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Overview

Today’s data-rich environment and the advance of big data analytics have changed the way of marketing and consumer behaviour in almost every industry. Today marketing manager should use such big and intelligent data analytics to better understand consumer purchase journey and thus improve marketing effectiveness by offering right product or information (e.g. personalized advertising and promotion) at right time and place.

Marketing, Product, Brand, Sales, Advertising, and PR Managers, Entrepreneurs, Data Scientist/Engineer and Business Analyst in the future must incorporate big data analytics in their marketing decision-making process. However, industry has difficulty in finding ideal workers who know both marketing and data analytics because most students have been trained for only data analytics methodology or for only marketing implication. 

This specialisation in Marketing Analytics will provide students with actionable marketing analytics training by offering specialized big data analytics tools for marketing manager’s decision-making. For example,

• The impact of digital technology (e.g. social media, search-engine) on marketing and consumer purchase journey

• Actionable marketing decision using new type of big consumer data

• Data product or service development such as recommendation tool (e.g. Amazon books, Netflix movies)  
• New product idea generation using natural language processing, sentiment analysis, or topic modelling to analyse social media, product reviews or start-up projects in crowdfunding platforms
• Text/picture/video content and emotion analysis for selling new product ideas or marketing messages

Students will exercise hands-on data analytics to tackle socially, culturally, environmentally, or commercially important real-world problems.

PLEASE NOTE: It is proposed that this major be offered in program 8404 and 8417 from 2019.

Study Level

Postgraduate

Minimum Units of Credit

36

Specialisation Type

Specialisation

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Specialisation Structure

Students must complete 36 UOC.

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Free Elective Courses

Students may take one course (6 UOC) from the courses listed below or from other MCom elective lists.

Visualization
- HDAT 9800 Visualisation and Communication of Health Data (6 UOC)

Programming
- COMP 9021 Principles of Programming (Python) (6 UOC)
- BENV 7500 Programmable Cities (Python) (6 UOC)

Business Analytics
- INFS 5720 Business Analytics Methods (6 UOC)
- INFS 5730 Social Media & Enterprise 2.0 (6 UOC)

Spatial Data Analysis
- BENV 7504 Digital Cities (6 UOC)
- BENV 7728 GIS and Urban Informatics (6 UOC)

Econometrics & Statistics
- ECON 5408 / ECON 3208 Applied Econometric Methods (6 UOC)
- MATH 5836 Data Mining and its Business Applications (6 UOC)
- MATH 5935 Statistical Consulting (6 UOC)

Pre-2019 Handbook Editions

Access past handbook editions (2018 and prior)

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