Students

MKTG3008 – Marketing and Customer Insights

2024 – Session 2, In person-scheduled-weekday, North Ryde

General Information

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Unit convenor and teaching staff Unit convenor and teaching staff Unit convenor and lecturer
Husain Akareem
husain.akareem@mq.edu.au
Contact via Email
4ER, Room 241
Tuesday 14:00 - 15:00
Credit points Credit points
10
Prerequisites Prerequisites
130cp at 1000 level or above including MKTG2002
Corequisites Corequisites
MKTG2017
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.

Important Academic Dates

Information about important academic dates including deadlines for withdrawing from units are available at https://www.mq.edu.au/study/calendar-of-dates

Learning Outcomes

On successful completion of this unit, you will be able to:

  • ULO2: Apply models/frameworks to generate marketing insights from data.
  • ULO1: Utilise data sources and variables to investigate marketing problems/opportunities.
  • ULO3: Synthesise insights and communicate recommendations to marketing decision-makers.

General Assessment Information

Late Assessment Submission Penalty (written assessments)   

Unless a Special Consideration request has been submitted and approved, a 5% penalty (of the total possible mark) will be applied each day a written assessment is not submitted, up until the 7th day (including weekends). After the 7th day, a grade of ‘0’ will be awarded even if the assessment is submitted. Submission time for all written assessments is set at 11.55pm. A 1-hour grace period is provided to students who experience a technical concern.   

For any late submissions of time-sensitive tasks, such as scheduled tests/exams, performance assessments/presentations, and/or scheduled practical assessments/labs, students need to submit an application for Special Consideration. 

Assessment Tasks

Name Weighting Hurdle Due
Practice-based Tasks 30% No Week 1 to Week 12
Quantitative Project 40% No Week 8
Qualitative Analysis Task 30% No Week 13

Practice-based Tasks

Assessment Type 1: Practice-based task
Indicative Time on Task 2: 15 hours
Due: Week 1 to Week 12
Weighting: 30%

 

Various practice-based tasks will be given throughout the semester. Some of these are take-home tasks, others are to be completed during the workshops. They might include using different software such as Tableau, completion of worksheets, hands-on practices etc. There will be minimum of three tasks. Each task is worth 10%

 
On successful completion you will be able to:
  • Apply models/frameworks to generate marketing insights from data.

Quantitative Project

Assessment Type 1: Project
Indicative Time on Task 2: 20 hours
Due: Week 8
Weighting: 40%

 

This is an individual assessment that involves conducting quantitative analysis using various industry relevant software analytic tools on a given dataset, interpreting results and writing a summary of the insights gained. Specific instructions and marking guide will be provided on iLearn. Analysis and 1,500 word results

 
On successful completion you will be able to:
  • Utilise data sources and variables to investigate marketing problems/opportunities.
  • Synthesise insights and communicate recommendations to marketing decision-makers.

Qualitative Analysis Task

Assessment Type 1: Qualitative analysis task
Indicative Time on Task 2: 14 hours
Due: Week 13
Weighting: 30%

 

This is an individual assessment that involves conducting qualitative analysis using various industry relevant software analytic tools on qualitative data, interpreting results and presenting a summary of the insights gained. Specific instructions and marking guide will be provided on iLearn. Analysis and video results summary

 
On successful completion you will be able to:
  • Utilise data sources and variables to investigate marketing problems/opportunities.
  • Synthesise insights and communicate recommendations to marketing decision-makers.

1 If you need help with your assignment, please contact:

  • the academic teaching staff in your unit for guidance in understanding or completing this type of assessment
  • the Writing Centre for academic skills support.

2 Indicative time-on-task is an estimate of the time required for completion of the assessment task and is subject to individual variation

Delivery and Resources

RECOMMENDED READING AND RESOURCES

  1. https://www.tableau.com/en-gb/resources
  2. https://displayrtest.wpengine.com/resources/
  3. https://education.rstudio.com/learn/beginner/
  4. Nussbaumer Knaflic, C., 2015. Storytelling with data: a data visualization guide for business professionals. Hoboken: John Wiley & Sons, 2, pp.165-185.
  5. Nussbaumer Knaflic, C., 2019. Storytelling with data: let's practice!. John Wiley & Sons.
  6. https://www.storytellingwithdata.com/

Additional recommended readings and resources will be provided on iLearn.

TECHNOLOGY NEEDS

  • Students will need to have access to a personal computer, with access to the Internet and word processing software.
  • Software which will feature in the unit: Tableau, Displayr, R.

DELIVERY FORMAT

  • 3 hours per week consisting of 1 hour of online lecture and one 2-hour workshop each week.
  • The timetable for classes can be found on the University website at: http://www.timetables.mq.edu.au/

Unit Schedule

  1. Introduction to Insights & Tableau

  2. Data visualization with Tableau

  3. Review of basic statistics & Intridcution to Displar

  4. Net Promoter Scores (NPS) & visualization with Displayr

  5. Correspondence Analysis with Displayr

  6. Regression with Displayr

  7. Experiments & Conjoint design with Displayr

  8. Conjoint Analysis & Story Telling with Displayr

  9. Introduction to R & Visualization with R

  10. Text Analysis with R

  11. Regression with R

  12. Customer Life-time Value (CLV) with R

  13. Market Basket with R

Policies and Procedures

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.

Student Code of Conduct

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

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 connect.mq.edu.au or if you are a Global MBA student contact globalmba.support@mq.edu.au

Academic Integrity

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.

Student Support

Macquarie University provides a range of support services for students. For details, visit http://students.mq.edu.au/support/

The Writing Centre

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. 

Student Services and Support

Macquarie University offers a range of Student Support Services including:

Student Enquiries

Got a question? Ask us via the Service Connect Portal, or contact Service Connect.

IT Help

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.

Changes from Previous Offering

Tableau, Net Promoter Scores, and Conjoint Analysis have been added.  Factor Analysis and Cluster Analysis have been deleted.

Unit information based on version 2024.04 of the Handbook