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MIS784 – Marketing Analytics – Trimester 3 2024 

Assessment Task 1 – Transaction Analysis – Individual  

DUE DATE: Friday, 6 December 2024, by 8:00pm (Melbourne time) 

PERCENTAGE OF FINAL GRADE: 30% 

Submission: You will submit to unit site: 

– one Word file, with your analysis queries, and 

– one Word file, with your written report (1000 words,  +/- 10%) 

Description 

The assignment requires that you analyze a data set, interpret, and draw conclusions from your analysis,  and then convey your conclusions in a written report. The assignment must be completed individually and must be submitted electronically in Cloud Deakin by the due date. When submitting electronically,  you must check that you have submitted the work correctly by following the instructions provided in  Cloud Deakin. Hard copies or assignments submitted via email will NOT be accepted. 

The assignment uses a data set which can be downloaded from Cloud Deakin. The assignment focuses  on materials presented up to and including Week 4. Following is an introduction to this scenario and  detailed guidelines. 

Context/Scenario:  

This trimester, although we have real data, the client organization cannot be identified for privacy  reasons. In this unit, we will refer to the client organization as “Market Co.” Market Co is a globally  recognized omnichannel retailer, renowned for its ability to sell products from worldwide to worldwide.  Leveraging advanced technology, Market Co ensures seamless operations and exceptional customer  experiences across multiple sales channels. 

Market Co’s primary goal is to deliver high-quality, personalized shopping experiences, catering to a  diverse global audience while generating revenue through various streams. The organization excels in  providing a seamless, engaging, and timely shopping journey, whether customers are purchasing  online, in-store, or through other integrated channels. 

With a vast product portfolio spanning electronics, fashion, home goods, and groceries, Market Co is  adept at meeting the varied needs of its international customer base. The company’s robust infrastructure enables it to trigger and manage multiple channels efficiently, ensuring a consistent and  comprehensive shopping experience. Beyond its primary retail offerings, Market Co also facilitates  sales for other organizations, earning commissions that are recorded in contract tables, thereby  diversifying its revenue streams. 

To maintain its competitive edge and enhance customer engagement, Market Co has hired you as a  marketing data analyst. Your mission is to derive insights into customer behaviors, optimize  subscription management, and boost online sales across its omni channel platform. The dataset includes  historical shopping behaviors from 2020 to 2024, reflecting purchases made across Market Co’s  diverse channels. 

Please answer the following questions raised by your shareholders and provide an analytical report to  assist them in understanding your analysis and providing suggestions. The questions are accompanied  by guidelines highlighted in blue. You are required to submit your analysis file, along with a report  that explains the outcomes of your analysis and two recommendations. Given that your audience may  not have training in marketing analytics, your report must present the results in plain, straightforward  language. A template has been provided for your use. 

1. Identify the best-selling product, the product with the highest return rate, and the  product with the most applied discounts. To calculate the best-selling product, we can sum  the Quantity for each Stock Code (product) and then find the product with the highest total  quantity sold. 

2. For each sales channel, how many unique customers have made at least one purchase? For each sales channel, list the total number of distinct customers who have made a purchase,  and order the results by the number of customers in descending order. Use the UserID to count  unique customers. 

3. For each customer, calculate and list their RFM Value scores based on their transaction  history. Display the customer ID along with their Recency Score, Frequency Score, and  Monetary Score. Use the User ID as the identifier for each customer. RFM stands for Recency,  Frequency, and Monetary value. 

Recency: How recently a customer made a purchase. 

Frequency: How often a customer makes a purchase. 

Monetary Value: How much money a customer spends.

4. Segment customers into five groups for each of the three key metrics: Recency,  Frequency, and Monetary value based on their transaction history. Combine these  rankings into a single RFM code for each customer. Display each customer’s ID, Recency,  Frequency, and Monetary scores. Combine the individual quintiles for Recency, Frequency,  and Monetary value into a single RFM code. Sort the results so that customers with higher  combined RFM codes (indicating better performance) appear first. 

5. Write an analytical report for Market Co that will assist them in making better business  decisions. 

o Summarize your findings from the above analyses. 

o Provide insights into the shopping habits of the customers. 

o Identify patterns and opportunities for increasing Market Co’s sales and improving  customer engagement. 

o Suggest actionable recommendations based on your analysis. 

Your report should help Market Co understand customer behavior, manage their offerings effectively,  and implement strategies to boost engagement and sales. 

Data description 

The provided data includes various types of information crucial for analyzing customer behavior and  sales performance. 

The data file includes information about the customers, such as their personal details and transaction history with Market Co. The data file also contains information about the amount, the products, and the  timing of each transaction. The variable User ID is linking customer and contract information. Please  carefully select the relevant variables for analysis, as it is not necessary to utilize all variables in  Assignment 1. 

Variables: 

• Invoice No: Unique identifier for each transaction (invoice). 

• Stock Code: The code representing the product stock-keeping unit (SKU). • Description: A brief description of the product. 

• Quantity: The number of units of the product sold in the transaction. 

• Invoice Date: The date and time when the sale was recorded.

• Unit Price: The price per unit of the product in the transaction currency. 

• Discount: The discount applied to the transaction, if any. 

• Payment Method: The method of payment used for the transaction (e.g., PayPal, Bank  Transfer). 

• Shipping Cost: The cost of shipping for the transaction. 

• Sales Channel: The channel through which the sale was made (e.g., Online, In-store). • Return Status: Indicates whether the item was returned or not. 

• Shipment Provider: The provider responsible for delivering the order (e.g., UPS, FedEx). • Warehouse Location: The warehouse location from which the order was fulfilled. • Order Priority: The priority level of the order (e.g., High, Medium, Low). • User ID: A unique identifier for each customer. 

• Age: The age of each customer. 

• Gender: The gender of each customer. 

• User Country: The customer’s country. 

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

Assignment instructions 

The assignment consists of two parts.  

Part 1: Data Analysis 

Your data analysis must be performed on the provided data files and conducted on Google Cloud  Platform with BigQuery as we have introduced in the tutorials. Big Query queries and output  screenshots should be provided.  

When conducting the analysis, you need to apply techniques from marketing analytics, including RFM  analysis and sales data examination. The analysis section you submit should be clearly labeled and  grouped around each question. Poorly presented, unorganized analysis or excessive output will be  penalized. 

Part 2: Report 

Having analyzed the data, you are required to provide a formal analytical 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, such as  RFM, Segmentation, Basket Analysis, etc. 

In Section 1 of the report, provide a brief interpretation of your findings from the data analysis. Apply the Integrated Engagement and Sales Approach which is a  newly developed method for integrating customer engagement metrics with sales performance indicators. 

In Section 2 of the report, provide TWO (2) recommendations that could help Market Co enhance  customer engagement and boost sales. Your recommendations should be based on the analysis  conducted in this assignment and any additional relevant analysis that enhances the impact of your  recommendations. 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 take into account a broad  range of data-supported considerations. Ap

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 1,000 words (900 to 1,100 words) for your report. Remember you  should use font size 11 and leave margins of 2.54 cm. 

A template is provided for your convenience. Carefully consider the following points: • Your report is to be written as a stand-alone document.  

• Keep the English simple and the explanations clear. Avoid the use of technical statistical  jargon. Your task is to convert your analysis into plain, simple, easy to understand language. 

• Follow the format of the template when writing your report. Delete the report template  instructions (in purple) when drafting your report.  

• Do not include any charts, graphs, or tables into your Report. 

• Include a succinct introduction at the start of your report, and a conclusion that clearly  summarize your findings. 

• Marks will be deducted for the inclusion of irrelevant material, poor presentation, poor  organization, poor formatting, and reports that exceed 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  familiarize 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 Cloud Deakin site on or  before the due date. 

Your submission will comprise of two files: 

1. A Microsoft Word document containing your analysis queries and results in screenshots, and 

2. A Microsoft Word document containing your analytical report with a detailed explanation of  your results.  

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

Word file 1: MIS784_A1_YOURStudentID_Query.doc (or .dox), and 

Word file 2: MIS784_A1_YOURStudentID_Report.doc (or .dox). 

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 Cloud Deakin 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. 

Marking and feedback 

The marking rubric indicates the assessment criteria for this task. It is available in the Cloud Deakin  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 familiarize yourself with the assessment criteria before  completing and submitting this task. 

Students who submit their work by the due date will receive their marks and feedback on Cloud Deakin  15 working days after the submission date. 

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 Cloud Deakin 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 submitted via Student Connect in your Deakin Sync 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 Monday at 8:00pm is as follows:  

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