Course overview
This course aims to provide students with an understanding of the semantics of customer behaviour and develop skills in data visualization for impactful and meaningful representations of complex information. Content will cover the theoretical foundations of customer behaviour, as well as practical techniques for data visualization and interpretation. Students will learn to create visual representations that effectively communicate insights into customer behaviour, enabling informed decision-making in data-driven contexts. This course aligns with the overall program goal of equipping students with data analytics skills and the ability to apply them in real-world scenarios, enhancing their readiness for careers in data analysis and decision support
- Foundations of Behavioural Analytics
- Analytical Techniques & Predictive Modelling
- Optimisation based Analytical Techniques
Course learning outcomes
- Describe impact of perception, motivation, attitudes, and lifestyle factors on customer behaviour
- Explain customer behaviour clearly and persuasively by written and oral communication
- Apply behaviour pattern recognition, optimisation, simulation and linear programming techniques to customer data
- Develop predictive models from customer data to recommend strategies for nudging customer behaviour and enhance engagement
- Analyse customer behaviour models to real-life business scenarios
- Apply customer analytics techniques to areas such as fraud and security and credit risk