Course Title: Marketing Analytics
Part A: Course Overview
Course Title: Marketing Analytics
Credit Points: 12.00
Terms
Course Code |
Campus |
Career |
School |
Learning Mode |
Teaching Period(s) |
MKTG1474 |
City Campus |
Postgraduate |
625H Economics, Finance and Marketing |
Face-to-Face |
Sem 2 2020, Sem 2 2021, Sem 2 2022, Sem 2 2023 |
Flexible Terms
Course Code |
Campus |
Career |
School |
Learning Mode |
Teaching Period(s) |
MKTG1475 |
RMIT Online |
Postgraduate |
625H Economics, Finance and Marketing |
Internet |
JulDec2020 (KP6) |
MKTG1475 |
RMIT Online |
Postgraduate |
625H Economics, Finance and Marketing |
Internet |
JulDec2021 (KP6) |
MKTG1475 |
RMIT Online |
Postgraduate |
625H Economics, Finance and Marketing |
Internet |
JulDec2023 (KP6) |
Course Coordinator: Hafizul Islam
Course Coordinator Phone: By appointment via email only
Course Coordinator Email: hafizul.islam@rmit.edu.au
Course Coordinator Location: Melbourne Campus, Building 80.
Course Coordinator Availability: By appointment via email only
Pre-requisite Courses and Assumed Knowledge and Capabilities
• 008994 Marketing Management (MKTG1100 or equivalent)
• 008995 Consumer Behaviour (MKTG1101 or equivalent)
Course Description
The aim of this course is to expose students to the application and presentation of analytical and statistical methods to solve marketing problems. Businesses today make marketing decisions that are driven by insights gained from the analysis of data. Especially, marketers nowadays have access to unparalleled data on opinions and behaviour from the digital marketing environment. These data used by marketers for decision-making come from various sources.
At a broad level, these data can be classified into two main types: structured data that come in numerical format, and unstructured data such as text, audio, and video. Furthermore, because of the scale, these data are called “Big Data” with principle characteristics of high volume, high velocity, and high variety. Therefore, data-driven marketing decisions require a different kind of understanding, a new set of skills, and a unique mindset to deal with ever-increasing influx of information.
This course will offer theoretical understanding of data to explain and explore the changes taking place in marketing. Also, the course will expose students to necessary tools and techniques to collect, summarize, visualize, and analyse different types of marketing data. Finally, the course will provide hands-on exercises to translate concepts into context-specific operational decisions and actions using analytical, quantitative, and computer modelling techniques.
Objectives/Learning Outcomes/Capability Development
On successful completion of the course you will be able to:
CLO-1: Critically analyse and interpret the role of analytical techniques, software tools, and empirical modelling in enhancing firms’ marketing decision-making.
CLO-2: Demonstrate the use of software tools in applying empirical skills to solve marketing problems using data driven approach.
CLO-3: Design and conduct field experiments for causal inference.
CLO-4: Apply techniques of marketing data collection, synthesize raw data using data summary, data visualization, and data analysis, and interpret the results to convey marketing insights to specialist and non-specialist audiences.
CLO-5: Apply content analysis to engage in social listening.
CLO-6: Analyse critically the logic of optimization and attribution in marketing analytics.
Overview of Learning Activities
The focus of this course will be to translate conceptual understanding of various marketing principles into specific operational plans. This will entail using actual or simulated data to take optimal marketing actions using insights from marketing analytics. Students will use analytical tools to approach such problems. In addition, application of theoretical concepts will be illustrated through cases, reading, and empirical examples.
Overview of Learning Resources
Various learning resources are available online through MyRMIT Studies\Canvas. The lecture notes and workshop notes are posted on Canvas.
Resources are also available online through RMIT Library databases and other facilities. Visit the RMIT library website for further details. Assistance is available online via our chat and email services, face to face at our campus libraries or via the telephone on (03) 9925 2020.
Additional resources and/or sources to assist your learning will be identified by your course coordinator and will be made available to you as required during the teaching period.
Overview of Assessment
Assessment Task 1: 30%
Linked CLOs 1,2,3
Assessment Task 2: 30%
Linked CLOs 1,2,4
Assessment Task 3: 40%
Linked CLOs 1,2,3,4,5,6
Feedback will be provided throughout the semester in class and/or in online forums through individual and group feedback on practical exercises and by individual consultation.