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QBUS3600 Individual Assignment 1 – UNICEF

Due dates: Friday 11:59pm 12th of September

Value:

30%

Notes to Students

1. The assignment MUST be submitted electronically to Turnitin through QBUS3600

Canvas site. Please do NOT submit a zipped file.

2. The assignment is due at 11:59pm on Friday the 12th of September The late penalty

for the assignment is 5% of the assigned mark per day, starting one minute after the

due date. The closing date Friday September 26th is the last date on which an

assessment will be accepted for marking.

3. Your answers shall be provided as a word-processed report (Microsoft Word, LaTeX or

equivalent) giving full explanation and interpretation of any results you obtain. Output

without explanation will receive zero marks.

4. Be warned that plagiarism between individuals is always obvious to the markers of the

assignment and can be easily detected by Turnitin.

5. The dataset for this assignment can be downloaded from Canvas. The dataset is highly

confidential, and you have responsibility to keep it secure and for it to be used only for

your QBUS3600 coursework.

6. Presentation of the assignment is part of the assignment. Marks are assigned for clarity

of writing and presentation.

7. You should submit your Python code or Jupyter notebook to the separate submission

page available on Canvas. Marks will be deducted if the code fails to execute properly.

8. You may insert small sections of your code into the report for better interpretation

when necessary. However, you must consider the audience of your report.

9. Think about the best and most structured way to present your work, summarise the

procedures implemented, support your results/findings and prove the originality of

your work.

10. Numbers with decimals should be reported to the second decimal point.

2025S1 QBUS3600 Assignment 1 - UNICEF – Classification

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Background

UNICEF Australia is a leading children's charity dedicated to protecting and improving the lives

of vulnerable children in over 190 countries. They work to amplify children's voices, defend

their rights, and help them reach their full potential. Our efforts span from emergency relief

to long-term development solutions and advocacy, ensuring every child has the opportunity

to thrive

Problem Description

Overall Semester Task Description

We are seeking your expertise in data science to assist with the following one of the following

two innovative projects aimed at enhancing our fundraising efforts:

1. Life Time Value Prediction (LTV)

o Objective: Develop a predictive model to forecast the value of a donor in the

24 months following the donors initial three months of activity. To be specific:

you will look at all donations made by a donor after (and including) their first

donation for a 90 day period and then predict the sum of donations that donor

will make in the next 24 months after that period.

o Target Variable: Next_24_Month_Value_LTV

2. Propensity Model for Single Giver to Regular Giver conversion (RG)

o Objective: Develop a predictive model to forecast the likelihood of individuals

converting from a single gift to becoming a regular donor within the 6 month

period after their initial donation. This means that the donor must

“purchase/subscribe” to a product with “RG” in the product name.

o Target Variable: ConvertedTo_RG_Within_6M

Approach: Utilize existing CRM data and augment it with third-party MOSAIC data (and

optionally third-party open-source data) to improve the accuracy of predictions. Techniques

such as (but not limited to) multiple regression, cluster analysis, multi-stage modelling, and

time series models can be employed to identify patterns and trends in donor behaviour.

Impact of Success

• Enhanced Fundraising Efficiency: Accurate donation forecasting will lead to more effective

fundraising campaigns, increasing overall donations.

• Improved Donor Engagement: Personalised and timely donation requests will enhance the

donor experience, fostering stronger relationships and higher retention rates.

• Data-Driven Decision Making: Leveraging advanced data science techniques will enable

UNICEF Australia to make informed decisions, ensuring resources are allocated efficiently

to support our mission.

2025S1 QBUS3600 Assignment 1 - UNICEF – Classification

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Note that in Assignment One, you are not required to build a model. The aim of this

assignment is to perform an EDA. Details are below.

Task 1 – Preliminary Investigation (80 marks)

You will be provided with a dataset encompassing donation data of UNICEF donors. This

dataset will include information on individual transactions, product details, and descriptive

features of the donors, such as their previous donations, and other relevant attributes. In

addition to this dataset, you must explore the MOSIAC dataset least dataset to enrich your

analysis and feature engineering. If may optionally include further datasets, such as from the

Australian Bureau of Statistics (for example).

The datasets will become available after you have returned your signed Deed Poll to the course

coordinator.

As a business analyst, you will do a preliminary Exploratory Data Analysis (EDA) of the dataset.

Identify meaningful trends and insights from the data that UNICEFs donation and marketing

strategies. Uncover patterns in donors’ behaviour to unlock potential growth opportunities.

You are expected to find or reveal all possible properties, characteristics, patterns, and

statistics hidden in the datasets. The results from your EDA may be used for the final goal of

maximising revenue for UNICEF.

Write a report, limited to 15 pages (including everything except for appendices), to describe,

explain, and justify your findings to the UNICEF team. Make sure your report is concise and

objective.

List key resources as references in the end of your report, such as journal articles, conference

papers, reports, news and software etc. Use APA style for your references.

Please align your EDA with one of the two projects in mind: Life Time Value Prediction (LTV)

or Propensity Model for Single Giver to Regular Giver Conversion (RG). Your chosen project

must remain the same for the Group Assignment.

Task 2 – Executive Briefing (20 marks)

You have been asked to summarise your findings so that they can be shared with the wider

business and in particular, management. This one-page briefing should concisely describe

your findings to a non-technical audience and primarily address the business problem. In the

briefing you should also outline your suggestions for acting on your findings.

You are limited to a maximum of 1 page (included in the overall 15 pages).

2025S1 QBUS3600 Assignment 1 - UNICEF – Classification

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Marking and Key Rules

Your reports will be marked against the following principles:

• Demonstrate a clear understanding of the problem

• Demonstrate consideration for the audience

• Clear outline and demonstration of investigation process

• Use of relevant statistical tests

• Clear explanation of outputs. Proper justification of used methods.

• The overall analysis is sound and logical

• Clearly draw conclusions based on analysis

• Statements are clear, concise and accurate, with correct spelling, free of grammar

errors and correct use of punctuation

• Use of visual presentation is appropriate

• The report is well structured, and sentences are well connected

• Closely follow a referencing style specified in Business School Referencing Guide (e.g.

APA) with consistency

• Clear, concise and commented Python code, if any.

A formal marking rubric is uploaded to canvas.

Datasets and Additional information

You have been provided a dataset in CSV format.

Review the provided data dictionary to understand each variable. This will aid in your

exploratory data analysis and feature selection, aligning with the first project objective.

UNICEF Australia has made an effort to ensure the data is relatively clean, however, we

encourage you to perform checks and conduct the necessary data processing and feature

engineering as required.

This project presents a unique opportunity to apply your data analytics skills to a real -world

business challenge and contribute to the ongoing success of UNICEF Australia. We are

confident that your work will provide valuable insights and drive impactful results for UNICEF.

Your contributions to these projects will play a crucial role in helping UNICEF Australia

continue to make a positive impact on the lives of children both locally and globally.

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