Serial Number
60363
Course Number
IB5082
Course Identifier
724 U4610
No Class
- 3 Credits
Elective
DEPARTMENT OF INTERNATIONAL BUSINESS / GRADUATE INSTITUTE OF INTERNATIONAL BUSINESS / Business Analytics Program / Master Program in Statistics of National Taiwan University / Branding and Customer Management Program
DEPARTMENT OF INTERNATIONAL BUSINESS
GRADUATE INSTITUTE OF INTERNATIONAL BUSINESS
Business Analytics Program
Master Program in Statistics of National Taiwan University
Branding and Customer Management Program
Elective- LICHUNG JEN
- View Courses Offered by Instructor
COLLEGE OF MANAGEMENT DEPARTMENT OF INTERNATIONAL BUSINESS
lichung@ntu.edu.tw
- 管理 學院 二號館 8 樓 804 室
02-33664983
- 現 職: 國立臺灣大學管理學院全球品牌與行銷研究中心 主任 國立臺灣大學管理學院國際企業學系暨研究所 行銷教授 靜宜大學資深策略 副校長 靜宜大學國際學院 院長 台灣行銷科學學會 理事長 中華應用統計學會 理事長 榮 譽: 榮獲台灣大學99學年度(國科會補助)獎勵特殊優秀研究人員獎 榮獲CMO Asia & CMO Council, USA. 2012年第3屆亞洲最佳商學院獎最佳行銷教授獎 著 作: 『行銷源典:任意行銷首部曲』 『統計學:管理者必備的修煉』 『行銷研究:發展有效行銷策略之基石』 『逐鹿全球:新世代台商戰略4.0』 『大數據戰略4.0』 『大數據行銷:邁向智能行銷之路』 譯 作: 『新東協 新思路:啟動未來經濟引擎的關鍵』 『行銷人攀越的7個頂峰:決策導向分析法』 『數位消費時代之競爭力行銷』
- Mon A, B, C
BLDG. 1 COLLEGE OF MANAG.1F Room101 (管一101)
Type 2
120 Student Quota
NTU 110 + non-NTU 10
No Specialization Program
- Chinese
- NTU COOL
- Core Capabilities and Curriculum Planning
- Notes、 CHUAN FENG SHIH合授
- Limits on Course Adding / Dropping
Restriction: juniors and beyond
NTU Enrollment Status
Loading...- Course DescriptionBig Data 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. the Big Data in Web Warehousing) provides a useful base for the investigation of research literature.
- Course ObjectiveThe 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 big data marketing. This background should be very useful as the student begins to design and execute research program in the content of e-commerce.
- Course RequirementCOURSE PREREQUISITES: 1. Marketing Management 2. Statistics
- Expected weekly study hours after class4 hours
- Office Hour
2/19, 4/8, 6/3 (In class)
*This office hour requires an appointment - Designated ReadingCOURSE METERIALS: Textbook 1. 任立中,陳靜怡(2019),大數據行銷:邁向智能行銷之路 (BIG DATA MARKETING: THE ROAD TO AI MARKETING),前程文化,臺北市。
- ReferencesReference Books 1. 任立中,周建亨,陳靜怡(譯),2016年12月,行銷人攀越的7個頂峰,前程文化,臺北市。 2. 任立中主編,2016年10月,大數據戰略4.0,前程文化,臺北市。 3. 任立中,陳靜怡(2015),行銷研究:發展有效行銷策略之基石,前程文化,臺北市。 4. 任立中(2010),行銷源典,前程文化,臺北市。 5. Blattberg, Robert C., Byung-Do Kim, and Scott A. Neslin (2008), Database Marketing: Analyzing and Managing Customers, Springer, New York, NY. 6. Aaker, David A., V. Kumar, George S. Day, and Robert P. Leone (2011), Marketing Research, 10th edition, John Wiley & Sons, Inc. 7. Rossi, Peter E., Greg Allenby, and Rob McCulloch (2005), Bayesian Statistics and Marketing, John Wiley and Sons, New York, NY. 8. Leeflang, Peter S.H., Dick R. Wittink, Michel Wedel, and Philippe A. Naert (2000), Building Models for Marketing Decisions, Lower Academic Publishers, Norwell, MA. 9. 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. 10. Lilien, Gary L. and Arvind Rangaswamy (2003), Marketing Engineering: Computer- Assisted Marketing Analysis and Planning, Pearson Education, NJ.
- Grading
70% Weekly Homework
The evaluation of each student's performance in the course will be based on the quality of the homework, performance on the online course materials, and the term paper. Details of the comprehensive homework will be provided in class.
30% Term Paper
Due on June 10
- Adjustment methods for students
Adjustment Method Description Teaching methods Assisted by video
Provide students with flexible ways of attending courses
Assignment submission methods Written report replaces oral report
Individual presentation replace group presentation
Mutual agreement to present in other ways between students and instructors
Exam methods Written (oral) reports replace exams
Others Negotiated by both teachers and students
- Course Schedule
2/19Week 1 2/19 In class lecture: The Course Philosophy, Structure, and Policy On Line Viewing Assignment: (1) 大數據時代之行銷戰略(上) (2) 大數據時代之行銷戰略(中) Homework Assignment: To be announced on the NTU COOL 2/26Week 2 2/26 Class Discussion: (1) 大數據時代之行銷戰略(上) (2) 大數據時代之行銷戰略(中) On Line Viewing Assignment: (3) 大數據時代之行銷戰略(下) (4) 萬丈高樓平地起:建構顧客關係行銷資料庫(上) Homework Assignment: To be announced on the NTU COOL 3/4Week 3 3/4 Class Discussion: (3) 大數據時代之行銷戰略(下) (4) 萬丈高樓平地起:建構顧客關係行銷資料庫(上) On Line Viewing Assignment: (5) 萬丈高樓平地起:建構顧客關係行銷資料庫(中) (6) 萬丈高樓平地起:建構顧客關係行銷資料庫(下) Homework Assignment: To be announced on the NTU COOL 3/11Week 4 3/11 Class Discussion: (5) 萬丈高樓平地起:建構顧客關係行銷資料庫(中) (6) 萬丈高樓平地起:建構顧客關係行銷資料庫(下) On Line Viewing Assignment: (7) 顧客價值的解析與策略運用:ARFM模型(上) (8) 顧客價值的解析與策略運用:ARFM模型(中) Homework Assignment: To be announced on the NTU COOL 3/18Week 5 3/18 Class Discussion: (7) 顧客價值的解析與策略運用:ARFM模型(上) (8) 顧客價值的解析與策略運用:ARFM模型(中) On Line Viewing Assignment: (9) 顧客價值的解析與策略運用:ARFM模型(下) (10) 海誓山盟:顧客終身價值與遷徙路徑之預測(上) Homework Assignment: To be announced on the NTU COOL 3/25Week 6 3/25 Class Discussion: (9) 顧客價值的解析與策略運用:ARFM模型(下) (10) 海誓山盟:顧客終身價值與遷徙路徑之預測(上) On Line Viewing Assignment: (11) 海誓山盟:顧客終身價值與遷徙路徑之預測( (中) (12) 海誓山盟:顧客終身價值與遷徙路徑之預測(下) Homework Assignment: To be announced on the NTU COOL 4/1Week 7 4/1 Class Discussion: (11) 海誓山盟:顧客終身價值與遷徙路徑之預測(中) (12) 海誓山盟:顧客終身價值與遷徙路徑之預測(下) On Line Viewing Assignment: (13) 啤酒與尿布、廚具與內褲:購物籃分析(上) (14) 啤酒與尿布、廚具與內褲:購物籃分析(中) Homework Assignment: To be announced on the NTU COOL 4/8Week 8 4/8 Course Review and Discussion (In class) 4/15Week 9 4/15 Class Discussion: (13) 啤酒與尿布、廚具與內褲:購物籃分析(上) (14) 啤酒與尿布、廚具與內褲:購物籃分析(中) On Line Viewing Assignment: (15) 啤酒與尿布、廚具與內褲:購物籃分析(下) (16) 透視需求、百步穿揚:新產品推薦系統(上) Homework Assignment: To be announced on the NTU COOL 4/22Week 10 4/22 Class Discussion: (15) 啤酒與尿布、廚具與內褲:購物籃分析(下) (16) 透視需求、百步穿揚:新產品推薦系統(上) On Line Viewing Assignment: (17) 透視需求、百步穿揚:新產品推薦系統(中) (18) 透視需求、百步穿揚:新產品推薦系統(下) Homework Assignment: To be announced on the NTU COOL 4/29Week 11 4/29 Class Discussion: (17) 透視需求、百步穿揚:新產品推薦系統(中) (18) 透視需求、百步穿揚:新產品推薦系統(下) On Line Viewing Assignment: (19) 物以類聚,人以群分:顧客的分群與複製(上) (20) 物以類聚,人以群分:顧客的分群與複製(中) Homework Assignment: To be announced on the NTU COOL 5/6Week 12 5/6 Class Discussion: (19) 物以類聚,人以群分:顧客的分群與複製(上) (20) 物以類聚,人以群分:顧客的分群與複製(中) On Line Viewing Assignment: (21) 物以類聚,人以群分:顧客的分群與複製(下) (22) 消費行為大透視:理論、模型、預測、決策(上) Homework Assignment: To be announced on the NTU COOL 5/13Week 13 5/13 Class Discussion: (21) 物以類聚,人以群分:顧客的分群與複製(下) (22) 消費行為大透視:理論、模型、預測、決策(上) On Line Viewing Assignment: (23) 消費行為大透視:理論、模型、預測、決策(中) (24) 消費行為大透視:理論、模型、預測、決策(下) Homework Assignment: To be announced on the NTU COOL 5/20Week 14 5/20 Class Discussion: (23) 消費行為大透視:理論、模型、預測、決策(中) (24) 消費行為大透視:理論、模型、預測、決策(下) Lecture: 大數據時代之行銷戰略_結論 5/27Week 15 5/27 Writing a final-term paper, no class 6/3Week 16 6/3 Course Review and Discussion (In class)