Late Submission Statement:

Sometimes unavoidable circumstances occur that might prevent you from submitting an assignment on time and, in that case, you may be eligible to lodge a Special Consideration request.

Unless a Special Consideration request has been submitted and approved, please note that no extensions to assignment deadlines will be granted. Assignments that are submitted late will attract a late penalty:

1. There will be a deduction of 10% of the total available marks made from the total awarded mark for each 24 hour period or part thereof that the submission is late.
2. No assignment will be accepted more than 72 hours after the due date and time (incl. weekends) after the original due date.
3. No late submissions will be accepted for timed assessments (e.g., quizzes, online tests) or for tasks with a weighting of 10% or less of the total unit assessment.

Classes

• 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/

Required and Recommended Texts and/or Materials

Prescribed Text:

• Joseph Hair, Dana E. Harrison and Haya Ajjan (2021) “Essentials of Marketing Analytics (International Student Edition) ” McGraw-Hill Education - ISBN13: 9781264263608; ISBN10: 1264263600

Other Useful Texts:

• Rajkumar Venkatesan, Paul Farris and Ronald T. Wilcox (2015) “Cutting Edge Marketing Analytics: Real World Cases and Data Sets for Hands-On Learning” Pearson Education - ISBN-13: 978-0133552522; ISBN-10: 0133552527
• Chuck Chakrapani (2018) “Analytics for Customer Insights: A Non-Technical Introduction” ISBN- 10:0920219527

• Ömer Artun and Dominique Levin (2015) “Predictive Marketing: Easy Ways Every Marketer Can Use Customer Analytics and Big Data” Wiley, ISBN 978-1-119-03736-1 (hardback); ISBN 978-1-119-03732-3 (ePDF); ISBN 978-1-119-03733-0 (ePub)
• Mike Grigsby (2018) “Marketing Analytics: A Practical Guide to Improving Consumer Insights Using Data Techniques” 2^nd Edition, Kogan Page, ISBN 978 0 7494 8216 9; E-ISBN 978 0 7494 8217 6

Technology Used and Required:

• 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: MS-Word, MS-PowerPoint, MS-Excel, SPSS statistical software, SQL software, IBM Cognos Analytics, Tableau, RapidMiner, Python, TextBlob, Vader

Unit Web Page

• The web page for this unit can be found at: iLearn http://ilearn.mq.edu.au
• All announcements and resources will be available on the web site. Resource materials include lecture slides, practice questions, case studies and other materials. There is also a forum for student interaction and contact with faculty. You should consult the unit Website several times per week for messages and updates.

Learning and Teaching Activities

• This unit will be conducted via a 1-hour online lecture and a 2-hour weekly workshop each week. The unit topics will be divided into 4 main modules with each module typically consisting of 3 weeks. Each workshop will consist of activities including case study discussions, data analysis and interactive learning tasks.

This unit is being offered for the first time in S2, 2021