School of Business

Guide on open lecture "Marketing Seminar" in 2nd semester 2015

“Database Marketing” was planned to be established as a new subject; however, it is feasible only by next semester. Subsequently, in 2nd semester, we will employ our existing subject “Marketing Seminar” to give lectures based on “Database Marketing”. The subject deals with marketing strategy methods based on data and follows latest big data and scientific marketing trends. The subject’s focus is to maximize the practical ability by combining theory with the actual training lecture.

Please show your interest and register the course as it is customized to meet the level of the students. Students who do not major marketing can also receive support on scientific data analysis methods.

- Professor: Hongjai Rhee (219-2718, hrhee@ajou.ac.kr)
- Students: 3rd and 4th year student in School of Business (possible for 2nd year students)
- Prerequisite subject: Marketing management
- Software: Excel, SPSS 
- Teaching materials: Distribution of lecture notes
- Assessment: Team projects 50%, final exam 50%

Lecture schedule and main content
Week 1: Understanding the structure of marketing model: Adbudg example, non-linear regression, excel optimizer
Week 2: Discovering market segmentation technique: Segmentation & Targeting, GE portfolio matrix
Week 3: Studying factorial analysis: MDS, Factor analysis
Week 4: Formulating positioning map: Positioning map (vector model, ideal-point model)
Week 5: Predicting market share: Market share simulation
Week 6: Conjoint analysis 1: Rating-based conjoint (dummy regression)
Week 7: Conjoint analysis 2: MLE estimation method, HUFF model
Week 8: Conjoint analysis: Choice-based conjoint (conditional logit)
Week 9: Learning big data analysis method: Price elasticity
Week 10: Practical using Lotte Mart data: Brand choice
Week 11: Predicting new product diffusion: New product diffusion (BASS model, Assessor)
Week 12: Pricing strategy and technique: Discrimination & Bundling, Price Sensitivity Meter
Week 13: Importance of loyalty management: Markov chain and loyalty management
Week 14: Measurement method of customer valuation: Customer valuation (RFM, CLV, and Brand Equity)
Week 15: Final exam