Data Empowered Marketing
Overview
This unit aims to develop students’ understanding of how data can be used to support marketing insight and decision-making. Students examine how marketing problems are translated into research objectives, how different forms of data are selected and evaluated, and how internal, external, digital and primary data can inform marketing practice. The unit introduces students to qualitative and quantitative approaches to data collection and analysis, with attention to data quality, research ethics, privacy, visualisation, reporting, and the communication of actionable insights. It also considers the emerging role of AI and generative AI in marketing analytics and insight work.
Requisites
01-November-2026
07-February-2027
30-May-2027
31-October-2027
Unit learning outcomes
Students who successfully complete this unit will be able to:
- Critically evaluate the role, value and limitations of data in contemporary marketing decision-making.
- Critically analyse the use of marketing data, analytics and research methods, including ethical, privacy and governance considerations.
- Design evidence-based marketing strategies by critically analysing marketing problems using advanced data-enabled approaches.
- Communicate data-informed marketing insights and recommendations professionally to a variety of audiences, and function effectively as a team member or leader where appropriate.
Teaching methods
Hawthorn
| Type | Hours per week | Number of weeks | Total (number of hours) |
|---|---|---|---|
| On-campus Class | 2.00Ìý | 12 weeks | 24 |
| Online Lecture | 1.00Ìý | 12 weeks | 12 |
| Unspecified Activities Independent Learning | 9.50Ìý | 12 weeks | 114 |
| TOTAL | 150 |
Assessment
| Type | Task | Weighting | ULO's |
|---|---|---|---|
| Written Assignment | Individual | 20-30% | 1,2 |
| Written Assignment | Group | 30-50% | 2,3,4 |
| Presentation and Report | Individual | 30-40% | 1,2,3,4 |
Content
- Foundations of data-empowered marketing
- Actionable insights, research problems and research briefs
- Marketing data sources and data-informed decision-making
- Data quality, relevance, limitations and fitness for purpose
- Internal, first-party, external, digital and primary data
- Research ethics, privacy and responsible data use
- Qualitative research, interpretation and insight generation
- Measurement, survey design and questionnaire quality
- Sampling, data collection and preparation
- Descriptive analysis and significance testing
- Data visualisation, dashboards and data storytelling
- AI-enabled analytics and generative AI in marketing research
Study resources
Reading materials
A list of reading materials and/or required textbooks will be available in the Unit Outline on Canvas.