Unit convenor and teaching staff | Unit convenor and teaching staff |
---|---|
Credit points |
Credit points
10
|
Prerequisites |
Prerequisites
40cp at 2000 level or above including MKTG2013 and MKTG2017
|
Corequisites |
Corequisites
|
Co-badged status |
Co-badged status
|
Unit description |
Unit description
The digital revolution has created an enormous volume of data about markets, customers and the business environment which marketers have sought to incorporate into their strategic decision-making. Yet, raw data on its own adds very little to the strategic decision process. Marketers need to understand how to organise and analyse available data to generate actionable insights. Such insights are useful in anticipating future consumer needs, identifying trends, forecasting market conditions, gauging competition and making informed predictions about an ever-changing environment. Marketers then utilise these insights to build compelling narratives and to provide actionable recommendations for important marketing decisions. In this unit students will investigate appropriate data, data sources and analytic techniques required to generate input for key marketing decisions regarding markets and customers. Students will assess suitable data analysis techniques and evaluate generated output to develop insights and determine potential marketing decision options. Additionally, students will appraise these key options by estimating likely impacts and integrating these impacts with practical organisational issues. |
Information about important academic dates including deadlines for withdrawing from units are available at https://www.mq.edu.au/study/calendar-of-dates
On successful completion of this unit, you will be able to:
Late submissions of assessments Unless a Special Consideration request has been submitted and approved, no extensions will be granted. There will be a deduction of 10% of the total available assessment-task marks made from the total awarded mark for each 24-hour period or part thereof that the submission is late. Late submissions will only be accepted up to 96 hours after the due date and time.
No late submissions will be accepted for timed assessments – e.g., quizzes, online tests.
Table 1: Penalty calculation based on submission time
Submission time after the due date (including weekends) |
Penalty (% of available assessment task mark) |
Example: for a non-timed assessment task marked out of 30 |
< 24 hours |
10% |
10% x 30 marks = 3-mark deduction |
24-48 hours |
20% |
20% x 30 marks = 6-mark deduction |
48-72 hours |
30% |
30% x 30 marks = 9-mark deduction |
72-96 hours |
40% |
40% x 30 marks = 12-mark deduction |
> 96 hours |
100% |
Assignment won’t be accepted |
Special Consideration To request an extension on the due date/time for a timed or non-timed assessment task, you must submit a Special Consideration application. An application for Special Consideration does not guarantee approval.
The approved extension date for a student becomes the new due date for that student. The late submission penalties above then apply as of the new due date.
Name | Weighting | Hurdle | Due |
---|---|---|---|
Online Assignment | 25% | No | Weeks 2-6 and Weeks 8-12 |
Customer Insights Critique | 25% | No | Week 7 |
Report | 50% | No | Week 13 |
Assessment Type 1: Participatory task
Indicative Time on Task 2: 12 hours
Due: Weeks 2-6 and Weeks 8-12
Weighting: 25%
Students will provide a written response to a weekly question that is posted to iLearn. Students’ responses need to use data sources to investigate marketing problems/opportunities and connect content to models/frameworks. Each response will be a minimum of 100 words and a maximum of 200 words.
Assessment Type 1: Case study/analysis
Indicative Time on Task 2: 12 hours
Due: Week 7
Weighting: 25%
Students will critique a provided Insights Analysis. They will apply models/frameworks to provided data sources to generate insights and then synthesise insights to communicate recommendations. Length: 1500 words
Assessment Type 1: Report
Indicative Time on Task 2: 25 hours
Due: Week 13
Weighting: 50%
Students will use customer datasets and apply models/frameworks to generate insights and then synthesise the insights to communicate recommendations in response to marketing problems/opportunities. Length: 2500 words
1 If you need help with your assignment, please contact:
2 Indicative time-on-task is an estimate of the time required for completion of the assessment task and is subject to individual variation
Please refer to iLearn.
Macquarie University policies and procedures are accessible from Policy Central (https://policies.mq.edu.au). Students should be aware of the following policies in particular with regard to Learning and Teaching:
Students seeking more policy resources can visit Student Policies (https://students.mq.edu.au/support/study/policies). It is your one-stop-shop for the key policies you need to know about throughout your undergraduate student journey.
To find other policies relating to Teaching and Learning, visit Policy Central (https://policies.mq.edu.au) and use the search tool.
Macquarie University students have a responsibility to be familiar with the Student Code of Conduct: https://students.mq.edu.au/admin/other-resources/student-conduct
Results published on platform other than eStudent, (eg. iLearn, Coursera etc.) or released directly by your Unit Convenor, are not confirmed as they are subject to final approval by the University. Once approved, final results will be sent to your student email address and will be made available in eStudent. For more information visit ask.mq.edu.au or if you are a Global MBA student contact globalmba.support@mq.edu.au
At Macquarie, we believe academic integrity – honesty, respect, trust, responsibility, fairness and courage – is at the core of learning, teaching and research. We recognise that meeting the expectations required to complete your assessments can be challenging. So, we offer you a range of resources and services to help you reach your potential, including free online writing and maths support, academic skills development and wellbeing consultations.
Macquarie University provides a range of support services for students. For details, visit http://students.mq.edu.au/support/
The Writing Centre provides resources to develop your English language proficiency, academic writing, and communication skills.
The Library provides online and face to face support to help you find and use relevant information resources.
Macquarie University offers a range of Student Support Services including:
Got a question? Ask us via AskMQ, or contact Service Connect.
For help with University computer systems and technology, visit http://www.mq.edu.au/about_us/offices_and_units/information_technology/help/.
When using the University's IT, you must adhere to the Acceptable Use of IT Resources Policy. The policy applies to all who connect to the MQ network including students.
Unit information based on version 2022.02 of the Handbook