Introductory description

Pricing Analytics focuses on how a company should set and update pricing and product availability decisions across its various selling channels in order to maximise its profitability in an automated fashion. In other words, we are concerned with algorithms making real-time pricing decisions, rather than strategic pricing.

Module web page

Module aims

Outline syllabus

This is an indicative module outline only to give an indication of the sort of topics that may be covered. Actual sessions held may differ.

The module makes heavy use of case studies and applied programming exercises in a programming software to study the following topics:

Demand modelling and estimation

Capacity control models

Price optimization

Dynamic pricing: promotions, markdowns

Machine learning models in pricing and revenue management

Learning outcomes

By the end of the module, students should be able to:

• Demonstrate comprehensive understanding of key concepts including the impact of constrained capacity, opportunity costs, customer response, demand uncertainty.
• Evaluate the critical differences among different types of opportunity and the approaches needed to address them.

Indicative reading list

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

Subject specific skills

Estimate and evaluate various demand models
Calculate and solve relevant price or capacity control optimisation models
Compare and assess the performance of different decision policies in simulation studies

Transferable skills

Numeracy
Problem solving