MARKETNG 3002 - Marketing Analytics

North Terrace Campus - Semester 2 - 2023

This course develops students? capabilities to use analytical tools and techniques to address marketing problems, with a focus on providing data to assist marketing decision-making. Marketing analytics enables marketers to measure, manage and analyse customer preferences and trends, as well as evaluate marketing performance to maximize its effectiveness. Students will develop an understanding how to use marketing analytics to predict outcomes. The course also examines the ethical and technical issues related to data privacy.

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Course Details

Course Code	MARKETNG 3002
Course	Marketing Analytics
Coordinating Unit	Marketing
Term	Semester 2
Level	Undergraduate
Location/s	North Terrace Campus
Units	3
Contact	Up to 3 hours per week
Available for Study Abroad and Exchange	Y
Prerequisites	ECON 1008, MARKETNG 2006, MARKETNG 1001
Incompatible	MARKETNG 2002
Assessment	Tests, assignments and final exam

Course Staff

Course Coordinator: Lachlan Schomburgk

Course Timetable

The full timetable of all activities for this course can be accessed from Course Planner.

Course Learning Outcomes

On successful completion of this course, students will be able to:

1. Demonstrate the use of analytical tools in marketing.

2. Choose appropriate data sources and analytical tools to assess marketing performance.

3. Apply analytics tools to a variety of data collected by marketers.

4. Translate the results of quantitative analyses into managerial insights for marketing decision-making.

5. Explain and illustrate how marketing analytics are used in an integrated manner to solve strategic marketing problems.

University Graduate Attributes

This course will provide students with an opportunity to develop the Graduate Attribute(s) specified below:

University Graduate Attribute	Course Learning Outcome(s)
Attribute 1: Deep discipline knowledge and intellectual breadth Graduates have comprehensive knowledge and understanding of their subject area, the ability to engage with different traditions of thought, and the ability to apply their knowledge in practice including in multi-disciplinary or multi-professional contexts.	1, 2, 3, 4, 5
Attribute 2: Creative and critical thinking, and problem solving Graduates are effective problems-solvers, able to apply critical, creative and evidence-based thinking to conceive innovative responses to future challenges.	1, 2, 3, 4
Attribute 3: Teamwork and communication skills Graduates convey ideas and information effectively to a range of audiences for a variety of purposes and contribute in a positive and collaborative manner to achieving common goals.	5
Attribute 4: Professionalism and leadership readiness Graduates engage in professional behaviour and have the potential to be entrepreneurial and take leadership roles in their chosen occupations or careers and communities.	1, 2, 3, 4
Attribute 5: Intercultural and ethical competency Graduates are responsible and effective global citizens whose personal values and practices are consistent with their roles as responsible members of society.	1, 5
Attribute 6: Australian Aboriginal and Torres Strait Islander cultural competency Graduates have an understanding of, and respect for, Australian Aboriginal and Torres Strait Islander values, culture and knowledge.	5
Attribute 7: Digital capabilities Graduates are well prepared for living, learning and working in a digital society.	1, 2, 3, 4, 5
Attribute 8: Self-awareness and emotional intelligence Graduates are self-aware and reflective; they are flexible and resilient and have the capacity to accept and give constructive feedback; they act with integrity and take responsibility for their actions.	4, 5

Learning Resources
Required Resources
- de Mesquita, J. M. C., & Kostelijk, E. (2021). Marketing Analytics: Statistical Tools for Marketing and Consumer Behavior Using SPSS. Routledge. ISBN: 9781000481747
Due to the practical nature of the subject, students should also rely on the lecture/tutorial slides and any additional material provided on MyUni by the subject coordinator. Additional readings will be available via the Course Readings link in the left-hand navigation panel. As a student in this class, you have full access to all University of Adelaide library resources.
Recommended Resources
1. Hair, J., Harrison, D.E., and Ajjan, H. (2022). Essentials of Marketing Analytics (1st Edition). MCGraw Hill. ISBN: 978-1-260-59774-5.
2. Lillien, G.L., Rangaswamy, A., and De Bruyn (2017). Principles of Marketing Engineering and Analytics (3rd Edition). DecisionPro, Inc. ISBN: 978-0985764821.
Learning & Teaching Activities
Learning & Teaching Modes

The subject is based on dynamic and interactive weekly sessions, comprising of a one-and-a-half-hour lecture and a one-and-a-half-hour tutorial. Both lecture and tutorial will involve critical debates, in-depth case discussions, in-class exercises, practical demonstrations, and student presentations. Students are expected to access materials provided online (lecture slides, textbooks, and other readings, videos and/or case studies) prior to class and to complete any set activities recommended by the lecturer.

Students are expected to review the weekly readings as well as online materials and to be able to discuss the material with other students during the course of the tutorials. Tutorials will include time where students will work together in student-led discussions of the exercise and/or case with the provision of tutor and peer feedback. The class will receive weekly feedback from both peers and instructors.

Workload

The information below is provided as a guide to assist students in engaging appropriately with the course requirements.

The University expects full-time students (i.e. those taking 12 units per semester) to devote a total of 48 hours per week to their studies. This means that you are expected to commit approximately 9 hours for a three-unit course or 13 hours for a four-unit course, of private study outside of your regular classes.

Learning Activities Summary
1. Overview of the Course and Introduction to Marketing Analytics
2. All About Data: Data Types, Data Management, and Wrangling
3. Measuring Customer Value
4. Assessing Measurement Scales: Validity, Reliability and Dimensionality
5. Experimental Research I: Experimental Designs and Applications
6. Experimental Research II: Advanced Experimental Analysis Methods
7. Predictive Analytics and Linear Regression
8. Discriminant Analysis and Logistic Regression
9. Analysis Methods for the STP Model I: Segmentation and Targeting
10. Analysis Methods for the STP Model II: Positioning
11. Market Basket Analysis
Specific Course Requirements
In order to enroll in MARKETNG 3002, students are required to have successfully completed the following courses:
- ECON 1008 - Data Analytics
- MARKETNG 1001 - Introduction to Marketing
- MARKETNG 2006 - Delivering Customer Insights
These subjects' contents will be considered assumed knowledge and briefly reviewed during the lectures and tutorials.

The University's policy on Assessment for Coursework Programs is based on the following four principles:

Assessment must encourage and reinforce learning.
Assessment must enable robust and fair judgements about student performance.
Assessment practices must be fair and equitable to students and give them the opportunity to demonstrate what they have learned.
Assessment must maintain academic standards.

Assessment Summary

Assessment Task	Task Type	Weighting	Learning Outcome
Two In-Class Quizzes	Individual	30%	1, 4, 5
Research Proposal	Group	10%	2, 5
Group Report and Presentation	Group	20%	1, 2, 3, 4
Weekly Homework (In-Class Participation)	Individual	10%	1, 2, 3, 4, 5
Take-Home Final Exam	Individual	30%	1, 3, 4

Assessment Detail

The assessment for this subject is made up of the following components:

Two in-class quizzes (30%), one in Week 7 (mid-term) and one in Week 12 (end-of-term). These quizzes are closed-book and will test students' knowledge and understanding of the topics covered in the lectures and the tutorials;
A group project (30%), which will require students to identify a marketing issue, collect data, interpret it, and provide recommendations based on their analysis to a company. This is a formative assignment and is made up of three parts:
- Part A: Group Project Research Proposal (10%) due in Week 6. Students will be required to deliver a research proposal, which should outline: (1) their main research problem/question, (2) their proposed methodology (including measures, sampling methods, and questionnaire draft), and (3) their result expectations (hypotheses);
- Part B: Group Project Report Presentation (5%) due in Week 11. Students will be required to present their research approach, methodology, and their preliminary findings in a 10-minute (max) presentation;
- Part C: Group Project Report (15%) due in Week 11. Students will be required to submit a report that outlines the main research problem(s), research questions, methodology, and the results of their research. The appendices should include the instruments utilised to collect data and the SPSS outcome/analysis. Students should integrate the feedback received on their presentation into the report;
Homework (In-Class Participation; 10%), assessed throughout the term. Students will be required to complete some weekly tasks aimed at strengthening their understanding of marketing analytics and developing their SPSS skills. These marks may be rounded up or down based on students' engagement in in-class discussions, participation in demonstrations (e.g., showing how to carry out homework, etc.), their willingness and proactiveness to help others, and general attitude both in lectures and tutorials;
A Take-home Final Exam (30%), due during the official final exam period. Students will be provided with a file, and they will have to conduct analyses on it using the methods learnt in class. They should finally draw conclusions and provide recommendations based on them. The turnaround for this assignment is one week;

Submission

Assignments must be submitted electronically via MyUni. For individual assignments, each student is responsible to submit their own work online, while group projects should only be submitted only by one of the group members.

Course Grading

Grades for your performance in this course will be awarded in accordance with the following scheme:

M10 (Coursework Mark Scheme)
Grade	Mark	Description
FNS		Fail No Submission
F	1-49	Fail
P	50-64	Pass
C	65-74	Credit
D	75-84	Distinction
HD	85-100	High Distinction
CN		Continuing
NFE		No Formal Examination
RP		Result Pending

Further details of the grades/results can be obtained from Examinations.

Grade Descriptors are available which provide a general guide to the standard of work that is expected at each grade level. More information at Assessment for Coursework Programs.

Final results for this course will be made available through Access Adelaide.

Student Feedback

The University places a high priority on approaches to learning and teaching that enhance the student experience. Feedback is sought from students in a variety of ways including on-going engagement with staff, the use of online discussion boards and the use of Student Experience of Learning and Teaching (SELT) surveys as well as GOS surveys and Program reviews.

SELTs are an important source of information to inform individual teaching practice, decisions about teaching duties, and course and program curriculum design. They enable the University to assess how effectively its learning environments and teaching practices facilitate student engagement and learning outcomes. Under the current SELT Policy (http://www.adelaide.edu.au/policies/101/) course SELTs are mandated and must be conducted at the conclusion of each term/semester/trimester for every course offering. Feedback on issues raised through course SELT surveys is made available to enrolled students through various resources (e.g. MyUni). In addition aggregated course SELT data is available.
Student Support
Policies & Guidelines
This section contains links to relevant assessment-related policies and guidelines - all university policies.
Fraud Awareness

Students are reminded that in order to maintain the academic integrity of all programs and courses, the university has a zero-tolerance approach to students offering money or significant value goods or services to any staff member who is involved in their teaching or assessment. Students offering lecturers or tutors or professional staff anything more than a small token of appreciation is totally unacceptable, in any circumstances. Staff members are obliged to report all such incidents to their supervisor/manager, who will refer them for action under the university's student’s disciplinary procedures.

The University of Adelaide is committed to regular reviews of the courses and programs it offers to students. The University of Adelaide therefore reserves the right to discontinue or vary programs and courses without notice. Please read the important information contained in the disclaimer.

Authorised by:	Deputy Vice-Chancellor and Vice-President (Academic)
Maintained by:	Course Outlines Administrator