Students
MKTG310 – Marketing Metrics
2014 – S2 Day
General Information
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| Unit convenor and teaching staff |
Unit convenor and teaching staff
Associate Professor in Business
Hume Winzar
Contact via Desk Phone: (02 9850) 6468
E4A 633
Thursday 11:00am to 1:00pm, or by appointment
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|---|---|
| Credit points |
Credit points
3
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| Prerequisites |
Prerequisites
MKTG101 and MKTG202 and MKTG203
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| Corequisites |
Corequisites
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| Co-badged status |
Co-badged status
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| Unit description |
Unit description
This unit introduces the conceptual and practical issues in developing models to aid in decision making in marketing. It considers a wide range of problems, with students developing practical skills in model building in applied computer sessions. Students will also translate those analytic models into competitive strategy models by making policy recommendations.
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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:
- Understand the benefits and objectives of marketing analytics
- Apply of spreadsheet-based models to resolve marketing problems
- Proficiency in the application of strategic decision models and metrics
- Ability to communicate to senior executives through data and data visualisation
General Assessment Information
Late Submissions
No extensions will be granted. Late submissions will be accepted up to 72 hours after the submission deadline.
There will be a deduction of 20% (4 marks) of the total available marks made from the total awarded mark for each 24 hour period, or part thereof, that the submission is late. For example, 25 hours late in submission – 40% penalty (8 marks).
This penalty does not apply for cases in which an application for special consideration is made and approved.
Assessment Tasks
| Name | Weighting | Due |
|---|---|---|
| Spreadsheet Skills | 20% | Week #5 |
| Data Visualisation Skills | 20% | Week #9 |
| Optimisation Skills | 20% | Week #12 |
| Final Examination | 40% | Examination Period |
Spreadsheet Skills
Due: Week #5
Weighting: 20%
Individual online submission demonstrating skills in:
- Spreadsheet data manipulation and presentation
Specific assessment tasks, data sets and marking guides are presented in the iLearn website.
On successful completion you will be able to:
- Understand the benefits and objectives of marketing analytics
- Apply of spreadsheet-based models to resolve marketing problems
- Ability to communicate to senior executives through data and data visualisation
Data Visualisation Skills
Due: Week #9
Weighting: 20%
Individual online submissions demonstrating skills in:
- Data visualisation
Specific assessment tasks, data sets and marking guides are presented in the iLearn website.
On successful completion you will be able to:
- Understand the benefits and objectives of marketing analytics
- Proficiency in the application of strategic decision models and metrics
- Ability to communicate to senior executives through data and data visualisation
Optimisation Skills
Due: Week #12
Weighting: 20%
Individual online submission demonstrating skills in:
- Optimisation using Solver
Specific assessment tasks, data sets and marking guides are presented in the iLearn website.
On successful completion you will be able to:
- Understand the benefits and objectives of marketing analytics
- Apply of spreadsheet-based models to resolve marketing problems
- Proficiency in the application of strategic decision models and metrics
- Ability to communicate to senior executives through data and data visualisation
Final Examination
Due: Examination Period
Weighting: 40%
Three (3) hour examination, consisting of short-answer questions based on a case problem and conceptual and analytical issues.
On successful completion you will be able to:
- Understand the benefits and objectives of marketing analytics
- Proficiency in the application of strategic decision models and metrics
Delivery and Resources
Required and Recommended Texts and/or Materials
Prescribed Unit Materials
Winston, Wayne L. (2014) Marketing Analytics: Data-Driven Techniques with Microsoft Excel, Wiley ISBN: 978-1-118-37343-9
Technology Used and Required
Students are required to learn how to use spreadsheet and word processing programs, statistical software (MINITAB or SPSS) and iLearn.
Unit Web Page
Course material is available on the learning management system (iLearn). The general online website is http://ilearn.mq.edu.au
Teaching and Learning Strategy
This is a predominantly applied course, designed to provide students with technical and analytical skills. Time in the “lectures” will be mostly a seminar/workshop format, with discussion of problems and demonstration of alternative solutions. Tutorials are held in PC Labs and provide an opportunity to try out different analytical approaches hands-on. The limited face-to-face time in class is not sufficient to learn all that we will need to develop some competence in the software and methods discussed and examined. Students will need to practice and research outside of the classroom.
Research and Practice
This unit draws from current research undertaken by the instructor and other members of the Faculty of Business and Economics. Examples of research results, instrumentation, and raw data are used in lectures and workshops to expand on and update the information presented in the unit readings.
Satisfactory Completion of the unit
Satisfactory completion of this unit, MKTG310 Marketing Metrics, requires that you achieve a minimum score of 50% overall for the total of all assessments. You do not need to pass all assessment items, including the final examination, to earn a pass overall. Generally, the following criteria are used as guidelines for grades awarded in this unit:
| Mark | Grade |
|---|---|
| 0% - 49% | Fail (F) |
| 50% - 64% | Pass (P) |
| 65% - 74% | Credit (C) |
| 75% - 84% | Distinction (D) |
| 85% - 100% | High Distinction (HD) |
Timetable
Timetables for this and other units, and for end-of-session examinations can be found at the Timetables portal: http://timetables.mq.edu.au
Unit Schedule
The following schedule contains topics for each week, and dates for each assessment item.
Textbook readings, and online resources are presented in the Unit Website on iLearn.
Week# |
Topic |
Readings, Activities & Assessment |
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1 |
Measurement and Modelling theory PivotTables & PivotCharts |
Winston, Chapters 1 & 2 |
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2 |
Pricing & Revenue MS Excel data handling, Graphs |
Winston, Chapters 4, 5, 6 & 7 |
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3 |
Summarising Sales |
Winston, Chapters 8, 9, & 10 |
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4 |
Forecasting Sales & Revenue Monte Carlo Simulation |
Winston, Chapters 10, 11, 12, 13 & 14 |
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5 |
Data Visualisation theory Introducing Tableau Software |
Tableau online video training Assignment #1: Excel Data Manipulation & Graphing (Online submission: Midnight Friday 5 August) |
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6 |
Combining data sources, Metadata Visualising events over time |
Tableau online video training |
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7 |
Social Media and Web traffic tools Google Analytics in Tableau |
Tableau online video training |
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8 |
Data calculation and advanced charts in Tableau |
Tableau online video training |
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9 |
Summarising Sales over time Forecasting Sales in Tableau Forecasting in Excel |
Tableau online video training Assignment #2: Data Visualisation (Online submission: Midnight, Friday 17 October) |
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10 |
Customer Lifetime Value Simulation and forecasting Using Solver in Excel for Optimisation |
Winston Chapters 19, 20 & 21 |
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11 |
New Product Forecasting Bass Models, Confidence Intervals Using Solver in Excel for Optimisation |
Winston Chapters 26, 27, 28, 29, 30 & 31 |
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12 |
Promotions Metrics and modelling Using Solver in Excel for Optimisation |
Winston Chapters 34, 35 & 36 Assignment #3: Optimisation & Modelling (Online submission: Midnight Friday, 7 November) |
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13 |
Review and Examination Preparation |
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Exam Period |
Final Examination |
Policies and Procedures
Macquarie University policies and procedures are accessible from Policy Central. Students should be aware of the following policies in particular with regard to Learning and Teaching:
Academic Honesty Policy http://mq.edu.au/policy/docs/academic_honesty/policy.html
Assessment Policy http://mq.edu.au/policy/docs/assessment/policy.html
Grading Policy http://mq.edu.au/policy/docs/grading/policy.html
Grade Appeal Policy http://mq.edu.au/policy/docs/gradeappeal/policy.html
Grievance Management Policy http://mq.edu.au/policy/docs/grievance_management/policy.html
Disruption to Studies Policy http://www.mq.edu.au/policy/docs/disruption_studies/policy.html The Disruption to Studies Policy is effective from March 3 2014 and replaces the Special Consideration Policy.
In addition, a number of other policies can be found in the Learning and Teaching Category of Policy Central.
Student Code of Conduct
Macquarie University students have a responsibility to be familiar with the Student Code of Conduct: https://students.mq.edu.au/support/student_conduct/
Student Support
Macquarie University provides a range of support services for students. For details, visit http://students.mq.edu.au/support/
Learning Skills
Learning Skills (mq.edu.au/learningskills) provides academic writing resources and study strategies to improve your marks and take control of your study.
Student Services and Support
Students with a disability are encouraged to contact the Disability Service who can provide appropriate help with any issues that arise during their studies.
Student Enquiries
For all student enquiries, visit Student Connect at ask.mq.edu.au
IT Help
For help with University computer systems and technology, visit http://informatics.mq.edu.au/help/.
When using the University's IT, you must adhere to the Acceptable Use Policy. The policy applies to all who connect to the MQ network including students.
Graduate Capabilities
Discipline Specific Knowledge and Skills
Our graduates will take with them the intellectual development, depth and breadth of knowledge, scholarly understanding, and specific subject content in their chosen fields to make them competent and confident in their subject or profession. They will be able to demonstrate, where relevant, professional technical competence and meet professional standards. They will be able to articulate the structure of knowledge of their discipline, be able to adapt discipline-specific knowledge to novel situations, and be able to contribute from their discipline to inter-disciplinary solutions to problems.
This graduate capability is supported by:
Learning outcomes
- Understand the benefits and objectives of marketing analytics
- Apply of spreadsheet-based models to resolve marketing problems
- Proficiency in the application of strategic decision models and metrics
Assessment tasks
- Spreadsheet Skills
- Optimisation Skills
- Final Examination
Critical, Analytical and Integrative Thinking
We want our graduates to be capable of reasoning, questioning and analysing, and to integrate and synthesise learning and knowledge from a range of sources and environments; to be able to critique constraints, assumptions and limitations; to be able to think independently and systemically in relation to scholarly activity, in the workplace, and in the world. We want them to have a level of scientific and information technology literacy.
This graduate capability is supported by:
Learning outcomes
- Understand the benefits and objectives of marketing analytics
- Apply of spreadsheet-based models to resolve marketing problems
- Ability to communicate to senior executives through data and data visualisation
Assessment tasks
- Spreadsheet Skills
- Data Visualisation Skills
- Final Examination
Problem Solving and Research Capability
Our graduates should be capable of researching; of analysing, and interpreting and assessing data and information in various forms; of drawing connections across fields of knowledge; and they should be able to relate their knowledge to complex situations at work or in the world, in order to diagnose and solve problems. We want them to have the confidence to take the initiative in doing so, within an awareness of their own limitations.
This graduate capability is supported by:
Learning outcomes
- Understand the benefits and objectives of marketing analytics
- Apply of spreadsheet-based models to resolve marketing problems
- Proficiency in the application of strategic decision models and metrics
Assessment tasks
- Spreadsheet Skills
- Data Visualisation Skills
- Optimisation Skills
- Final Examination
Effective Communication
We want to develop in our students the ability to communicate and convey their views in forms effective with different audiences. We want our graduates to take with them the capability to read, listen, question, gather and evaluate information resources in a variety of formats, assess, write clearly, speak effectively, and to use visual communication and communication technologies as appropriate.
This graduate capability is supported by:
Learning outcomes
- Understand the benefits and objectives of marketing analytics
- Apply of spreadsheet-based models to resolve marketing problems
- Proficiency in the application of strategic decision models and metrics
- Ability to communicate to senior executives through data and data visualisation
Assessment tasks
- Spreadsheet Skills
- Data Visualisation Skills
- Optimisation Skills
- Final Examination
Changes from Previous Offering
Changes since First Published
| Date | Description |
|---|---|
| 23/01/2014 | The Prerequisites was updated. |