Course Title: Marketing Analytics

Part A: Course Overview

Course Title: Marketing Analytics

Credit Points: 12.00


Course Code




Learning Mode

Teaching Period(s)


City Campus


625H Economics, Finance and Marketing


Sem 1 2023,
Sem 1 2024

Course Coordinator: Fatima Madani

Course Coordinator Phone: +61 3 9925 4124

Course Coordinator Email:

Course Coordinator Location: Building 80

Course Coordinator Availability: via appointment

Pre-requisite Courses and Assumed Knowledge and Capabilities

Required Prior Study:

Course ID 008953 Marketing Principles;

Course ID 008961 Market Research

Course Description

Achieving the ultimate goal of any marketing strategy, “delivering the right message to the right audience at the right time,” remains a distant dream for marketers. However, with increasing access to a wide variety of marketing data, firms can take a data-driven approach to formulate marketing strategies that are more scientific and number-driven. The objective of this course is to develop marketing strategies using data-driven marketing approaches. The course will introduce various tools and techniques of marketing analytics to generate marketing insights from data. Through the lenses of marketing analytics, you will analyse consumers’ online and offline behaviour to maximize firm value and precisely quantify the return of marketing investment. With the growing role of data in marketing, this course will help you answer these following marketing questions: what data/numbers are important, how to use data to tell a brand story, optimize marketing goals, and quantify the return on investment.

Objectives/Learning Outcomes/Capability Development


Upon successful completion of this course, you will be able to:

CLO1: Analyse the role of data and related technologies (data collection, data management systems, data visualization, and data analysis) in marketing decision-making.

CLO2: Review different types of marketing data in managing customer experience.

CLO3: Analyse structured marketing data to tell brand stories.   CLO4: Apply marketing mix and attribution models/metrics to analyse marketing scenarios, phenomenon, issues and problems and develop marketing strategies.   CLO5: Apply marketing analytics to solve real business problems, communicate managerial insights, recommendations and research findings.

Overview of Learning Activities

In this course you will be encouraged to be an active learner. You will be supported by various learning activities.

The course will expose you to various primary and secondary marketing data used for data-driven marketing decision-making. The course will use real-world examples, practical assignments, and business projects that allow you to understand the role of these marketing data in improving marketing outcomes, quantify marketing return on investment, and increase marketing campaigns' effectiveness via attribution modelling.

Overview of Learning Resources

Various learning resources are available online through MyRMIT Studies/Canvas. The lecture notes and workshop notes are posted on Canvas.

RMIT Library provides extensive resources, services and study spaces. All RMIT students have access to scholarly resources including course related material, books, e-books, journals and databases.

Computers and printers are available at every Library. You can access the Internet and Library e-resources. You can also access the RMIT University wireless network in the Library.

Contact: Ask the Library for assistance and information on Library resources and services: Study support is available for assistance with assignment preparation, academic writing, information literacy, referencing, maths and study skills.  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

The assessment tasks, their weighting and the course learning outcomes to which they are aligned are as follows.

  Assessment Task 1: 30%  Linked CLOs: 1, 2, 3, 4, 5   Assessment Task 2: 30%  Linked CLOs: 2, 3, 4   Assessment Task 3: 40%  Linked CLOs: 1, 2, 3, 5