Programme Structure

This refresher course is geared towards providing you with the fundamentals of the topic, which will help you transition into the dynamic world of marketing analytics.

This course carries zero (0) Units and will be conducted as part of our Orientation programme. You are highly encouraged to attend this course if you have not taken similar courses in your undergraduate degree.

Big marketing data are increasingly available for managerial decision making. This course introduces concepts, techniques, and latest applications of big data in marketing. It covers the difference between big data and normal data and the potential of big data in marketing, the foundations of data structure, collection, and warehousing, and the latest applications of deriving marketing insights from big data. It engages students in a capstone project in groups to provide a holistic hands-on experience of analysing big data in marketing.

A clear understanding of consumer insights is critical to firms who want to use big data to predict consumer future behaviour and determine the most effective marketing strategies. This course is designed to provide students with a comprehensive coverage of frameworks, concepts, tools, and techniques to gain consumer insights, with an emphasis on uncovering, generating, and interpreting business-relevant consumer insights. Relevant theories and research in behavioural sciences will be discussed with the goal of understanding and eventually influencing consumer behaviour.

Information and communications technologies have brought fundamental changes to the business world. Being digitally smart and able to harness the digital technologies to effectively interact and engage with ever-changing consumers has become necessities for businesses to survive. The course takes the view that digital technologies have reshaped not just advertising, but all aspects of marketing. Students will first learn how digital technologies affect key elements of marketing strategy: segmentation, targeting and positioning. They will then be exposed to how product management, brand management, pricing, promotions and channel management, are all fundamentally changing in a digital era.

The digital age has fundamentally altered the manner we collect, process, analyse and disseminate market intelligence. The increased velocity of information flow enables marketers to respond with much greater speed to changes in the marketplace. Marketing analytics is timelier, less expensive, more actionable and accurate, and it is increasingly infused into today’s business decision-making processes. This course combines theory with practice, linking the classroom with the consumer marketing workplace. To help students become more effective marketing decision makers, the course involves holistic learning experience in business management. In addition to experiential learning, lectures, presentations, class discussions and case studies, teams are coached and grilled in close business review meetings.

Today’s businesses are bombarded with data. It is a key skill to be able to tell a story from this data so that businesses can leverage on market intelligence for marketing effectiveness. To achieve this objective, this course is designed with two integrated components: 1) data visualisation, and 2) marketing strategy. We will start with understanding how humans interpret and perceive visual cues. Then, we introduce various tools and techniques for visualisation. Subsequently, we apply these insights obtained to learn how to maximise the impact on communication to win the buy-in of the relevant decision makers within the organisation.

In recent years, as the quantity of business data has exploded and computing power has continued to improve, opportunities to automate many parts of the marketing function have emerged. We approach this ever-evolving topic holistically, including identifying the business opportunities and pitfalls AI presents, the legal and ethical considerations associated with the use of AI and a close look at the algorithms that make such automation possible. The course will present business applications, some of the theory behind machine learning and implement standard machine learning methods in the R programming language.

To facilitate well-informed marketing analysis and decision making, marketing scholars and practitioners have not only developed but also implemented a large variety of analytic models and tools to facilitate marketing decision making and oftentimes high-level strategic consultation.

This course helps student to digest the underlying mathematics details of the most popular analytical marketing models, and more importantly will guide them through the development and use of applicable software and interpretation of results. The aim of course is to build the student’s skills and confidence in undertaking analytics for marketing decision making.

The course is designed to provide the students an understanding of basic marketing concepts, tools and techniques and their application in the analysis of marketing problems. The focus is on creativity and appreciation of the role of marketing in an enterprise and its relationship with other functions of business. The course deploys a combination of teaching methods, including lectures, cases, exercises, and projects and covers topics such as the marketing concept, analysis of the marketing environment, segmentation and targeting and development of marketing programmes. Issues in implementing marketing strategy, evaluating the market environment, and integrating marketing mix are also addressed.

This course provides students with an overview of the theory and practice of personal selling and sales management. It will cover issues faced by sales practitioners and learn the practical ins and outs of how to sell products and services to a sophisticated marketplace.

The first part focuses on personal selling (face-to-face selling). Emphasis is given to improving the soft skills of the students. In particular, attention is devoted to the student’s communication abilities as a life skill and to the need to develop professional relationships in business. The second part addresses how to build and manage a sales department. Students will also learn various quantitative methods to achieve the best results. Emphasis is given to improving the analytical and problem-solving skills of the students.

Pricing is one of the most important but least understood of marketing decisions. This course aims to equip you with key concepts and techniques for evaluating and formulating pricing strategies. We will use a combination of analytical and experiential learning methods to accomplish this objective. Students will learn the fundamental techniques of setting prices and evaluating price changes across a variety of business contexts. They will apply these techniques to propose a more profitable pricing model for a company through their projects.

A product or service is central to a company’s success, its existence and continued existence in the market. A good, strong product may launch the company into the marketplace but it takes continuous and consistent effort to come up with a string of successful products to sustain the company.

This course focuses on the product manager’s myriad tasks of product planning, product development and strategy, marketing planning and strategy, implementing these strategies and brand husbandry. Students will also be introduced to the various marketing tools that are used in product management. With globalisation and the fragmentation of the process of first identifying or anticipating the need, to the creation of the product and delivering value to customers across different parts of the world, many companies grapple with managing products that are conceived in one country, made in another and distributed to every corner of the world. Managing a common brand identity becomes even more of a challenge. Students will acquire the skills to product management and brand management in the new business environment.

This course is an introductory course for Python programming and data analytics. It covers basic Python programming techniques and preliminary data analysis, with a great emphasis on addressing practical business problems and real datasets. As a basic level course, there is no prerequisite for students. From this course, students will learn the basic Python programming and modelling techniques through extensive exercises and case studies. They will apply these techniques in real-world datasets for solving practical business problems.

The course provides the essence of systematic and objective research designs, methods, analyses, report writing, and presentation for marketing insights. It covers both conventional methods for small data and cutting-edge methods for big data for marketing insights. It combines lectures, video case studies, group discussions, and self reflections. The class together will discuss how to analyse the short-term and long-term impact of COVID-19 on the restaurant industry and the education industry, and provide recommendations.

Through an industry internship, you will be able to engage in experiential learning in analysing and solving problems faced by peers working in marketing and analytics functions in the various industries. These internships will also enable student to acquire a variety of analytical, communication, interpersonal and collaboration skills, particularly in understanding the impact of your actions on your colleagues and companies.

These internships are primarily self-sourced.

Through the Marketing Analytics Consultancy Project, you will work in groups to analyse and solve marketing – and analytics-related problems faced by actual companies, resulting in a recommendation, of a comprehensive, in-depth business proposal or solution.

These projects are primarily self-sourced.