Students

MKTG310 – Marketing Metrics

2019 – S2 Day

General Information

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Unit convenor and teaching staff Unit convenor and teaching staff Unit Convenor/Lecturer
Dr. Jun Yao
jun.yao@mq.edu.au
Contact via Email
4ER 653
Thursday 2:30pm - 3:30pm
Credit points Credit points
3
Prerequisites Prerequisites
MKTG202 and (MKTG203 or MKTG204 or MKTG207 or MKTG208 or MKTG209)
Corequisites Corequisites
Co-badged status Co-badged status
Unit description Unit description
Data is a key to marketing success. Effective use of data enables organisations to make better marketing decisions and effectively measure their marketing performance. In recent years, data-driven marketing has become increasingly important and prevalent in the business world due to the availability of a growing range of data and computing power. This unit develops students’ knowledge and skills in building and interpreting quantitative analytical models. Students learn to apply a range of marketing models and metrics to analyse marketing data that assists in assessing marketing performance and making optimal and competitive marketing decisions. Students gain knowledge on identifying marketing problems, analysing data, interpreting results and developing solutions for a range of marketing 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:

  • Explain and apply marketing models and metrics to solve a range of marketing problems.
  • Analyze and interpret output of marketing analytics to develop management recommendations.
  • Recognize and demonstrate the assumptions and limitations of various marketing models and metrics.
  • Communicate marketing problems and solutions effectively through data and data visualisation.

Assessment Tasks

Name Weighting Hurdle Due
Market Share Analysis 20% No Week 4, Friday 11:59PM
Price Promotion Analysis 20% No Week 8, Friday 11:59PM
Data Visualisation 20% No Week 12, Friday 11:59PM
Final Examination 40% No Examination Period

Market Share Analysis

Due: Week 4, Friday 11:59PM
Weighting: 20%

Task Description: This is an individual assessment that involves analyzing market share data with appropriate metrics/models, interpreting output , developing management recommendations and reporting. Specific assessment task, data set and marking guide will be provided on iLearn. Type of Collaboration: Individual Submission: Submit your assignment through the Turnitin link on iLearn, no hard copies of soft copies via email will be accepted. You must submit by the due date as specified. Format: Please refer to the iLearn Unit page Length: Please refer to the iLearn Unit page Inherent Task Requirement No Late Submissions: No extensions will be granted, except for cases in which an application for Special Consideration is made and approved. Late submission will incur a penalty of 10% of the total available marks for each 24 hour period or part thereof (for example, 25 hours late in submission - 4 marks penalty on a 20% assignment). Penalties do not apply when an application for Special Consideration is made and approved. No submission will be accepted after solutions have been posted. 
On successful completion you will be able to:
  • Explain and apply marketing models and metrics to solve a range of marketing problems.
  • Analyze and interpret output of marketing analytics to develop management recommendations.
  • Recognize and demonstrate the assumptions and limitations of various marketing models and metrics.
  • Communicate marketing problems and solutions effectively through data and data visualisation.

Price Promotion Analysis

Due: Week 8, Friday 11:59PM
Weighting: 20%

Task Description: This is an individual assessment that involves analyzing price promotion data with appropriate metrics/models, interpreting output , developing management recommendations and reporting. Specific assessment task, data set and marking guide will be provided on iLearn. Type of Collaboration: Individual Submission: Submit your assignment through the Turnitin link on iLearn, no hard copies of soft copies via email will be accepted. You must submit by the due date as specified. Format: Please refer to the iLearn Unit page Length: Please refer to the iLearn Unit page Inherent Task Requirement No Late Submissions: No extensions will be granted, except for cases in which an application for Special Consideration is made and approved. Late submission will incur a penalty of 10% of the total available marks for each 24 hour period or part thereof (for example, 25 hours late in submission - 4 marks penalty on a 20% assignment). Penalties do not apply when an application for Special Consideration is made and approved. No submission will be accepted after solutions have been posted. 
On successful completion you will be able to:
  • Explain and apply marketing models and metrics to solve a range of marketing problems.
  • Analyze and interpret output of marketing analytics to develop management recommendations.
  • Recognize and demonstrate the assumptions and limitations of various marketing models and metrics.
  • Communicate marketing problems and solutions effectively through data and data visualisation.

Data Visualisation

Due: Week 12, Friday 11:59PM
Weighting: 20%

Task Description: This is an individual assessment that involves analyzing the sales data and visualising the data with Tableau Software. Specific assessment task, data set and marking guide will be provided on iLearn. Type of Collaboration: Individual Submission: Submit your assignment through the Turnitin link on iLearn, no hard copies of soft copies via email will be accepted. You must submit by the due date as specified. Format: Please refer to the iLearn Unit page Length: Please refer to the iLearn Unit page Inherent Task Requirement No Late Submissions: No extensions will be granted, except for cases in which an application for Special Consideration is made and approved. Late submission will incur a penalty of 10% of the total available marks for each 24 hour period or part thereof (for example, 25 hours late in submission - 4 marks penalty on a 20% assignment). Penalties do not apply when an application for Special Consideration is made and approved. No submission will be accepted after solutions have been posted. 
On successful completion you will be able to:
  • Analyze and interpret output of marketing analytics to develop management recommendations.
  • Communicate marketing problems and solutions effectively through data and data visualisation.

Final Examination

Due: Examination Period
Weighting: 40%

Task Description: A closed-book 2 hours final examination will be held during the University's formal examination period. The final examination provides assurance that the student has attained the knowledge and skills assessed by the exam. Type of Collaboration: Individual Submission: Students are expected to present for examination at the time and place designated in the University Examination Timetable. Format: Details will be provided in the Week 13 lecture Length: 2 hours Inherent Task Requirement No Late Submissions: Please see Assessment Policy Schedule 4
On successful completion you will be able to:
  • Explain and apply marketing models and metrics to solve a range of marketing problems.
  • Analyze and interpret output of marketing analytics to develop management recommendations.
  • Recognize and demonstrate the assumptions and limitations of various marketing models and metrics.

Delivery and Resources

Classes

  • 3 hours face-to-face teaching per week consisting of: 1 × 1.5-hour lecture and 1 × 1.5-hour tutorial (lab session). Tutorials commence in Week 2. 
  • The timetable for classes can be found on the university website at: http://timetable.mq.edu.au

Recommended Texts and/or Materials

Prescribed text:

Farris, P., Bendle, N., Pfeifer, P.E. and Reibstein, D.J. (2015). Marketing Metrics: The Manager's Guide to Measuring Marketing Performance. Pearson. ISBN: 978-0-13-408596-8

Recommended text:

Winston, Wayne L. (2014) Marketing Analytics: Data-Driven Techniques with Microsoft Excel, Wiley ISBN: 978-1-118-37343-9

Grigsby, M. (2015), Marketing Analytics: A Practical Guide to Real Marketing Science, KoganPlay EAN: 9780749474171

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 practice exam questions for both the within-semester and final exams. There is also a forum for student interaction and contact with faculty. You should consult the course Website several times per week for messages and updates.

Teaching and Learning Strategy

This unit is aimed at students who have developed higher levels of strategic insight and who desire improved skills in data manipulation, analysis and presentation. This is a predominantly applied course, designed to provide students with technical and analytical skills. Lecture attendance is critical, as it is only by attending lectures that students will understand the concepts used in tutorials. Tutorials are held in PC Labs and provide an opportunity to practice analytics 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.

Satisfactory Completion of Unit

  • It is normally expected that students attempt all assessment tasks for this unit. Students are required to accumulate at least 50% of the total marks possible in order to satisfactorily pass this unit.

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#

Lecture Topic

Tutorial Activities & Assessment

1

Unit Introduction and Overview

No tutorials this week, tutorials commence in Week 2

2

Market Share Analysis 

Weekly laboratory exercise: Basic Excel skills, NPS 

3

Multi-Attribute Framework

Weekly laboratory exercise: Market Share Analysis

4

Conjoint Analysis

Weekly laboratory exercise: Multinomial Logit Model

Assignment 1 is due by 11:59PM Friday (23 August) 
5

New Product Diffusion

 Weekly laboratory exercise: Conjoint Analysis
6

Price Promotion Analysis

 Weekly laboratory exercise: Bass Diffusion Model
7

Customer Profitability

 Weekly laboratory exercise: Evaluation of Price Promotion
 

Mid Session Break 

  
8

Pricing Strategy

Weekly laboratory exercise: Customer Lifetime Value and Customer Equity

Assignment 2 is due by 11:59PM Friday (4 October) 
9

Data Visualisation Theory

Introducing Tableau Software

 Weekly laboratory exercise: Pricing Strategy 

10

 Sales Analysis

Weekly laboratory exercise: Data Blending and Chart Creation in Tableau
11

Advertising Metrics

 Weekly laboratory exercise: Sales Analysis using Tableau 
12

Marketing and Finance

Weekly laboratory exercise: Advertising Metrics

Assignment 3 is due by 11:59PM Friday (1 November) 

13

Review and Examination Preparation

Weekly laboratory exercise: Marketing and Finance

 

Examination Period

Final Examination

Policies and Procedures

Macquarie University policies and procedures are accessible from Policy Central (https://staff.mq.edu.au/work/strategy-planning-and-governance/university-policies-and-procedures/policy-central). Students should be aware of the following policies in particular with regard to Learning and Teaching:

Undergraduate students seeking more policy resources can visit the Student Policy Gateway (https://students.mq.edu.au/support/study/student-policy-gateway). It is your one-stop-shop for the key policies you need to know about throughout your undergraduate student journey.

If you would like to see all the policies relevant to Learning and Teaching visit Policy Central (https://staff.mq.edu.au/work/strategy-planning-and-governance/university-policies-and-procedures/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/study/getting-started/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 ask.mq.edu.au or if you are a Global MBA student contact globalmba.support@mq.edu.au

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

If you are a Global MBA student contact globalmba.support@mq.edu.au

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.

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

  • Explain and apply marketing models and metrics to solve a range of marketing problems.
  • Analyze and interpret output of marketing analytics to develop management recommendations.
  • Recognize and demonstrate the assumptions and limitations of various marketing models and metrics.
  • Communicate marketing problems and solutions effectively through data and data visualisation.

Assessment tasks

  • Market Share Analysis
  • Price Promotion Analysis
  • Data Visualisation
  • 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

  • Explain and apply marketing models and metrics to solve a range of marketing problems.
  • Analyze and interpret output of marketing analytics to develop management recommendations.
  • Recognize and demonstrate the assumptions and limitations of various marketing models and metrics.

Assessment tasks

  • Market Share Analysis
  • Price Promotion Analysis
  • Data Visualisation
  • 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

  • Explain and apply marketing models and metrics to solve a range of marketing problems.
  • Analyze and interpret output of marketing analytics to develop management recommendations.
  • Communicate marketing problems and solutions effectively through data and data visualisation.

Assessment tasks

  • Market Share Analysis
  • Price Promotion Analysis
  • Data Visualisation
  • 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 outcome

  • Communicate marketing problems and solutions effectively through data and data visualisation.

Assessment tasks

  • Market Share Analysis
  • Price Promotion Analysis
  • Data Visualisation

Changes from Previous Offering

  1. UC's consultation time is added.
  2. The length of the final exam is reduced from 3 hours to 2 hours.
  3. Weekly teaching activities consist of an 1.5-hour lecture and an 1.5-hour tutorial.