Unit Outline
BMA708
Marketing Insights into Big Data
Semester 1, 2024
Denni Arli
Tasmanian School of Business & Economics (TSBE)
College of Business and Economics
CRICOS Provider Code: 00586B

Unit Coordinator
Denni Arli
Email: denni.arli@utas.edu.au
What is the Unit About?
Unit Description
 

Marketing decision-making is growing in importance in the business world. More than ever before, organisations are placing greater emphasis on the marketers' ability to evaluate, anticipate, and illustrate the contribution of marketing to organisational performance. Increasingly, senior managers are requiring greater rigour and accountability for investments in marketing activities. Within marketing, there is a realisation that practitioners need to be able to justify their strategies, tactics and the associated outcomes, using relevant metrics. Marketing analytics seeks to build a link between the marketing activity of the organisation and the outcomes that result from it. The focus of this unit is on developing, analysing, and evaluating appropriate models to measure the performance of marketing activities. It will develop students' knowledge of key strategic and technical decision-making models and metrics that form the foundation of marketing analytics. Students will gain knowledge and skills to predict the outcome of marketing plans in order to boost return on marketing investment.
Intended Learning Outcomes
As per the Assessment and Results Policy 1.3, your results will reflect your achievement against specified learning outcomes.
On completion of this unit, you will be able to:
1.
Critically examine different methods of data analysis and presentation for social networks, complex systems and relational links.
2.
Apply intermediate skills in spreadsheets and data visualisation software to identify trends and relationships among factors in industry and society.
3.
Analyse government, industry and social media data to identify relationships and trends.
4.
Critically evaluate conclusions drawn from different data and analytic tools.
5.
Create interactive models using appropriate software and effectively communicate results and findings to aid decision-makers in understanding interrelationships and trends.
Alterations as a result of student feedback
To Be Determined. 
 
 

Teaching arrangements
ATTENDANCE MODE
TEACHING TYPE
LEARNING ACTIVITY
CONTACT HOURS
FREQUENCY
On Campus
Workshop
Introductory 1-hr workshop, Week 1
1
Once only
Lecture (Online)
Pre-recorded 1-hr lecture, once a week
1
Weekly
Workshop
2-hr workshop, fortnightly, commencing in Week 2
2
1 time per fortnight
Other
5-hrs independent learning
5
Weekly
Online
Online Class
Introductory 1-hr workshop, Week 1
1
Once only
Independent Learning
Pre-recorded 1-hr lecture, once a week
1
Weekly
Online Class
1-hr workshop, weekly, commencing in Week 2
1
Weekly
Independent Learning
5-hrs independent learning
5
Weekly
Attendance / engagement expectations
If your unit is offered On campus, it is expected that you will attend all on-campus and onsite learning activities. This is to support your own learning and the development of a learning community within the unit. If you are unable to attend regularly, please discuss the situation with your course coordinator and/or our UConnect support team.

If your unit is offered Online, it is expected you will engage in all those activities as indicated in the Unit Outline, including any self-directed learning.

If you miss a learning activity for a legitimate reason (e.g., illness, carer responsibilities) teaching staff will attempt to provide alternative activities (e.g., make up readings) where it is possible.
 
The Tasmanian School of Business and Economics regularly hosts Masterclasses and Industry Engagement and Employability Events, which students are encouraged to attend. Registration and details will be available via the College of Business and Economics channel on the Uni App and/or via your Unit Coordinator.  
 
 

How will I be Assessed?
 
For more detailed assessment information please see MyLO.
Assessment schedule
ASSESSMENT TASK #
ASSESSMENT TASK NAME
DATE DUE
WEIGHT
LINKS TO INTENDED LEARNING OUTCOMES
Assessment Task 1:
Descriptive Statistics Analysis.
Week 4
35 %
LO1, LO2, LO3, LO4, LO5
Assessment Task 2:
Data Visualisation
Week 9
35 %
LO1, LO2, LO3, LO4, LO5
Assessment Task 3:
Big Data Reporting using Correlation Analysis
Week 13
30 %
LO1, LO2, LO4, LO5
 
Assessment details
    
Assessment Task 1: Descriptive Statistics Analysis.
Task Description:
The purpose of this assignment is to assess your ability to perform descriptive analysis and interpret the results. Descriptive analysis is a statistical method used to describe and summarise the characteristics of a dataset. In this assignment, you will be given a dataset and you will be required to perform descriptive analysis and report your findings.

Tasks:

• Data Collection: You will be given a dataset and you will be required to collect and record the data in a spreadsheet.
• Data Cleaning: Once you have collected the data, you will need to clean the dataset by removing any outliers or errors.
• Descriptive Analysis: After cleaning the data, you will need to perform descriptive analysis to summarise the characteristics of the dataset. You will be required to calculate measures of central tendency, measures of variability, and any other relevant statistical measures.
• Interpretation of Results: Once you have performed the descriptive analysis, you will need to interpret the results and provide a written explanation of what the results mean. This explanation should be clear and concise, and should include a discussion of any limitations or assumptions that may affect the results.
• Visualisation: You will be required to create a visualisation of the descriptive analysis results, such as a histogram or a box plot. This visualisation should clearly show the distribution of the data.

Deliverables:
Your submission for this assignment should include the following:

• A report explaining the results of the correlation analysis, including any limitations or assumptions that may affect the results.
• A visualisation of the correlation analysis results.
• Report Format:
o Page 1 – Cover Page
o Page 2 – Insight 1 (Data analysis and figures)
o Page 3 – Insight 2 (Data analysis and figures)
o Page 4 – Insight 3 (Data analysis and figures)
Page 5 – References

Task Length:
5 pages (single space, 12 fonts); 2000 words
Due Date:
Week 4
Weight:
35 %
 
CRITERION #
CRITERION
MEASURES INTENDED
LEARNING OUTCOME(S)
1
Identify the relevant types and sources of data to be gathered for different marketing decision-making situations.
LO1
2
Design models to represent different marketing decisions at strategic and tactical levels.
LO1
3
Analyse market size, conduct market segmentation, evaluate positioning strategies, and calculate relevant strategic metrics.
LO2
4
Use forecasting methods for different marketing outcomes.
LO2
5
Use software to make decisions about product and service development, pricing, distribution, and promotion tactics.
LO2
6
Interpret models and result outputs related to product and service development, pricing, distribution, and promotion tactics.
LO2
7
Design strategies based on the evaluation of the calculated marketing metrics.
LO3
8
Evaluate the legal, ethical, and cultural issues associated with the recommended marketing strategies.
LO3
9
Communicate decisions on strategies, both in oral and written formats for diverse audiences.
LO4
10
Identify and evaluate different types of data, including structured and unstructured data, and apply appropriate data analysis techniques to draw valid conclusions.
LO4
11
Identify appropriate data visualisation techniques for different types of data and tasks.
LO5
12
Develop a critical understanding of how data visualisations can be used to influence decisions and shape public opinion.
LO5
13
Dashboard- Comparisons
LO5
 
 

Assessment Task 2: Data Visualisation
Task Description:
Introduction:

The purpose of this assignment is to assess your ability to create effective data visualisations using Tableau. In this assignment, you will be given a dataset and you will be required to create visualisations that effectively communicate the insights and trends in the data.

Tasks:

• Data Collection: You will be given a dataset and you will be required to collect and record the data in a spreadsheet.
• Data Cleaning: Once you have collected the data, you will need to clean the dataset by removing any outliers or errors.
• Data Visualisation: After cleaning the data, you will need to create visualisations using Tableau that effectively communicate the insights and trends in the data. You should create at least three different types of visualisations, such as bar charts, line charts, scatter plots, or heat maps.
• Interpretation of Results: Once you have created the visualisations, you will need to interpret the results and provide a written explanation of what the results mean. This explanation should be clear and concise, and should include a discussion of any limitations or assumptions that may affect the results.
• Dashboard Creation: You will be required to create a dashboard in Tableau that brings together the different visualisations you have created. The dashboard should be well-organised and should effectively communicate the insights and trends in the data.

Deliverables:
Your submission for this assignment should include the following:

• At least three different types of visualisations created using Tableau.
• A report explaining the insights and trends in the data, including any limitations or assumptions that may affect the results.
• A well-organised dashboard that effectively communicates the insights and trends in the data.

Task Length:
5 pages (single space, 12 fonts); 2000 words
Due Date:
Week 9
Weight:
35 %
 
CRITERION #
CRITERION
MEASURES INTENDED
LEARNING OUTCOME(S)
1
Identify the relevant types and sources of data to be gathered for different marketing decision-making situations.
LO1
2
Design models to represent different marketing decisions at strategic and tactical levels.
LO1
3
Analyse market size, conduct market segmentation, evaluate positioning strategies, and calculate relevant strategic metrics.
LO2
4
Use forecasting methods for different marketing outcomes.
LO2
5
Use software to make decisions about product and service development, pricing, distribution, and promotion tactics.
LO2
6
Interpret models and result outputs related to product and service development, pricing, distribution, and promotion tactics.
LO2
7
Design strategies based on the evaluation of the calculated marketing metrics.
LO3
8
Evaluate the legal, ethical, and cultural issues associated with the recommended marketing strategies.
LO3
9
Communicate decisions on strategies, both in oral and written formats for diverse audiences.
LO4
10
Identify and evaluate different types of data, including structured and unstructured data, and apply appropriate data analysis techniques to draw valid conclusions.
LO4
11
Identify appropriate data visualisation techniques for different types of data and tasks.A
LO5
12
Develop a critical understanding of how data visualisations can be used to influence decisions and shape public opinion
LO5
13
Dashboard- Comparisons
LO5
 
Assessment Task 3: Big Data Reporting using Correlation Analysis
Task Description:
Introduction:
The purpose of this assignment is to assess your ability to perform correlation analysis and interpret the results. Correlation analysis is a statistical method used to determine the strength and direction of the relationship between two variables. In this assignment, you will be given a dataset with two variables and you will be required to perform correlation analysis and report your findings.

Tasks:

Data Collection: You will be given a dataset containing two variables, and you will be required to collect and record the data in a spreadsheet.

Data Cleaning: Once you have collected the data, you will need to clean the dataset by removing any outliers or errors.

Correlation Analysis: After cleaning the data, you will need to perform a correlation analysis to determine the strength and direction of the relationship between the two variables.

Interpretation of Results: Once you have performed the correlation analysis, you will need to interpret the results and provide a written explanation of what the results mean. This explanation should be clear and concise, and should include a discussion of any limitations or assumptions that may affect the results.

Visualisation: You will be required to create a visualisation of the correlation analysis results, such as a scatter plot or a correlation matrix. This visualisation should clearly show the relationship between the two variables.

Deliverables:
Your submission for this assignment should include the following:

• A report explaining the results of the correlation analysis, including any limitations or assumptions that may affect the results.
• A visualisation of the correlation analysis results.
• Report Format:
o Page 1 – Cover Page
o Page 2 – Insight 1 (Data analysis and figures)
o Page 3 – Insight 2 (Data analysis and figures)
o Page 4 – Insight 3 (Data analysis and figures)
o Page 5 – References

Task Length:
5 pages (single space, 12 font); 2000 words
Due Date:
Week 13
Weight:
30 %
 
CRITERION #
CRITERION
MEASURES INTENDED
LEARNING OUTCOME(S)
1
Identify the relevant types and sources of data to be gathered for different marketing decision-making situations.
LO1
2
Design models to represent different marketing decisions at strategic and tactical levels.
LO1
3
Analyse market size, conduct market segmentation, evaluate positioning strategies, and calculate relevant strategic metrics.
LO2
4
Use forecasting methods for different marketing outcomes.
LO2
5
Use software to make decisions about product and service development, pricing, distribution, and promotion tactics.
LO2
6
Interpret models and result outputs related to product and service development, pricing, distribution, and promotion tactics.
LO2
7
Design strategies based on the evaluation of the calculated marketing metrics.
LO2
8
Evaluate the legal, ethical, and cultural issues associated with the recommended marketing strategies.
LO2
9
Communicate decisions on strategies, both in oral and written formats for diverse audiences.
LO4
10
Identify and evaluate different types of data, including structured and unstructured data, and apply appropriate data analysis techniques to draw valid conclusions.
LO4
11
Identify appropriate data visualisation techniques for different types of data and tasks.
LO5
12
Develop a critical understanding of how data visualisations can be used to influence decisions and shape public opinion.
LO5
13
Dashboard- Comparisons
LO5
 

 
 
 

How your final result is determined
To pass this unit, you need to demonstrate your attainment of each of the Intended Learning Outcomes, achieve a final unit grade of 50% or greater, and pass any hurdle tasks.
 
Submission of assignments
Where practicable, assignments should be submitted to an assignment submission folder in MYLO. You must submit assignments by the due date or receive a penalty (unless an extension of time has been approved by the Unit Coordinator). Students submitting any assignment in hard copy, or because of a practicum finalisation, must attach a student cover sheet and signed declaration for the submission to be accepted for marking.
 
Requests for extensions
If you are unable to submit an assessment task by the due date, you should apply for an extension.
 
A request for an extension should first be discussed with your Unit Coordinator or teaching support team where possible. A request for an extension must be submitted by the assessment due date, except where you can provide evidence it was not possible to do so. Typically, an application for an extension will be supported by documentary evidence: however, where it is not possible for you to provide evidence please contact your Unit Coordinator.
 
The Unit Coordinator must notify you of the outcome of an extension request within 3 working days of receiving the request.
Late penalties
Assignments submitted after the deadline will receive a late penalty of 5% of the original available mark for each calendar day (or part day) that the assignment is late. Late submissions will not be accepted more than 10 calendar days after the due date, or after assignments have been returned to other students on a scheduled date, whichever occurs first. Further information on Late Penalties can be found on the Assessments and Results Procedure.
 
Review of results and appeals
You are entitled to ask for a review of the marking and grading of your assessment task if there is an irregularity in the marking standards or an error in the process for determining the outcome of an assessment. Details on how to request a review of a mark for an assignment are outlined in the Review and Appeal of Academic Decisions Procedure.