Li Xiuping

Data or the results do not bear meanings and are not useful unless you translate them into insights. Such insights can be learnt from well established theories to help you understand your customers and markets. When teaching Consumer Insights, I believe in letting students know how to think rather than what to think. I encourage them to be independent in thinking, appreciative of soft science, and curious about great minds.

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Noah Lim

Pricing is the only P in the marketing mix that produces revenue. Therefore, it is essential to understand how to price to maximise sales revenue as that is a step towards generating higher returns. Yet, pricing is tricky. Setting too low a price means lost revenue; too high a price may scare off potential customers. Besides such importance to any profit-making organisation, almost everyone is interested in making more money, right? So I see Pricing as a topic that is both important and interesting. I also see students as my friends; friends whom I’m responsible for in terms of cultivating knowledge. And so, as I share my knowledge, I bring not just applications grounded on theories, but also various in-class simulations for an enjoyable learning experience.

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Liu Qizhang

In Big Data in Marketing, students learn how to perform analytics on various marketing scenarios using different machine learning algorithms such as linear regression, classification, basket analysis, and text analytics through the popular programming language R. My philosophy is: it’s much better to teach people how to fish than to give them fish. As such, students are expected to learn how to source information by themselves to tackle problems. Weekly assignments, tests and project assignment are designed to stretch students’ understanding of the topics taught and beyond. In learning programming, practice is the best teacher. Try to source your own data and apply learned techniques on them.

Samer Hajjar

Personal Selling and Sales Management module is important because it provides students with an overview of the theory and practice of sales. Students will understand the key success factors for driving the change toward data-driven sales management. In particular, they will learn how to incorporate analytics in sales processes as well as the effects these tools can cause in sales.

Xiong Peng

Python is becoming the most popular programming language for data analysis, as we have seen a dramatic increase in the job market demand for Python programming skills in recent years. As such, Python for Marketing Analytics is offered to better prepare students for their future careers.

You might think that I only teach Python syntax and coding logics. Far from it. I believe that students should also appreciate the large and active ecosystem of Python where a great many tools are provided for data processing, visualisation, and statistical learning. These tools will be applied in case studies for a richer learning experience.

Michael Thomas

Artificial Intelligence is changing the face of marketing, with a host of new opportunities and challenges. In this course, we discuss both the technical concepts that make this technology possible and the opportunities they present for businesses.