Unit Outline

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.	Analyse big data using a range of statistical techniques.
2.	Create effective data visualisations to identify meaningful relationships.
3.	Communicate actionable marketing insights derived from data analysis

Alterations as a result of student feedback

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, LO3
Assessment Task 2:	Data Visualisation	Week 8	35 %	LO2, LO3
Assessment Task 3:	Big Data Reporting using T-test, Correlation and Regression Analysis	Week 12	30 %	LO1, LO2, LO3

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.

Task Length:

5 pages (single space, 12 fonts).

Due Date:

Week 4

Weight:

35 %

CRITERION #

CRITERION

MEASURES INTENDED

LEARNING OUTCOME(S)


1	Evaluate different types of data, including structured and unstructured data.	LO1
2	Apply appropriate data analysis techniques to draw valid conclusions.	LO1
3	Propose relevant marketing strategies based on data analysis.	LO1
4	Communicate data outputs related to product and service development, pricing, distribution, and promotional tactics.	LO3

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).

Due Date:

Week 8

Weight:

35 %

CRITERION #

CRITERION

MEASURES INTENDED

LEARNING OUTCOME(S)


1	Design marketing strategies based on insights from data visualisations.	LO2
2	Select appropriate data visualisation techniques to convey insights across different data types.	LO2
3	Explain how data visualisations can be used to influence decisions and shape public opinion.	LO3

Assessment Task 3: Big Data Reporting using T-test, Correlation and Regression Analysis

Task Description:

Introduction:
The purpose of this assignment is to assess your ability to perform t-test, correlation analysis, regression analysis and interpret the results.

In this assignment, you will be given a dataset with multiple variables and you will be required to perform statistical 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.

T-Test: It is used to determine whether there is a statistically significant difference between the means of two groups.

Correlation: it measures the strength and direction of the linear relationship between two continuous variables.

Regression: It explores the relationship between a dependent variable and one or more independent variables to predict outcomes.

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.

Task Length:

5 pages (single space, 12 font); 2000 words

Due Date:

Week 12

Weight:

30 %

CRITERION #

CRITERION

MEASURES INTENDED

LEARNING OUTCOME(S)


1	Evaluate different types of data, including structured and unstructured data.	LO1
2	Apply data analysis techniques to draw valid conclusions.	LO1
3	Create data visualisations that illustrate the data to produce meaningful insights.	LO2
4	Communicate strategic decision clearly through written formats.	LO3

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.

Academic integrity

Academic integrity is about acting responsibly, honestly, ethically, and collegially when using, producing, and communicating information with other students and staff members.

In written work, you must correctly reference the work of others to maintain academic integrity. To find out the referencing style for this unit, see the assessment information in the MyLO site, or contact your teaching staff. For more detail about Academic Integrity, see Important Guidelines & Support.

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.