Curriculum

Curriculum

Students in the MSc Marketing Programme are required to complete 7 compulsory courses and 5 elective courses to qualify for graduation, within the prescribed Programme duration. Each course usually has 3 credits. All electives are available for any enrolled student, regardless of track. However, students who have completed any four elective courses marked * in the table below can apply for the "Artificial Intelligence Marketing" major upon graduation. Compulsory and elective course options are subject to actual course availability.

  • Managerial Marketing Track

    Preparation for professional careers in marketing management; particularly appropriate for fields such as consumer, product, service, brand, advertising, and cross-border marketing.

  • Artificial Intelligence Marketing Track

    Preparation for professional careers in more technical roles such as digital marketing, marketing engineering, and database marketing.


Core Courses ( Total 7 Courses / 21 Credits )

Strategic Marketing Management

Strategic marketing focuses on the concepts and processes involved in developing market-driven strategies. This course examines the marketing management concepts underlying both consumer and industrial marketing strategy and tactics. It covers major marketing decisions in a problem oriented setting, the in-depth study of general marketing management and the development of marketing plans and strategies. It illustrates how marketing management varies the marketing mix (price, product, promotion, and place) to achieve maximum consumer satisfaction. Emphasis is placed on marketing strategy (formulation and implementation) and the role of the firm vis-a-vis its various environments (socio-political-economic).

Consumer Behavior

Consumer Behaviour is the study of the processes involved when individuals or groups select, purchase, use, or dispose of products, services, ideas, or experiences to satisfy their needs and desires. By the completion of this subject, students will be able to explain the major stages which consumers usually go through when making a consumption-related decision; identify the major individual, social and cultural factors that affect consumers’ decision making; and assess marketing implications for practitioners.

Marketing Research in the Digital Age

In the digital age, information abundance creates new opportunities for firms to understand and assess the outcome of their marketing strategies. The broad objective of this course is to provide a fundamental understanding of marketing research methods employed by well-managed firms. The course focuses on integrating problem formulation, research design, questionnaire construction, sampling, data collection, data analysis, AI methods in marketing to yield the most valuable information. The course also examines the proper use of statistical applications, with an emphasis on the AI application of consumer data and the interpretation and use of results.

Communications in the Digital Age

Theoretical and practical appreciation of the role of “integrated marketing communication” (IMC) in today’s business environment. IMC differs from traditional advertising and promotion programmes by using zero-based planning, data-driven communication and brand touch points. The course focuses on using strategic mix of advertising, sales promotion, public relations, event marketing and direct response promotions along with mass and two-way communication in the digital age.

Big Data Marketing Strategy

The global top 100 companies are using at least one digital and social media platforms to promote their brands and build stronger connections with their target customers. Definitely, digital and social media marketing has emerged as a tectonic shift from traditional marketing. This course introduces concepts, theories and applications of digital and social media marketing strategies in the Greater China and around the globe. With an in-depth study of display advertising, search advertising and social media marketing, students would be able to implement digital and social media strategies which involve different aspects of marketing. Due to a strong need for marketing professionals who are attuned to this area, this course is specifically for students who are planning to enter digital and social media marketing, consulting and brand management roles.

Customer Relationship Management

The purpose of this course is to provide students with a deep understanding of current big data approaches and marketing applications. The topics include trends of big data applications, consumer evolution in the digital age, big data insights into business, text mining and topic modeling, Web search data and Internet marketing, social network and social media marketing, mobile marketing, and data driven marketing strategy. Methodologies and techniques, including text analysis, Web crawling, logistic regression, and social network analysis, will be introduced and their business applications will be explained. This course aims to help students develop analytics skills and abilities combined with innovative business ideas to create effective big-data marketing strategies in today’s marketing.

Digital and Social Media Marketing

The course aims at providing participants with a basic understanding on what customer relationship management (CRM) is, why it is so important in the contemporary business world, and how it is implemented using recent information technology. In addition to the traditional lecturing method, this course will include a lot of case analyses, small group discussions, and/or presentations. Specifically, the following topics will be covered: - customer heterogeneity, - customer lifetime value, - customer dynamism, - CRM-based marketing strategies, - and one-to-one marketing. The implementation of CRM via Internet marketing, data warehouse, data mining, and database marketing will also be discussed.

Elective Courses ( Select 5 Courses / 15 Credits )

Managerial Marketing Track
Internship Training

This course links classroom knowledge and real-world applications with an actual work setting opportunity. It provides students with hands-on work experience in the marketing related industry, which are necessary for a successful career path. Students should have some ideas of their job interests, personal skill sets and career path, and then secure a position in line with that. Students should take the initiative to contact the Career Development Centre for assistance and continual feedback. After the internship, students can have a reflection opportunity on the direction of their career paths.

Market Intelligence and Digital Consumer

New digital technologies have fundamentally reshaped marketing theory and practice in the last decade alone. Technology has changed the modes of communication through which firms engage with consumers. Moore’s law has made the storage and analysis of consumer data scalable, creating opportunities for fine-grained behavioral analytics. New monitoring tools have fostered precise and personalized customer relationship management practices. This course is about gathering, analyzing, and interpreting data about markets and customers. It has been designed for analysts and managers who will be using market intelligence, and so is intended for students wanting to go into marketing management, consulting, strategy, general management, and entrepreneurship. Students who take this class will learn about the types of digital marketing decision problems in which research information is most useful – fundamentals problems of target market selection, new product or service introduction or modification, customer retention, pricing, etc. that are crucial in the digital age. Throughout the course we will specifically stress the theory and practice of randomized experimentation, A/B testing and the importance of causal inference for marketing strategy.

Managerial Marketing Practicum

The objective of this course is to provide students hand-on experience to solve managerial marketing problems in the real-world environment. The course consists of lectures, group projects, meetings, reports and presentations. Student work on the real world data and collaborate closely with professors to deliver joint solutions to the managerial marketing problems in the industry.

Service Marketing

Much of the global economy is increasingly dominated by services. This course focuses on challenges of managing service brands and delivering quality service to customers across industry sectors. The attraction, retention, and building of strong customer relationships through quality service (and services) are all at the heart of the course content. This course considers service excellence as a corporate strategic vision and views effective service strategy from an integrative perspective that covers customers, employees, and firm operations. This course is designed to help students recognize the vital role that services play in the economy and its future as well as acquire the necessary knowledge and skills to implement quality service strategies for competitive advantage across industries.

Strategic Brand Marketing

Over the last decades, the concept of brands and branding is increasingly important for companies in almost every industry, from consumer goods markets to business to business (B2B) organizations. In contemporary markets where competition is multifaceted, brands and brand equity are the most valuable strategic assets in developing effective marketing strategies, competitive advantage and long-term profitability.
This course is designed to acquaint students with how strong brands are created and managed, as well as what should be done to sustain and leverage their brands over time. Students learn to build and manage strong brands to help organizations compete in the marketplace. Conceptual theories and case studies will be used to enhance understanding of the application of knowledge in real world situations. Topics will cover from the meanings of brand, building strong brands in the global and digital world to specific categories of branding strategies, such as luxury branding.

Creative Marketing and Design Thinking

Design thinking is an essential tool for simplifying and humanizing. The principles of design thinking include a focus on users’ experiences. It is a multi-step method for understanding users’ needs better, creating innovative solutions for them and iterating quickly to get it just right. In the course, students will learn how to use the physical models such as diagrams and sketches, to explore problems and the use of prototypes to experiment with solutions to create more relevant marketing.

IOT and Retail Technology

Internet of Things (also referred to as IoT) is an Internet technology that extends Internet connectivity beyond standard devices, such as desktops, laptops, and smartphones, to any range of everyday objects including traditionally non-internet-enabled physical devices. By combining low-power, battery-free hardware with real-time digital analytics, IoT disrupts the traditional retail process and enables retailers to transform their customer service relationships and provide consumers with a seamless shopping experience, while meeting, and surpassing, the expectations of increasingly tech-savvy consumers. This course introduces the key concepts of IoT and its applications in Retail industry.

Artificial Intelligence Marketing Track
Big Data Marketing Practicum *

The objective of this course is to provide students hand-on experience to solve big data marketing problems in the real-world environment. The course consists of lectures on big data software, big data group projects, meetings, reports and presentations. The big data project can be a data mining project or a text mining project or a voice mining project. Student work on the real world data and collaborate closely with professors to deliver joint solutions to the big data marketing problems in the industry.

Marketing Analytics and Machine Learning *

The objective of the course is to help student to understand what machine learning is and how it can be used in marketing analytics. The course will first introduce to students the major machine learning algorithms that are commonly used in marketing and sales. It will also discuss real examples of using machine learning in marketing scenarios, such as personalizing offers to customers or improving an online customer experience. Students will also learn about the theory, techniques and how to choose the machine learning algorithm that best fits a particular marketing problem in industry.

Big Data Processing in Digital Marketing*

With the rapid development of high technology, high-volume marketing data are everywhere and booming exponentially. Currently the most important challenge for marketers is how to process the big data, dig out the valuable information from the big data, and obtain meaningful insights from the information. The purpose of this course is to provide fundamental knowledge to familiarize students with the most important information technologies used for preprocessing, analyzing the big data and concluding with managerial insights. The first half of the course introduces a brief overview of big data challenges in marketing and Apache Spark with its fundamental implementations, which is a powerful big data analytics engine. The second half of the course mainly focuses on how to tap into Apache Spark’s machine learning packages to extract the useful managerial insights: three most popular methods, regression, convolutional neural network, and natural language processing are introduced. Moreover, several marketing problems in practice (sentimental analysis, pricing, recommendation) are introduced and solved by these methods.

Reinforcement Learning in Digital Marketing*

Reinforcement learning (RL) becomes popular in digital marketing: it helps the marketers to make the optimal marketing strategies. By taking this course, students will be exposed to both theoretical foundation and practices of RL. The topics includes dynamic programming and its approximate form, Q learning, policy gradient methods, model-based methods. The first half of the course mainly focuses on the mathematical foundation of RL, dynamic programming and its approximate form, which can only be solved in practice for low dimension. The second half of the course introduces three major methods used for RL and shows how to apply these methods to solve the specific marketing problems in practice.

Marketing Engineering*

The course objective is to equip students with quantitative and analytical skills to solve problems associated with data driven marketing. Students will learn how to formulate marketing problems regarding product, price, place, and promotion as mathematical and statistical models and how to solve them with data mining and statistical techniques. Applications of these models will be discussed.

Artificial Intelligence applications in Marketing*

The course will provide an overview of AI from theory to practical. Student will learn what is AI and how it can be integrated into businesses from identify marketing potential to chatbot customer communication. The course will teach students how to use AI natural language classification services to build chatbots/virtual agents across of marketing channels and touchpoints to support sales and marketing; using image recognition to tag and classify visual content to support visual listening and unlock hidden value in unstructured data using the natural language understanding to find answers, monitor trends, and surface patterns.

Artificial Intelligence Principles*

This course presents students with a foundational understanding of state-of-the-art artificial intelligence (AI) technologies and their marketing implications as well as their limitations. We will cover three key AI technologies: machine learning, natural language processing, and robotics and discuss their marketing applications. Students will gain a practical introduction to these key AI technologies and their marketing implications. The course does not assume any particular technological background, though some programing knowledge is a plus. Students will focus on the marketing and managerial implications of these technologies and how they can be applied in the workplace. In addition, students will have the opportunities to learn how to apply these AI technologies using real marketing dataset.