This course teaches students how to translate practical strategic marketing problems into models using simulations, and gives them optimization tools to solve these models. This set of skills is different and complementary to other marketing skills (e.g. marketing models) students would learn in the program. For example, for a typical marketing model, when a problem becomes too complicated, its assumptions may not hold, or it may not yield a closed form solution.  This course will provide students with the skills to enable them to solve complicated models using simulation and optimization. These skills are not currently covered by the existing courses offered by ANU (MMIB), in either undergraduate or postgraduate level.

Broadly, this course aims to equip participants with a skill set for 1) modeling practical strategic marketing problems, 2) tackling complicated models with simulation, and 3) optimizing marketing decisions based on model results.

The emphasis in this course is on (i) building simulation models based on strategic marketing problems, (ii) solving these models by analyzing simulation results, and (iii) optimizing the solution to strategic marketing problem using the analysis.

This course will equip students with the ability to:

• Understand statistical distributions, and link them to people, events and other factors associated with strategic marketing decisions.
• Decompose and conceptualize strategic marketing problems, and build models that are described by statistical variables and the relationships between these variables.
• Simulate data (based on these models), which are realistic and could be very complex.
• Analyze simulation data and optimize marketing strategies to solve the problems underlying the models.
• Make managerial recommendations based on the results and communicate the solutions effectively.

Assessment will be based on three elements: (i) participation in coursework, inclusive of class and workshop participation, (ii) group based homework exercises, and (iii) a major individual exercise.

Students taking this course are expected to commit at least 18 hours a week during the seven weeks completing the work.  This will include:

Lectures:                                            3.5 hours

Workshops                                        1.5 hours

Private study                                     6 hours

Group work                                       4 hours

Individual major exercise:               3 hours per week.

At least an average of 65% (or equivalent) in the final two years of an Australian undergraduate degree with at least one year of university level study in quantitative analysis, including basic mathematics and data analysis techniques.

MKTG8001 Marketing Analytics

STAT7055 Financial Statistics and MKTG8003 Marketing Models

Please refer to course website