This course develops a systematic and analytical approach to marketing decision making, focusing on how to measure customer preferences and how to use those preferences to make the marketing of products and services more efficient and effective. At the ANU (MMIB) there are other courses at both undergraduate or postgraduate level that cover some aspects of marketing analytics, yet there is no course that covers the state-of-the-art marketing analytics tools and frameworks. Moreover, there is no course at the ANU which combines cases, tools, frameworks, and software in this area.

Broadly, this course aims to equip participants with proven concepts, techniques, and frameworks for 1) measuring customer preferences, and 2) using those preferences to make marketing more efficient and effective.

This course will equip students with the ability to:

• Understand utility theory, and use that understanding to measure customer preferences
• Understand what customers’ value in a product, and assess what they are willing to pay for it.
• Understand how to segment customers based on the differences in what they value.
• Understand different ways to segment customers, including state of the art latent class methods.
• Understand how to determine the most effective target markets, and how to market to those markets efficiently.
• Demonstrate how to design a study that does all of the above.
• Understand how different tools and frameworks are used in an integrated manner to solve strategic marketing problems.
• Obtain the best possible return from other courses such as Creating and Communicating Value and Marketing Accountability.

Assessment will be based on three elements: participation in coursework, inclusive of class and workshop participation, group based homework exercises, and a major individual exam.

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 exam preparation:          3 hour 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.

Corequisite: STAT7055 Financial Statistics

STAT7055 Financial Statistics

For further information please refer to course website