EXAMINATION PAPER
Faculty of Business and Law
Trimester 1 2023 Examination
Unit Code: MMK365
Unit Name: Marketing Insights
Exam Name: Open-book Take Home Online Exam
Anticipated writing time: TWO (2) HOURS
Special instructions for Candidates:
This examination is OPEN BOOK.
This examination is open for 24 HOURS. Within this period, you can select when you complete the exam.
This examination constitutes 50% of your assessment in this unit.
This examination comprises 6 questions. You are required to answer ALL 6 questions.
Save your exam response on your computer using the file name: student ID, unit code and the unit name, for example: 216123123_MMM365_MarketingInsights.
Record all answers in the spaces provided below for each question and upload the .docx to the Exam Submission Dropbox on the CloudDeakin unit site.
Please note that only the Word file should be submitted and will be marked. Analyses output used to answer the questions should be presented in the Word file, where required.
Late submissions will not be marked.
Remember to save your work regularly.
It is important that you complete this task individually. Your submission will be reviewed for the purposes of detecting collusion and/or plagiarism.
If you encounter any technical issues with CloudDeakin, please contact the IT Service Desk online or via phone (1800 463 888; +61 5227 8888 if calling from outside Australia) and record your ticket number as evidence of technical issues during the examination period.
In the unlikely event that you cannot upload your completed exam paper, email it as an attachment to your unit chair [[email protected]] within the submission time.
The breakdown of marks in this exam is:
-
Question Marks Question Marks 1 9 5 20 2 24 6 15 3 10 4 22 Total Available Marks
100
Note that each question includes different parts.
All candidates MUST complete this section
Type your student ID number here: _________________________________
MMK365: Marketing Insights
T1 2023 EXAMINATION
Question 1: After completing MMK365, you are hired to help with data analysis work in a “Marketing Insights” firm. From the following issues you are asked to identify the ones that can be solved by conducting a regression analysis (no justification required) (9 marks)
Segment the market based on the income and age simultaneously.
Predict whether a person will take a COVID-19 vaccine.
Investigate how advertising affects firm’s sales.
What is the average income for firms’ consumers above 30 years old in Australia?
How effective is Deakin’s new advertising campaign in attracting new students?
Explore how price promotion affects firm’s profit.
Question 2. Tom, a micro-entrepreneur who runs a local grocery store at Burwood, is planning to open his second store in a nearby neighbourhood. He is considering borrowing money to fund his second store from a crowdlending platform where he has been maintaining a good credit history. Tom knows how the platform determines initiators’ (borrowers’) loan interest rates. However, he is unaware of how initiators’ (borrowers’) credit scores are calculated on this platform. He would like to seek some insights about this.
Tom provided you with the dataset (“data_question2.xlsx”) collected from the crowdlending platform. You are asked to help Tom understand the data and obtain the insights. (8+10+6= 24 marks)
What is the best central tendency statistic for credit score in this dataset?
What is the effect of one’s income on her/his credit score on this crowdlending platform? What insights can you draw? What will you recommend Tom to do based on these insights?
Estimate the following regression model using the dataset in data_question2.xlsx, and discuss the effect of borrower’s location and borrowers’ borrowing history on the credit score.
score=a + b*income+ c*new+ d*location+ error
Question 3. Aussie Farmers Direct (AFD) is an Australian online grocery retailer. The company would like to know whether changing the colour of the logo from blue to yellow helps bring more conversions in its online advertising campaigns. The two versions of the logo are presented in the following Table:
-
Old logo:
Aussie Farmers
New logo
Aussie Farmers
When AFD conducts an A/B test, it randomly assigns customers to both logos and collects the data for conversions (“data_question 3.xlsx”). (4+6 = 10 marks)
Can the above A/B test conducted by AFD help the company with understanding the effect of logo colour change (from blue to yellow) on conversions? Explain your answer. (Hint: If yes, then conduct the A/B test analysis to obtain the effect. If no, then explain why.)
Question 4. Digitalworld is a company that sells digital products and was impressed by your past work on (RFM) segmentation. Recently, Digitalworld developed a new product which could improve user online viewing experience and would like to promote the new product to the market. Digitalworld reached you again and would like to seek some insights about customer segmentation.
Digitalworld provided you the dataset with the following variables:
|
Variable |
Definition |
| customer | Customer’s ID |
| income | Customer’s annual income (in dollars) |
| age | Customer’s age (in years) |
| purchase_location | The purchasing location where a customer buys Digitalworld’s products (takes one of the following five values: specialty stores, mass-consumer electronics, discount stores, regular retail stores, and online stores) |
| spending | Customer’s annual spending on Digitalworld’s products (in dollars) |
| online_hours | The number of hours that a customer spends online per day |
| early_adopter | Whether customer is an early adopter of the digital product, 1 = early adopter and 0 = late adopter |
You compute the correlations among variables such as “income”, “age”, “spending”, and “online_hours” and get the following table:
|
Correlation Coefficient Table |
||||
|
income |
age |
spending |
online_hours |
|
|
income |
1 |
|||
|
age |
0.7698 |
1 |
||
|
spending |
0.5385 |
0.4123 |
1 |
|
|
online_hours |
-0.1732 |
-0.6245 |
-0.7874 |
1 |
You also generate a pivot table that shows customers’ annual income (affordability) and annual spending on Digitalworld’s products (profitability) based on their purchasing locations.
|
Purchasing location |
Average annual income |
Average annual spending on Digitalworld’s product |
|
specialty stores |
$69,910 |
$5,500 |
|
mass-consumer electronics stores |
$55,080 |
$4,100 |
|
discount stores |
$29,840 |
$610 |
|
regular retail stores |
$29,970 |
$590 |
|
online stores |
$30,020 |
$3,900 |
Based on the above information, please answer the following questions (5+7+10 =22 marks):
Digitalworld would like to know how consumers’ annual spending is associated with their hours spent online per day. Please provide this insight.
Digitalworld is considering using the variables “income” and “age” to segment the customers. Do you agree with the Digitalworld’s approach? Please explain why you agree or disagree. Digitalworld is also considering using the variables “online hours” and “spending” to segment the customers simultaneously. Do you agree with the Digitalworld’s approach? Please explain why you agree or disagree.
Digitalworld presents you three segmentation plans as follows:
-
Segment ID
Plan A
Plan B
Plan C
1
Customers who buy at specialty stores and customers who buy at online stores
Customers who buy at specialty stores and customers who buy at discount stores
Customers who buy at specialty stores
2
Customers who buy at mass-consumer electronics stores and customers who buy at discount stores
Customers who buy at mass-consumer electronics stores
Customers who buy at mass-consumer electronics stores
3
Customers who buy at regular retail stores
Customers who buy at retail stores
Customers who buy at discount stores and customers who buy at regular retail stores
4
Customers who buy at online stores
Customers who buy at online stores
Among three customer segmentation plans above, which one is the best segmentation plan for Digitalworld and Why?
Question 5. Please help solve the problems of the following scenarios for the decision maker or managers. (6+6+8 = 20 marks).
Carmen’s Kitchen would like to know how much sales of its muesli bar packs (in dollars) it would require, to generate $100,000 in profit. The muesli bar packs sell for $7.50 each. There are 5 bars in each pack. It costs Carmen’s Kitchen $0.20 to make each muesli bar. Carmen’s Kitchen has a fixed cost of $50,000.
Suppose a grocery store at CBD Melbourne sells a brand of canned soup at $10 per can. During one month, it decreased the price to $9 per can and observed an increase of demand from 1000 to 1200 cans. Please help the store figure out what is the price elasticity for this brand of canned soup. What insights can you draw based on this price elasticity and share with the grocery store manager?
Calculate the Net Promoter Score based on the sample data in the following table:
| ID | On a scale from 0 to 10 how likely are you to recommend company X to a friend or colleague? |
| 1 |
10 |
| 2 |
1 |
| 3 |
0 |
| 4 |
5 |
| 5 |
9 |
| 6 |
7 |
| 7 |
2 |
| 8 |
1 |
| 9 |
7 |
| 10 |
9 |
| 11 |
6 |
| 12 |
4 |
| 13 |
7 |
| 14 |
7 |
| 15 |
9 |
| 16 |
7 |
| 17 |
1 |
| 18 |
2 |
| 19 |
2 |
| 20 |
8 |
Question 6 The following cumulative concentration (lift) chart presents the performance of RFM on a dataset of 100,000 customers. Based on the information given on the chart: What is the top 20% cumulative lift of the model? What does this number mean? How does the model perform compared to the random targeting (blue diagonal line)? (15 marks)
END OF EXAMINATION
london, londonstudent, alwaysopen, plagiarismfreework, melbourne, assignmenthelpmelbourne, assignmenthelpaustralia, assignmenthelpsydney, studentassignmenthelp, assignmenthelpwebsites, myassignmenthelp