Introduction
Marketing decision-making is growing in importance in the business world. More than ever before, organisations are placing greater emphasis on the marketers' ability to evaluate, anticipate, and illustrate the contribution of marketing to organisational performance. Increasingly, senior managers are requiring greater rigour and accountability for investments in marketing activities. Within marketing, there is a realisation that practitioners need to be able to justify their strategies, tactics and the associated outcomes, using relevant metrics. Marketing analytics seeks to build a link between the marketing activity of the organisation and the outcomes that result from it. The focus of this unit is on developing, analysing, and evaluating appropriate models to measure the performance of marketing activities. It will develop students' knowledge of key strategic and technical decision-making models and metrics that form the foundation of marketing analytics. Students will gain knowledge and skills to predict the outcome of marketing plans in order to boost return on marketing investment.
Summary
| Unit name | Marketing Insights into Big Data |
| Unit code | BMA708 |
| Credit points | 12.5 |
| College/School | Tasmanian School of Business and Economics |
| Discipline | Marketing |
| Coordinator | Doctor Denni Arli |
| Delivered By | University of Tasmania and Third Party(ies): ECA |
| Level | Postgraduate |
Sustainable Development Goals
The Unit Coordinator has identified that this unit aligns with the following UN Sustainable Development Goals. We welcome your thoughts and feedback on the alignment of the unit with these goals.
Availability
Specific information on 2027 unit availability will be available in August
Learning Outcomes
- Analyse big data using a range of statistical techniques.
- Create effective data visualisations to identify meaningful relationships.
- Communicate actionable marketing insights derived from data analysis
Fee Information
2027 fee information will be available in August.
Teaching
| Teaching Pattern | Workshops will be delivered weekly to support student learning and engagement across both delivery modes. In-person workshops will be conducted on campus. Online workshops will be delivered via Zoom.
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| Assessment | Big Data Reporting using T-test, Correlation and Regression Analysis (30%)|Data Visualisation (35%)|Descriptive Statistics Analysis. (35%) |
| Timetable | View the lecture timetable | View the full unit timetable |
Textbooks
| Required |
Required readings will be listed in the unit outline prior to the start of classes. |
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The University reserves the right to amend or remove courses and unit availabilities, as appropriate.