarily deliver their insights to the class will be given extra credit based on the quality of content, organization and clarity as part of the 10% class participation mark.

TERM PAPER

Each group (or student) will be required to turn in a typed formal research proposal designed to advance a major theoretical or methodological issue considered in this course. It is to be a proposal for research that can actually be carried out by you while you are in the MBA program. This proposal will be expected to include an up-to-date literature review and hypotheses (e.g. a better research framework or model), which follow directly from that literature review. In addition, a research design should be specified which provides a test of the implications of these hypotheses. A section on limitations may be advisable to treat weaknesses in the design as well as to incorporate changes or additions that would strengthen the design. A discussion section could be used to spell out the implications of the student’s proposed research for understanding marketing models and to suggest implications for further research. The paper will be due, with enough copies for distribution to the other members of the class, at the beginning of class on the 16th week (June 7). An oral defense of the proposal will be presented in class at the last session (June 14).

MIDTERM AND FINAL EXAM:
There are two exams during the semester, a midterm and a final exam. Each exam will comprise of 4 to 6 short essay questions. The short essay questions will focus on the various topics discussed throughout the semester. Therefore, in order to get a good mark, you should not limit yourself to those topics you presented in class, but also need to study the rest of the topics. The Midterm and the Final Exam will each count towards 20% of the final mark.
 
預期每週課後學習時數
  
Office Hours
  
指定閱讀
 COURSE SUPPLEMENT MATERIALS
1. Shugan, Steven M. (2006), “Save Research – Abandon the Case Method of Teaching,” Marketing Science, 25(2), 109-115.
2. Morgan, Michael S. (2001), “Research Boosts Database’s Power,” Marketing News, Oct 8, 2001, 16.
3. McKim, Bob (2002), “The Differences Between CRM and Database Marketing,” Journal of Database Marketing, Vol. 9 (4), 371-375.
4. Tapp, Alan (2001), “The Strategic Value of Direct Marketing: What Are We Good At? Part 1,” Journal of Database Marketing, Vol. 9 (1), p. 9-15.
5. Tapp, Alan (2002a), “The Strategic Value of Direct Marketing: Expanding Its Role Within the Company, Paper 2,” Journal of Database Marketing, Vol. 9 (2), p. 105-112.
6. Tapp, Alan (2002b), “Proactive or Reactive Marketing? The Influence of the Internet on Direct Marketing, Paper 3,” Journal of Database Marketing, Vol. 9 (3), p. 238-247.
7. Peltier, Schibrowsky, Schultz, and Davis (2002), “Interactive Psychographics: Cross-Selling in the Banking Industry,” Journal of Advertising Research, March/April, p. 7-22.
8. Wulf, Kristof De, Gaby Odekerken-Schröder, and Dawn Iacobucci (2001), “Investments in Customer Relationships: A Cross-Country and Cross-Industry Exploration,” Journal of Marketing, 65(4), 33-50.
9. Chandon, Pierre, Vicki G. Morwitz, and Werner J. Reinartz (2005), “Do Intentions Really Predict Behavior? Self-Generated Validity Effects in Survey Research,” Journal of Marketing, 69(2), 1-14.
10. Zack (1999), "Managing Codified Knowledge," Sloan Management Review, Summer, p. 45-58.
11. Jayachandran, Satish, Subhash Sharma, Peter Kaufman, and Pushkala Raman (2005), “The Role of Relational Information Processes and Technology Use in Customer Relationship Management,” Journal of Marketing, 69(4), 177-192.
12. Srinivasan, Raji and Christine Moorman (2005), “Strategic Firm Commitments and Rewards Customer Relationship Management in Online Retailing,” Journal of Marketing, 69(4), 193-200.
13. Miglautsch, John (2002), “Application of RFM Principles: What to Do with 1-1-1 Customers?” Journal of Database Marketing, Vol. 9(4), p.319-324.
14. Lewis, Michael (2005), “Incorporating Strategic Customer Behavior into Customer Valuation,” Journal of Marketing, 69(4), 230-238.
15. Ryals, Lynette (2005), “Making Customer Relationship Management Work: The Measurement and Profitable Management of Customer Relationships,” Journal of Marketing, 69(4), 252-261.
16. Verhoef, Peter C. (2003), “Understanding the Effect of Customer Relationship Management Efforts on Customer Retention and Customer Share Development,” Journal of Marketing, 67(4), 30-45.
17. Boulding, William, Richard Staelin, Michael Ehret, and Wesley J. Johnston (2005), “A Customer Relationship Management Roadmap: What is Known, Potential Pitfalls, and Where to Go,” Journal of Marketing, 69(4), 155-166.
18. Payne, Adrian and Pennie Frow (2005), “A Strategic Framework for Customer Relationship Management,” Journal of Marketing, 69(4), 167-176.
19. Allenby, Greg M., Lichung Jen, and Robert P. Leone (1996), “Economic Trends and Being Trendy: The Influence of Consumer Confidence on Retail Fashion Sales,” Journal of Business & Economic Statistics, 14(1), 103-111.
20. Allenby, Greg M., Neeraj Arora, and James L. Ginter (1998), “On the Heterogeneity of Demand,” Journal of Marketing Research, 35(3), 384-389.
21. Shugan, Steven M. (2006), “Errors in the Variables, Unobserved Heterogeneity, and Other Ways of Hiding Statistical Error,” Marketing Science, 25(3), 203-216.
22. Schmittlein and Peterson (1994), “Customer Base Analysis: An Industrial Purchase Process Application,” Marketing Science, 13(1), 41-67.
23. Jen, Lichung, Chien-Heng Chou, and Greg M. Allenby (2003), “A Bayesian Approach to Modeling Purchase Frequency,” Marketing Letters, 14(1), 5-20.
24. Jen, Lichung and Shih-Ju Wang (2002), Segmentation vs. Individualization: The Indisputable Role of Heterogeneity, Western Decision Sciences Institute, Thirty -First Annual Meeting, April 2-6, 2002, MGM Grand, Las Vegas, Nevada, USA. (Best Paper Award in Marketing Strategy and Management).
25. Reinartz, Werner J. and V. Kumar (2003), “The Impact of Customer Relationship Characteristics on Profitable Lifetime Duration,” Journal of Marketing, 67(1), 77-99.
26. Rust, Roland T., Katherine N. Lemon, and Valarie A. Zeithaml (2004), “Return on Marketing: Using Customer Equity to Focus Marketing Strategy,” Journal of Marketing, 68(1), 109-127.
27. Vorhies, Douglas W. and Neil A. Morgan (2005), “Benchmarking Marketing Capabilities for Sustainable Competitive Advantage,” Journal of Marketing, 69(1), 80-94.
28. Homburg, Christian, Nicole Koschate, and Wayne D. Hoyer (2005), “Do Satisfied Customers Really Pay More? A Study of the Relationship Between Customer Satisfaction and Willingness to Pay,” Journal of Marketing, 69(2), 84-96.
29. Mithas, Sunil, M. S. Krishnan, and Claes Fornell (2005), “Why Do Customer Relationship Management Applications Affect Customer Satisfaction?” Journal of Marketing, 69(4), 201-209.
30. Gustafssopm, Anders, Michael D. Johnson, and Inger Roos (2005), “The Effects of Customer Satisfaction, Relationship commitment Dimensions, and Triggers on Customer Retention,” Journal of Marketing, 69(4), 210-218.
31. Allenby, Leone, & Jen (1999), “A Dynamic Model of Purchase Timing with Application to Direct Marketing,” Journal of the American Statistical Association, Vol. 93 (June), p.365-374.
32. Venkatesan, Rajkumar and V. Kumar (2004), “A Customer Lifetime Value Framework for Customer Selection and Resource Allocation Strategy,” Journal of Marketing, 68(4), 106-125.
33. Lemon, Katherine N., Tiffany Barnett White, and Russell S. Winer (2002), “Dynamic Customer Relationship Management: Incorporating Future Considerations into the Service Retention Decision,” Journal of Marketing, 66(1), 1-14.
34. Jen, Lichung, Chien-Heng Chou, and Greg M. Allenby, “A Bayesian Approach to Integrating the Interpurchase Time and the Purchase Amount in Customer Portfolio Analysis,” Working paper, National Taiwan University.
35. Johnson, Michael and Fred Selnes (2004), “Customer Portfolio Management: Toward a Dynamic Theory of Exchange Relationships,” Journal of Marketing, 68(2), 1-17.
36. Chen, Ching-I (2005), “When and How Many to Buy: A Hierarchical Bayesian Forecasting Model Incorporating Latent Consumption Rates,” Journal of Marketing Science, 1(1), 5-22. 
參考書目
 Textbook
1. 任立中(2010)，行銷源典，前程文化。
2. Blattberg, Robert C., Byung-Do Kim, and Scott A. Neslin (2008), Database Marketing: Analyzing and Managing Customers, Springer, New York, NY.
3. Aaker, David A., V. Kumar, George S. Day, and Robert P. Leone (2011), Marketing Research, 10th edition, John Wiley & Sons, Inc. (雙葉書局)

Reference Books
1. Rossi, Peter E., Greg Allenby, and Rob McCulloch (2005), Bayesian Statistics and Marketing, John Wiley and Sons, New York, NY.
2. Leeflang, Peter S.H., Dick R. Wittink, Michel Wedel, and Philippe A. Naert (2000), Building Models for Marketing Decisions, Lower Academic Publishers, Norwell, MA.
3. Blattberg, Robert C., Gary Getz, and Jacquelyn S. Thomas (2001), Customer Equity: Building and Managing Relationships as Valuable Assets, Harvard Business School Press, Boston, Massachusetts.
4. Lilien, Gary L. and Arvind Rangaswamy (2003), Marketing Engineering: Computer- Assisted Marketing Analysis and Planning, Pearson Education, NJ.
5. Koch, Richard (1998), The 80/20 Principle: The Secret of Achieving More with Less, Doubleday, New York, NY.

Articles from:
Journal of Database Marketing
Journal of Marketing Research
Journal of Marketing
Marketing Science
Sloan Management Review
Journal of the American Statistical Association
Selected Master Theses or Doctorial Dissertations and other journals
 
評量方式
(僅供參考)
  
No.
項目
百分比
說明
1. 
 Group Presentation and Written Report 
20% 
  
2. 
 Contribution to Class Discussion (extra credit) 
10% 
  
3. 
 Term Paper 
30% 
 due on June 13 and Presentation on June 20 
4. 
 Final Exam  
20% 
 in class on June 20 
5. 
 Midterm Exam  
20% 
 in class on April 18 
 
課程進度
週次
日期
單元主題
第1週
 2/22  Lecture:
(1) The Course Philosophy, Structure, and Policy
(2) The Paradigm Shift in Modern Marketing Thoughts
The Heterogeneous and Dynamic in Consumer Behavior
Satisfy Consumer Needs – Reactive Marketing Paradigm
Shape Consumer Needs – Proactive Marketing Paradigm
Customize Consumer Needs – Interactive Marketing Paradigm
Individualize Consumer Needs – Chain-Reactive Marketing Paradigm
(3) Group assignments and free discussion
Homework Assignment:
(1) Wulf, Kristof De, Gaby Odekerken-Schroder, and Dawn Iacobucci (2001), “Investments in Customer Relationships: A Cross-Country and Cross-Industry Exploration,” Journal of Marketing, 65(4), 33-50. 
第2週
 2/29  National Holiday (No class) 
第3週
 3/7  Lecture:
(1) Strategic Planning in Database Marketing
(2) Organizing for Database Marketing (BKN 3)
The Customer-Centric Organization
Processes for Managing Information: Knowledge Management
(3) Customer Privacy and Database Marketing (BKN 4)
Customer Attitudes Toward Privacy
Current Practices Regarding Privacy
Potential Solutions to Privacy Concerns
(4) Sources of Data (BKN 8)
Types of Data for Describing Customers
Sources of Customer Information
Group (1) Presentation: Wulf, Odekerken-Schröder, and bucci (2001)
Homework Assignment:
(2) Chandon, Pierre, Vicki G. Morwitz, and Werner J. Reinartz (2005), “Do Intentions Really Predict Behavior?Self-Generated Validity Effects in Survey Research,” Journal of Marketing, 69(2), 1-14.
 
第4週
 3/14  Lecture:
(1) Data Collection and Questionnaire Design
Survey Methods
Measurements
Questionnaire Design
(2) Test Design and Analysis (BKN 9)
Sampling Techniques
Determining the sample size
Test Designs
Group (2) Presentation: Chandon, Morwitz, and Reinartz (2005)
Homework Assignment:
(3) Allenby, Greg M., Lichung Jen, and Robert P. Leone (1996), “Economic Trends and Being Trendy: The Influence of Consumer Confidence on Retail Fashion Sales,” Journal of Business & Economic Statistics, 14(1), 103-111. 
第5週
 3/21  Lecture:
(1) The Predictive Modeling Process (BKN 10)
Predictive Modeling and the Quest for Marketing Productivity
The Predictive Modeling Process: Overview the Process in Detail
A Predictive Modeling Example
Long-Term Considerations
(2) Statistical Issues in Predictive Modeling (BKN 11)
Ecnomic Justification for Building a Statistical Model
Selection of Variables and Models
Treatment of Missing Variables
Evaluation of Statistical Models
Concluding Note: Evolutionary Model-Building
Group (3) Presentation: Allenby, Jen, and Leone (1996).
Homework Assignment:
(4) Colombo, Richard and Weina Jiang (1999), “A Stochastic RFM Model,” Journal of Interactive Marketing, 13(3), 2-12. 
第6週
 3/28  Lecture:
(1) FRM Analysis (BKN 12)
The Basics of the RFM Model
Definition of Recency, Frequency, and Monetary Value
RFM for Segment-Level Prediction
Breakeven Analysis: Determining the Cutoff Point
Profit Maximizing Cutoff Response Probability
Heterogeneous Order Amounts
Extending the RFM Model
Treating the RFM Model as ANOVA
Alternative Response Models Without Discretization
(2) Marketing Basket Analysis (BKN 13)
Deriving Market Basket Association Rules
Setup of a Market Basket Problem
Deriving "Interesting" Association Rules
Zhang (2000) Measures of Association and Dissociation
Issues in Market Basket Analysis
Using Taxonomies to Overcome the Dimensionality Problem
Association Rules for More than Two Items
Adding Virtual Items to Enrich the Quality of the Market Basket Analysis
Adding Temporal Component to the Market Basket Analysis
Group (4) Presentation: Colombo and Jiang (1999)
Homework Assignment:
(5) Ansari, Asim, Skander Essegaier, and Rajeev Kohli (2000), “Internet Recommendation Systems,” Journal of Marketing Research, 37 (August), 363–75.
 
第7週
 4/4  National Holiday (No class) 
第8週
 4/11  Lecture:
(1) Profiling and Cloning Customers (BKN 16)
The Clustering Process
Applying Cluster Analysis
(2) Targeting the Best/Right Customers (BKN 17)
Fundamentals of Decision Trees
Finding the Best Splitting Rule
Finding the Right Sized Tree
Other Issues in Decision Trees
Application to a Direct Mail Offer
Strengths and Weaknesses of Decision Trees
Group (5) Presentation: Ansari, Essegaier, and Kohli (2000)
Homework Assignment:
(6) Jen, Lichung, Chien-Heng Chou, and Greg M. Allenby (2003), “A Bayesian Approach to Modeling Purchase Frequency,” Marketing Letters, 14(1), 5-20.
 
第9週
 4/18  Midterm Exam (25%)  
第10週
 4/25  Lecture:
(1) Collaborative Filtering (BKN 14)
Introduction
Memory-Based Methods
Model-Based Methods
Current Issues in Collaborative Filtering
(2) Discrete Dependent Variables (BKN 15)
Binary Response Model
Linear Probability Model
Binary Logit and Probit Models
Logistic Regression with Rare Events Data
Discriminant Analysis
Multinomial Response Model
Models for Count Data
Poisson Regression
Negative Binomial Regression
Censored Regression (Tobit) Models and Extensions
Group (6) Presentation: Jen, Chou, and Allenby (2003)
Homework Assignment:
(7) Allenby, Greg M., Robert P. Leone, and Lichung Jen (1999), “A Dynamic Model of Purchase Timing with Application to Direct Marketing,” Journal of the American Statistical Association, 93 (June), 365-374.
 
第11週
 5/2  Lecture:
(1) Lecturing Bayesian Statistical Decision Analysis
Review Classical Statistics
Distribution Theory
Bayes Theorem and Inferences
Hierarchical Bayes Models
Group (7) Presentation: Allenby, Leone, and Jen (1999)
Homework Assignment:
(8) Jen, Lichung, Demetrios Vakratsas, and Wei-Lin Wang (2009). "Regular and Irregular Purchase Timing Behaviors," working paper, National Taiwan University.
 
第12週
 5/9  Lecture:
(1) Purchase Timing Models and Duration (Hazard) Models (BKN 15)
Characteristics of Duration Data
Analysis of Duration Data Using a Classical Linear Regression
Hazard Models
Incorporating Covariates into the Hazard Function
(2) Patterns in Time Series
(3) Dependency Derivation
Group (8) Presentation: Jen, Vakratsas, and Wang (2009)
Homework Assignment:
(9) Jen, Lichung, Chien-Heng Chou, and Greg M. Allenby (2009), "The Importance of Modeling Temporal Dependence of Timing and Quantity in Direct Marketing," Journal of Marketing Research, 46(4), 482-493.
 
第13週
 5/16  Lecture:
(1) Customer Lifetime Value: Fundamentals (BKN 5)
Mathematical Formulation of LTV
The Two Primary LTV Models: Simple Retention and Migration
LTV Models that Include Unobserved Customer Attrition
Estimating Revenues
Group (9) Presentation: Jen, Chou, and Allenby (2009)
Homework Assignment:
(10) Venkatesan, Rajkumar and V. Kumar (2004), “A Customer Lifetime Value Framework for Customer Selection and Resource Allocation Strategy,” Journal of Marketing, 68(4), 106-125.
 
第14週
 5/23  Lecture:
(1) Issues in Computing Customer Lifetime Value (BKN 6)
Discount Rate and Time Horizon
Customer Portfolio Management
Cost Accounting Issues
Incorporating Marketing Response
Incorporating Externalities
(2) Customer Lifetime Value Applications (BKN 7)
Using LTV to Target Customer Acquisition
Using LTV to Guide Customer Reactivation Strategies
Using SMC's Model to Value Customers
A Case Example of Applying LTV Modeling
Segmentation Methods Using Variants of LTV
Drivers of the Components of LTV
Forecasting Potential LTV
Valuing a Firm's Customer Base
Group (10) Presentation: Venkatesan and Kumar (2004)
Homework Assignment:
(11) Rust, Roland T., Katherine N. Lemon, and Valarie A. Zeithaml (2004), “Return on Marketing: Using Customer Equity to Focus Marketing Strategy,” Journal of Marketing, 68(1), 109-127.

 
第15週
 5/30  Lecture:
(1) Acquiring Customers (BKN 20)
The Fundamental Equation of Customer Equity
Acquisition Costs
Strategies for Increasing Number of Customers Acquired
Developing a Customer Acquisition Program
Research Issues in Acquisition Marketing
(2) Cross-Selling and Up-Selling (BKN 21)
The Strategy
Cross-Selling Models
Up-Selling
Developing an Ongoing Cross-Selling Effort
(3) Frequency Reward Programs (BKN 22)
How Frequency Reward Programs Influence Customer Behavior
Do Frequency Reward Programs Increase Profits in a Competitive Environment?
Frequency Reward Programs Design
Frequency Reward Programs Examples
(4) Customer Tier Programs (BKN 23)
Design Customer Tier Programs
Examples of Customer Tier Programs
Risks in Implementing Customer Tier Programs
Group (11) Presentation: Rust, Lemon, and Zeithaml (2004)
Homework Assignment:
(12) Gustafssopm, Anders, Michael D. Johnson, and Inger Roos (2005), “The Effects of Customer Satisfaction, Relationship commitment Dimensions, and Triggers on Customer Retention,” Journal of Marketing, 69(4), 210-218.
 
第16週
 6/6  Lecture:
(1) Churn Management (BKN 24)
Factors that Cause Churn
Predicting Customer Churn
Managerial Approaches to Reducing Churn
(2) Multichannel Customer Management (BKN 25)
The Emergence of Multichannel Customer Management
The Multichannel Customer
Developing Multichannel Strategies
Industry Examples
(3) Acquisition and Retention Management (BKN 26)
Modeling Acquisition and Retention
Optimal Acquisition and Retention Spending
Acquisition and Retention Budget Planning
Acquisition and Retention Strategy: An Overall Framework
Group (12) Presentation: Gustafssopm, Johnson, and Roos (2005)
Homework Assignment:
(13) Homburg, Christian, Nicole Koschate, and Wayne D. Hoyer (2005), “Do Satisfied Customers Really Pay More? A Study of the Relationship Between Customer Satisfaction and Willingness to Pay,” Journal of Marketing, 69(2), 84-96.
(14) Boulding, William, Richard Staelin, Michael Ehret, and Wesley J. Johnston (2005), “A Customer Relationship Management Roadmap: What is Known, Potential Pitfalls, and Where to Go,” Journal of Marketing, 69(4), 155-166.
 
第17週
 6/13  Lecture:
(1) Database Marketing Communications (BKN 27)
The Planning Process
Setting the Overall Plan
Developing Copy
Selecting Media
Evaluating Communications Programs
(2) Multiple Campaign Management (BKN 28)
Dynamic Response Phenomena
Optimal Contact Models
(3) Pricing (BKN 29)
Overview -- Customer-based Pricing
Customer Pricing when Customers Can Purchase Multiple One-Time Products from the Firm
Pricing the Same Products/Services to Customers over Two Periods
Acquisition and Retention Pricing Using the Customer Equity Model
Pricing to Recapture Customers
Pricing Add-on Sales
Price Discrimination Through Database Targeting Models
Group (13) Presentation: Homburg, Koschate, and Hoyer (2005)
Group (14) Presentation: Boulding, Staelin, Ehret, and Johnston (2005)
 
第18週
 6/20  Term Paper Presentation and Final Exam
You must each read and be prepared to discuss each student’s written research proposal. Each proposal writer is expected to briefly present key aspects of the proposal, explain its contribution and respond to questions, criticisms and suggestions.