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Assignment Details

• Course Code: MIS784
• Course Title: Marketing analytics
• Referencing Styles : Harvard
• Words : 2,500
• University: Deakin Business School
• Country: AU

To apply analytics models to a wide range of marketing activitiesULO2: Use computer software to analyze consumers’ data and understand the strength and limitations of each softwareULO3: Analyze and interpret the output of a range of Customer analytics models in order to improve the decision making processULO4: Demonstrate comprehensive understanding of Customer analytics models.

Context/Scenario:

This trimester, we are excited to continue to work with real-world data to analyze and provide insights for a dynamic non-profit organization. For confidentiality, we will refer to this organization as “MobileImpact.”

MobileImpact is a non-governmental organization focused on tackling pressing global challenges such as combating hunger, expanding access to education, and fostering sustainable communities. What makes MobileImpact unique is its innovative use of mobile applications and mobile gaming platforms to reach and engage a broad audience. By designing games with in-app purchase mechanisms and

embedding donation options, MobileImpact transforms entertainment into an impactful fundraising channel, complementing more traditional donation pathways such as recurring pledges and campaign- based fundraising drives.

The organization aligns its mission with several United Sustainable Development Goals (SDGs), particularly: SDG 1: No Poverty, SDG 3: Good Health and Well-being, and SDG 4: Quality Education.

The SDGs1, established in 2015 as part of the UN’s 2030 Agenda, serve as a global framework for tackling challenges such as poverty, inequality, and climate change2. By designing mobile engagement strategies that support these objectives, MobileImpact contributes to global efforts to create a more equitable, sustainable future. Students are strongly encouraged to familiarize themselves with the SDGs, as this understanding will help them align their analysis and recommendations with the organization’s broader mission.

MobileImpact’s operations are funded through a hybrid model:

1. In-app purchases and micro-donations embedded in mobile apps, allowing casual users to contribute seamlessly while engaging with the games.
2. Recurring subscriptions from long-term supporters, providing predictable monthly
3. Targeted fundraising campaigns, often tied to specific projects or emergency relief

This combination allows the organization to diversify its revenue sources while deepening relationships with both casual participants and loyal donors.

At its core, MobileImpact values building meaningful and transparent relationships with its supporters. This includes sharing stories of impact, hosting interactive digital events, and regularly updating users and donors on project outcomes. However, sustaining engagement requires overcoming challenges such as donor fatigue, attrition, and the balancing of entertainment-driven app interactions with the seriousness of philanthropic missions.

To advance these goals, MobileImpact has engaged your team as data experts to explore their dataset, create actionable insights, and apply cutting-edge marketing analytics techniques. Your tasks include (but not limited to):

• Exploring user and donor datasets to identify behavioral
• Segmenting contributors based on app engagement and donation
• Measuring donor retention and finding high-impact
• Assessing the influence of seasonal campaigns, digital platforms, and in-app features on overall fundraising performance.
• Comparing the effectiveness of digital (apps, social media) versus traditional channels in mobilizing support.

A recent internal review has highlighted the need to optimize engagement strategies across these touchpoints. Your data-driven insights will guide MobileImpact in refining its outreach efforts, strengthening donor relationships, and maximizing its contribution toward achieving the SDGs. Additionally, MobileImpact is exploring how new marketing technologies, including social media analytics, Generative AI (e.g., content personalization, conversational assistants), and virtual reality (e.g., immersive impact storytelling) can open new avenues for acquisition, engagement, and retention. In parallel, the organization is concerned about data privacy and compliance, particularly how evolving data privacy policies (e.g., the GDPR) may affect data collection, consent management, cross-border processing, and campaign measurement. Your task is to deliver evidence-based recommendations that leverage advanced marketing analytics while ensuring privacy-preserving, regulation-compliant practices.

The organization is particularly interested in:

• Identifying patterns of donor behaviour: Examine differences between traditional donors and in-app contributors. This includes analyzing donation frequencies, in-app purchase behaviors, preferred channels of engagement (e.g., apps, social media, campaigns), and long- term giving Insights will help define performance indicators for sustained engagement.
• Analysing and reducing donor churn: Detect which donors are at risk of attrition, whether from recurring donations or in-app contributions. Develop evidence-based strategies and targeted interventions (e.g., personalized retention campaigns, tailored incentives) to minimize churn and maintain supporter loyalty.
• Guiding future donation activities: Leverage historical data on both donations and in-app purchases to identify drivers of high-yield campaigns and recurring Use these insights to recommend how future activities, seasonal drives, in-app promotions, or social media campaigns, can be optimized for impact and efficiency.
• Enhancing donor engagement: Provide data-driven recommendations to improve engagement strategies, including personalized outreach, dynamic campaign messaging, and app-based incentives. Insights should also inform how MobileImpact can integrate emerging technologies (Generative AI, VR, advanced social media targeting) while balancing effectiveness with compliance under evolving data privacy regulations (e.g., GDPR).

As part of this assignment, you are encouraged to create and explore various data features: Think about which variables and features could be most useful for analysis. However, feel free to explore additional features that you believe are relevant.

Some general points:

• Membership is an ongoing monthly
• If a customer does not have any record on Tradition_Donation_Patterns table, means they may have an active membership product and no history of cancel or donation to one-off donation in the reported time. Our data only contains Jan 2024 to August 2025.
• As part of this assignment, you are encouraged to be creative in your You will need to explore the dataset, identify key trends, and develop your own analytical questions and methodologies. The aim is to think critically and strategically about how MobileImpact can leverage data to achieve its mission more effectively.

You are required to submit both your analysis file and a written report that explains the outcomes of your analysis and includes at least three strategic recommendations. Given that your audience may not have extensive training in data analytics, your report should present the results in plain, straightforward language.

Data description

MobileImpact collects data from its donors to better understand their behaviour and optimize fundraising strategies. The provided data is contained in five data files named: Customers.csv, Tradition_Donation_Patterns.csv,                                          Mobile_Game_Inapp_Purchases.csv, Marketing_Campaigns.csv and Campaign_Response.csv. These files include various types of information crucial for analysing donor behaviour and donation patterns.

Contained in the five files are three basic data types:

1. Customers: This includes information about the donors, such as their personal details, membership status, and other relevant information.
2. Donation in traditional and the new channel (mobile games): This includes information about the donations made, including the amount, the products, and the timing of each
3. Campaign Performance and Marketing Campaigns: These include information about donor engagement with marketing campaigns, such as campaign types, response rates, and engagement levels.

Customers.csv Variables:

• Customer_ID: A unique identifier assigned to each donor for tracking
• Age: The age of the donor in
• Gender: The gender of the donor, categorized as “Male,” “Female,” or “Unknown” (for missing values).
• Occupation: The profession or job role of the
• Income_Level: The income category of the donor. Categories are “High,” “Medium,” or “Low.”
• Location: The state or territory in Australia where the donor
• City: The city in that state or
• Family_Size: The number of people in the donor’s

Tradition_Donation_Patterns.csv Variables:

• Customer_ID: Unique identifier linking to the
• Donation_ID: Unique identifier for each
• DonationDate: Date the donation was
• DonationEndDate: Relevant only for the product “Membership.” If filled, it indicates that the membership was cancelled on that date; if ‘NA,’ the membership is still active.
• DonationAmount: Total amount received from the donation for that specific
• Product: Type of product or service associated with the
  • Membership: A recurring monthly donation made by the donor, supporting ongoing initiatives or causes. The amount is not fixed.
  • Membership_TopUp: An additional contribution made on top of the regular monthly membership donation, either as a one-time or periodic enhancement.
  • General Donation: A flexible, one-off donation that may include monetary contributions, items, or services provided by the donor.

• Channel_Pay: The primary method of payment used for the donation (e.g., online, bank transfer, credit card).

Mobile_Game_Inapp_Purchases.csv Variables:

• Customer_ID: Unique identifier assigned to each donor/player.
• Device: Mobile platform used (e.g., iOS, Android).
• GameGenre: Primary game genre engaged with (e.g., MOBA, Battle Royale, Action RPG, Puzzle).
• SessionCount: Total number of gaming sessions
• AverageSessionLength: Average duration of a session, measured in
• SpendingSegment: A predefined classification of players based on spending behavior (e.g., minnow, dolphin, whale). As no further detailed definition is provided, you may choose to adapt or propose your own spending segmentation.
• InAppPurchaseAmount: Total value of in-app donations (AUD).
• FirstPurchaseDaysAfterInstall: Number of days elapsed between app installation and the user’s first purchase.
• PaymentMethod: Preferred payment channel or gateway (e.g., credit card, PayPal, app store billing).
• LastPurchaseDate: Timestamp of the most recent donation in the mobile

Campaign_Reponse.csv Variables:

• Customer_ID: Unique identifier linking to the
• Campaign_ID: Unique identifier for each
• Response: Indicates if the donor responded to the
• ClickThroughRate: The percentage of times donors clicked on a campaign
• EngagementFrequency: How often the donor engaged with the campaign (e.g., number of clicks, responses).

Marketing_Campaigns.csv Variables:

• Campaign_ID: Unique identifier for each
• CampaignType: The type of campaign (e.g., email, social media, TV).
• CampaignDate: The date the campaign was
• CampaignBudget: The budget allocated for the
• TargetAudience: The predefined audience targeted by the campaign (e.g., high-value donors, returning donors).

The dataset you will be working with in this assignment is compiled from real interactions of MobileImpact, offering authentic data and insights directly relevant to the operations of a modern charity. It is specifically curated by MIS784 team at Deakin Business School to be used for educational purposes in the Marketing Analytics unit.

Specific Requirements

The assignment consists of two parts: Data Analysis and Written Business Report. You are required to submit both the business report (approx. 4000 words) and analysis part (query & results are put in the appendix). The report should be written based on your analysis.

Part 1: Data Analysis

Your data analysis must be performed on the provided five data files. When conducting the analysis, you need to apply techniques from marketing analytics, using Google Cloud Platform (e.g., BigQuery, Looker Studio). Poorly presented, unorganised analysis or excessive output will be penalised.

Part 2: Report

Having analysed the data, you are required to provide a formal business report. Given that your audience may not have training in marketing analytics, your report must present the results in plain, straightforward language. The audience will only be familiar with broad, generally understood terms (e.g., Average, Correlation, Causality). They will need you to explain more technical terms.

There is no requirement on the report format, and you can use any format that best presents your work. One of the many ways to structure the report is shown below for your information, but please note that you do not have to follow this structure.

• Executive Summary
• Understanding the Consumers
• Methodology (analysis conducted)
• Evaluating the Performance
• Strategic Recommendations
• References
• Appendix (Data Analysis and group documents to be put in another file)

Your business report and recommendations should be based on the analysis conducted in this assignment and any additional relevant analysis that enhances the impact of your recommendations and also backed up with relevant academic theories and research. Ensure that both recommendations are directly informed by your data analysis. Avoid including any commentary not supported by your data analysis. Highest marks will be awarded to students who draft distinct recommendations, and whose recommendations consider a broad range of data-supported considerations.

You must include 4 to 6 charts, graphs, or tables in your report to visually represent your data analysis and support your findings. These visual aids should be clearly labelled, easy to interpret, and directly related to the key points in your analysis. Using visual elements will enhance the clarity of your report, making it easier for your audience to understand the data-driven insights and recommendations you are presenting.

When presenting your recommendations, it is essential to back them up with relevant academic theories and research from recent articles. Using up-to-date academic sources will provide a stronger foundation for your analysis and ensure that your suggestions are informed by proven concepts from fields such as marketing, data analytics, and donor behaviour. A minimum of 5 academic sources is required, and all sources must be cited and referenced using the APA 7^th edition referencing style. Be sure to provide in-text citations for any ideas, data, or theories you reference, and include a full reference list at the end of your report (this will not count toward the 4,000-word limit).

When exploring data, we often produce more results than we eventually use in the final report, but by investigating the data from different angles, we can develop a much deeper understanding of the data. This will be valuable when drafting your written report.

You are allowed approximately 4,000 words (3,600 to 4,400 words) for your report. You must provide evidence of your team meetings in the final project report. Include the meeting minutes in the report’s Appendix (this will not count toward the 4,000-word limit).

Please consider the following points:

• Your report should be a stand-alone
• Use simple English and clear Avoid technical statistical jargon and focus on presenting your analysis in easy-to-understand language.
• Include 4 to 6 charts, graphs, or tables in your
• You must include at least 5 academic
• Marks will be deducted for including irrelevant material, poor presentation, disorganized content, poor formatting, or exceeding the word limit.

When you have completed drafting your report, it is a useful exercise to leave it for a day, and then return to it and re-read it as if you knew nothing about the analysis. Does it flow easily? Does it make sense? Can someone without prior knowledge follow your written conclusions? Often when re- reading, you become aware that you can edit the report to make it more direct and clearer.

Learning Outcomes

This task allows you to demonstrate your achievement towards the Unit Learning Outcomes (ULOs) which have been aligned to the Deakin Graduate Learning Outcomes (GLOs). Deakin GLOs describe the knowledge and capabilities graduates acquire and can demonstrate on completion of their course. This assessment task is an important tool in determining your achievement of the ULOs. If you do not demonstrate achievement of the ULOs you will not be successful in this unit. You are advised to familiarise yourself with these ULOs and GLOs as they will inform you on what you are expected to demonstrate for successful completion of this unit.

The learning outcomes that are aligned to this assessment task are:

Submission

You must submit your assignment in the Assignment Dropbox in the unit CloudDeakin site on or before the due date.

Your submission will comprise of two files:

1. A Microsoft Word document containing your analysis queries & team contribution relevant materials, and
2. A Microsoft Word document containing your report (Part 2).

When uploading your assignment, your submission files should be named:

Word file 1: MIS784_A3_GroupID_Query.doc (or .docx), and Word file 2:  MIS784_A3_GroupID_Report.doc (or .docx).

Submitting a hard copy of this assignment is not required. You must keep a backup copy of every assignment you submit until the marked assignment has been returned to you. In the unlikely event that one of your assignments is misplaced you will need to submit your backup copy.

Any work you submit may be checked by electronic or other means for the purposes of detecting collusion and/or plagiarism and for authenticating work.

When you submit an assignment through your CloudDeakin unit site, you will receive an email to your Deakin email address confirming that it has been submitted. You should check that you can see your assignment in the Submissions view of the Assignment Dropbox folder after upload and check for, and keep, the email receipt for the submission.

Use of Generative Artificial Intelligence (genAI) in this assessment

Deakin welcomes the opportunity to engage with emerging technologies in education and seeks to build your capability in the ethical and responsible use of current and emergent technology. Deakin also upholds a commitment to academic integrity and to ensuring high-quality educational outcomes that prepare you for an AI-driven future.

Using genAI as an assistant is appropriate in this assessment task.

To support your learning in this assessment task, it is recommended that you limit genAl use to assist with specific tasks such as editing your work to identify grammatical and spelling errors, getting feedback on your work to improve clarity, refining multimedia content and analysing data. You must modify any AI-generated content you use. Your final submission should be your own work and show how you have used your own critical thinking skills and what you have learnt in this unit.

It is important that you take responsibility for your final submission, including:

• Evaluating the accuracy and quality of any genAI generated
• Acknowledging how you used genAI tools in this assessment to ensure you are making informed decisions about your learning, demonstrating learning you have gained in the unit, and acting with integrity.

Please use the Acknowledgement statements to guide how you acknowledge the use of genAI in this assessment.

Marking and feedback

The marking rubric indicates the assessment criteria for this task. It is available in the CloudDeakin unit site in the Assessment folder, under Assessment Resources. Criteria act as a boundary around the task and help specify what assessors are looking for in your submission. The criteria are drawn from the ULOs and align with the GLOs. You should familiarise yourself with the assessment criteria before completing and submitting this task.

This is the final assessment task in MIS784. Students who submit their work by the due date will receive their marks and feedback on CloudDeakin after the unit results are released.

Extensions

Extensions can only be granted for exceptional and/or unavoidable circumstances outside of your control. Requests for extensions must be made by 12 noon on the submission date using the online Extension Request form under the Assessment tab on the unit CloudDeakin site. All requests for extensions should be supported by appropriate evidence (e.g., a medical certificate in the case of ill health).

Applications for extensions after 12 noon on the submission date require University level special consideration and these applications must be must be submitted via StudentConnect in your DeakinSync site.

Late submission penalties

If you submit an assessment task after the due date without an approved extension or special consideration, 5% will be deducted from the available marks for each day after the due date up to seven days*. Work submitted more than seven days after the due date will not be marked and will receive 0% for the task. The Unit Chair may refuse to accept a late submission where it is unreasonable or impracticable to assess the task after the due date. *’Day’ means calendar day for electronic submissions and working day for paper submissions.

An example of how the calculation of the late penalty based on an assignment being due on a Thursday at 8:00pm is as follows:

• 1 day late: submitted after Thursday 11:59pm and before Friday 11:59pm– 5%
• 2 days late: submitted after Friday 11:59pm and before Saturday 11:59pm – 10%
• 3 days late: submitted after Saturday 11:59pm and before Sunday 11:59pm – 15%
• 4 days late: submitted after Sunday 11:59pm and before Monday 11:59pm – 20%
• 5 days late: submitted after Monday 11:59pm and before Tuesday 11:59pm – 25%
• 6 days late: submitted after Tuesday 11:59pm and before Wednesday 11:59pm – 30%
• 7 days late: submitted after Wednesday 11:59pm and before Thursday 11:59pm – 35% The Dropbox closes the Thursday after 11:59pm AEST/AEDT time.

Support

The Division of Student Life provides a range of Study Support resources and services, available throughout the academic year, including Writing Mentor and Maths Mentor online drop ins and the SmartThinking 24 hour writing feedback service at this link. If you would prefer some more in depth and tailored support, make an appointment online with a Language and Learning Adviser.

Referencing and Academic Integrity

Deakin takes academic integrity very seriously. It is important that you (and if a group task, your group) complete your own work in every assessment task Any material used in this assignment that is not your original work must be acknowledged as such and appropriately referenced. You can find information about referencing (and avoiding breaching academic integrity) and other study support resources at the following website: http://www.deakin.edu.au/students/study-support

Your rights and responsibilities as a student

As a student you have both rights and responsibilities. Please refer to the document Your rights and responsibilities as a student in the Unit Guide & Information section in the Content area in the CloudDeakin unit site.