Pricing Analytics - (BA) - Q3

Participation Prerequisites

This course focusses on how to formulate and implement demand models and price optimization models, assuming a basic familiarity with mathematical optimization (linear programs), linear regression models and R.

Course Content

The course aims to impart the skills needed to build demand models and price optimization tools in practice. In fact, there will be an actual consultancy project with an external partner as part of this course in which you will build (in a team) a complete prototype demand model and ticket pricing solution for an annual event in Koblenz with an estimated 14.000 participants! The teams will be supported by a doctoral student (with pricing consultancy experience at McKinsey).

Session 1: Segmentation and Basic Demand Estimation

• Introduction to segmentation
• Interactive valuation game
• Overview of basic demand model estimation

Session 2: Advanced Demand Model Estimation

• Detailed analysis of the New York Health Club (NYHC) case study
• Advanced demand estimation techniques, including Poisson and discrete choice models

Session 3: Demand Forecasting

• Discussion on demand forecasting
• Overview of demand data sources
• Basic forecasting methods for independent demand, covering time series analysis, error measures, autocorrelation, exponential smoothing, and ARIMA
• Endogenous demand forecasting, including linear regression and a case study on promotion forecasting
• Advanced forecasting methods

Session 4: Revenue Management under Independent Demand

• Network revenue management under independent deterministic demand
• Network revenue management under independent stochastic demand
• Comparing decision policies using simulation

Session 5: Revenue Management under Dependent Demand and B2C Pricing

• Assortment optimization
• Dynamic capacity control
• B2C pricing strategies

Session 6: B2C Pricing Special Cases (Markdowns/Promotions)

• Markdown pricing strategies, including a small retailer case study
• Promotion pricing strategies, including a large retailer case study

Session 7: B2B Pricing and Strategic Pricing

• Customized pricing strategies for B2B/B2C
• Car loan pricing case study
• Discussion on strategic pricing, irrational behavior, and ethics

Session 8: Mock exam and guest lecture

• Mock exam
• Guest lecture
• Wrap-up and course conclusion

Discover what the course has to offer - watch the introductory video for a comprehensive overview.

Intended Learning Outcomes and Competencies

• Ability to match typical pricing analytics approaches with business problems
• Ability to implement prototypes of typical pricing analytics approaches, including fundamentals of demand forecasting and demand estimation

Instruction Type

in-person

Form of Examination

Literature

T. Bodea and M. Ferguson. Segmentation, Revenue Management, and Pricing Analytics. Routledge, 2014