COMM 1190 University of Sydney The Mobile Hub Sales and App Analysis Visual Report

COMM1190 Assessment 1: Individual Report
Week 4: 3:00 pm Friday (AEDT)
20%
A visual and written report
Maximum word count of 750, excluding references, figures, tables.
Via Turnitin on Moodle course site
Objective
In this short individual assignment, you will play the role of a junior consultant for the
firm Insight Bridge Consulting. You have been tasked by your manager to work on a
data analysis project for an e-commerce website called The Mobile Hub. The Mobile
Hub is a technology retailer that sells a range of consumer electronic products,
including smartphones, tablets and accessories. The site has recently launched a new
mobile app, but downloads and sales have been lower than expected. The site’s
managers are looking to better understand user behaviour to optimise the app and
improve sales. They have hired Insight Bridge Consulting to help them analyse a
dataset of user behaviour and spending patterns.
As a junior consultant on the project, your task is to use R to explore the dataset and
create visualisations that help The Mobile Hub app’s managers understand how users
behave and engage with the app. Using R, you will explore a dataset and create
exploratory visualisations to identify trends and patterns that could inform the website’s
marketing and sales strategies. You will present your findings in a one-page visual
report that clearly and concisely communicates the results of your analysis. The visual
report should incorporate three high-quality declarative graphics that effectively
communicate your findings and insights to managers of The Mobile Hub. These
graphics should highlight three separate findings from the analysis and be good charts.
The one-page visual report has a word limit of 250 words.
In addition to submitting your one-page visual report, you will also provide a two part
appendix. Appendix A outlines the end-to-end process of your data analysis. Appendix
A, which has a 500 word limit, should detail your approach to the problem, including
the methods used to select and clean the data, any data exploration or visualisation
techniques used, and how you arrived at your final conclusions. You should also
include any graphs, tables, or summary statistics that helped guide your analysis. The
technical appendix should be written clearly and concisely so that another analyst can
understand your approach to the problem and replicate your findings. Appendix B is a
printout or screenshots of your data exploration and R-code that can re-create the
exploratory data visualisations associated with the graphs presented in the one-page
report. Overall, the assessment is designed to help you develop your R and data
communication skills. Appendix B does not have a word count.
What is a visual report?
A visual report is a traditional form of reporting that includes visual aids such as charts,
graphs, and tables to present data and information. A visual report typically follows a
linear narrative and presents information in a structured and sequential way. Visual
reports may be used in academic, scientific, or professional contexts where data
analysis and presentation are critical. The report should introduce the topic and
provide a brief conclusion. Overall, a one-page visual report can be a great way to
present key information in a concise and engaging way.
Note that visual reports are similar to but distinct from typical infographics. Infographics
are a more creative and engaging way of presenting information, and in addition to
charts and graphs, they often include other visual elements, such as icons and images,
employing a more artistic or playful design aesthetic. Typically, the goal of infographics
is to capture the audience’s attention. As a result, infographics focus on
communicating information in a memorable and visually appealing way rather than
presenting data in a structured linear fashion.
Elements to Include in a One-Page Visual Report:
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Title: Start with a clear and concise title that accurately reflects the content of
the report.
Introduction: Provide a brief overview of the topic, including the purpose and
context of the report.
Key Findings: Use charts, graphs, or other visual elements to highlight the
most important findings from the research.
Conclusion: Summarize the main takeaways from the report, including any
recommendations or next steps. If applicable, include a call to action or a way
for readers to get involved with the topic.
Sources: If the report draws on specific sources or data, include a brief citation
or link to the original sources.
Guidance on Data Analysis:
Note: the dataset and the data dictionary will be provided to you separately.
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It is important to emphasize that there is no single correct answer to the
assignment. The data set involves many different dimensions for you to explore,
and some aspects and dimensions of the data are likely to be more useful than
others. Therefore, it is important that you systematically explore the different
variables in the dataset before starting your assignment.
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Although you may create many graphs for your assessment (e.g., histograms to
better understand the data), you only want to include figures that support your
main findings in the one-page visual report.
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Also, look for potential outliers in the dataset. What can you infer from these
outliers? Should the outliers be included in the analysis of the data? Any decisions
made about including or excluding outliers should be justified in the report’s
Appendix.
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Remember that your conclusions should be well supported by your data
exploration and visualisations. You should also outline any key assumptions in
your data-driven conclusions and acknowledge any limitations.
Tips for Designing Your One-Page Visual Report:
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When designing a one-page visual report, it’s important to balance brevity with
clarity.
Use a clear and legible font, and ensure the visual elements are easy to
understand and reinforce the report’s key points.
You may also want to consider using colour or other design elements to help the
report stand out and catch the reader’s attention.
Tips for the Technical Appendix:
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Explain your methodology: Describe the methods you used to select and clean
the data, including any pre-processing or data-wrangling techniques you used. Be
sure to explain why you made your choices and how they relate to the problem
you were trying to solve.
Detail your analysis process: Describe how you analysed the data, including any
statistical techniques you used. Explain how you arrived at your conclusions,
including any graphs, tables, or summary statistics that helped guide your
analysis.
Include visuals: Include relevant graphs, charts, or other visual aids in your
technical appendix to help illustrate your points and make your analysis more
accessible.
Be transparent about any limitations: Be transparent about any limitations of your
analysis, such as missing data or sample size limitations, and explain how you
accounted for these limitations.
Keep it concise: While it’s important to be specific and thorough, it’s also
important to be concise since you only have 500 words. To ensure that you
maximize your space, take time to edit and revise your Appendix.
Requirements:
1. Problem Analysis (50%). Identify business problems, issues, relevant questions.
Apply rigorous analysis, appropriate frameworks, tools, and standards to develop
and/or evaluate data.
2. Quality of Conclusions and Recommendations (10%). Develop well-reasoned,
appropriate conclusions or solutions.
3. Visual Communication (30%). Use appropriate visualisations to communicate
insights effectively.
4. Non-visual communication and organisation (10%). Uses language to convey
ideas and information effectively and accurately. Report should professionally
presented.
Submission Instructions
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Submit your one-page visual report, Appendix A, and Appendix B (which should
include all relevant codes) as a single document to the Turnitin assessment
submission link on Moodle. Please note that the submission link can be reached
by logging into Moodle or through Ed.
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5% of the marks available for the assessment will be deducted for this
assessment if you do not submit a fully completed and signed cover page.
5% of the marks available for the assessment will be deducted for every 50 words
the visual report is over the word limit and for every 100 words that Appendix A is
over the word limit.
Late Submission Penalties
1. Late submission will incur a penalty of 5% per day or part thereof (including
weekends) from the due date and time. An assessment will not be accepted
after 5 days (120 hours) of the original deadline unless special consideration
has been approved. An assignment is considered late if the requested format,
such as hard copy or electronic copy, has not been submitted on time or where
the ‘wrong’ assignment has been submitted.
2. No extensions will be granted except in the case of serious illness,
misadventure, or bereavement, which must be supported with documentary
evidence. Requests for extensions must be made to the Lecturer-in-charge by
email and be accompanied by the appropriate documentation no later than 24
hours before the due date of the assignment. In circumstances where this is not
possible, students must apply for Special Consideration.
3. The Course Convenor is the only person who can approve a request for an
extension. If you do make a request for an extension, the Lecturer in Charge
will email you and the course convener with the decision. Note: A request for
an extension does not guarantee that you will be granted one.
Smarthinking English Support
“… an online writing support platform officially sanctioned by UNSW. Students can
submit drafts of their writing to a Smarthinking tutor or connect to a Smarthinking
tutor in a real-time session and receive comprehensive feedback on a variety of
writing areas”. https://www.student.unsw.edu.au/smarthinking.
Smarthinking is available on the COMM1190 Moodle Site. Using the service, you
can:
• Submit your drafts to a Smarthinking tutor for comprehensive feedback on
your writing typically within 24 hours; or
• Connect to a Smarthinking tutor in a live one-on-one session about writing.
• Receive comments on a variety of writing areas including clarity of your
ideas, grammar, organisation etc.
• Use up to 2 hours on Smarthinking reviews
Marking Rubric for Individual Assessment
Criteria
Problem Analysis
(50%)
Visual
Communication
(30%)
High Distinction
(85%-100%)
Demonstrates a thorough
understanding of the
business problem or issue,
identifies relevant
questions and uses
appropriate frameworks,
tools, and standards to
develop and evaluate data.
Explicitly presents a
coherent and clear logic
between business issues,
analytical techniques, and
variable selection.
Distinction
(75%-84%)
Demonstrates a good
understanding of the
business problem or issue,
identifies relevant
questions, and applies
appropriate frameworks,
tools, and standards to
develop and evaluate data.
Explicitly presents a
coherent and clear logic
between business issues,
analytical techniques, and
variable selection.
The justification is sound
and convincing. Skillfully
explores data with
compelling explanations of
the issues identified.
The justification is
convincing. Explores data
with explanations of the
issues identified.
Uses appropriate
visualisations to effectively
communicate insights.
Three graphs are included,
each of which
communicates an important
insight.
Uses appropriate
visualisations to
communicate insight. Three
graphs are included, each
of which communicates an
important insight.
The graph designs are
well-crafted and the key
takeaways are clear and
easily understood.
The graph designs are
generally good, and the key
takeaways are mostly clear
and easily understood.
Credit
(65%-74%)
Demonstrates a
satisfactory understanding
of the business problem or
issue, identifies some
relevant questions, and
uses some appropriate
frameworks, tools, and
standards to develop and
evaluate data. Presents a
somewhat coherent and
clear logic between
business issues, analytical
techniques, and variable
selection.
Pass
(50%-64%)
Demonstrates a limited
understanding of the
business problem or issue,
does not identify relevant
questions, and does not
use appropriate
frameworks, tools, and
standards to develop and
evaluate data. Does not
present a coherent and
clear logic between
business issues, analytical
techniques, and variable
selection.
No Bueno
(0%-49%)
Does not demonstrate a
basic understanding of the
business problem or issue,
does not identify relevant
questions, and does not
use appropriate
frameworks, tools, and
standards to develop and
evaluate data. Does not
present any coherent or
clear logic between
business issues, analytical
techniques, and variable
selection.
The justification is partially
convincing. Explores data
adequately with adequate
explanations of the issues
identified.
The justification is not
convincing. Explores data
inadequately with
insufficient explanations of
the issues identified.
The justification is absent.
Does not explore data
adequately with insufficient
explanations of the issues
identified.
Uses appropriate
visualisations, but one or
more of the three graphs
do not effectively
communicate insights.
Inappropriate use of
visualisations and/or one or
more of the three graphs
do not effectively
communicate insights.
Inappropriate use of
visualisations and all three
graphs do not
communicate insights
effectively.
One or more of the three
graph designs and/or key
takeaways are not clear or
easily understood.
The graph designs and/or
key takeaways are not
clear or easily understood.
The graph designs and key
takeaways are not clear or
easily understood
Criteria
Quality of
Conclusions and
Recommendations
(10%)
Non-visual
Communication
and Organisation
(10%)
High Distinction
(85%-100%)
Develops well-reasoned,
appropriate conclusions or
solutions based on the
results of the analysis. The
results of each analytic
technique performance and
findings are correctly
interpreted and critically
examined supported by
academic references.
Results interpretation is
relevant and meaningful in
the case context.
Recommendations are
logically and consistently
tied to each issue
discussed, with critical
thinking manifest in
business recommendations.
Uses language effectively
and accurately to convey
ideas and information, with
clear and concise writing
that is well-structured and
free of errors.
Good structure with
organized headings and
coherent flow between
sections.
Distinction
(75%-84%)
Develops good conclusions
or solutions based on the
results of the analysis. The
results of each analytic
technique performance and
findings are correctly
interpreted and examined.
Credit
(65%-74%)
Develops satisfactory
conclusions or solutions
based on the results of the
analysis. The results of each
analytic technique
performance and findings
are partially interpreted
and examined.
Pass
(50%-64%)
Develops limited
conclusions or solutions
based on the results of the
analysis. The results of each
analytic technique
performance and findings
are not interpreted and
examined.
Results interpretation is
somewhat relevant and
meaningful in the case
context. Recommendations
are somewhat tied to each
issue discussed.
Results interpretation is not
relevant or meaningful in
the case context.
Recommendations are not
consistently tied to each
issue discussed.
Uses language effectively
and accurately to convey
ideas and information, with
clear writing that is wellstructured and mostly free
of errors.
Uses language somewhat
effectively and accurately
to convey ideas and
information, but the writing
may lack clarity, structure,
or contain errors.
Uses language ineffectively
or inaccurately to convey
ideas and information, with
unclear or poorlystructured writing that
contains errors.
Uses language incoherently
or inaccurately to convey
ideas and information, with
writing that is unclear,
poorly-structured, and
contains numerous errors.
Structure is generally sound
and headings are wellorganized, but flow
between sections may be
uneven or unclear.
Structure is adequate, but
headings may be less wellorganized and flow
between sections may be
inconsistent.
Structure is inadequate,
with poorly organized
headings and inconsistent
or incoherent flow between
sections.
Structure is extremely poor
or absent, with no
discernible organisation or
headings.
Results interpretation is
generally relevant and
meaningful in the case
context. Recommendations
are tied to each issue
discussed.
No Bueno
(0%-49%)
Develops no conclusions or
solutions based on the
results of the analysis. The
results of each analytic
technique performance and
findings are not interpreted
and examined.
Results interpretation is not
relevant or meaningful in
the case context.
Recommendations are not
tied to each issue
discussed.
Variables
Range of Values and Constraints
Description
1
C_ID
Alphanumeric
Unique customer identifier
2
C_TotalSpending
Range: min: 0, max: 3536
Total Spending via the e-store app.
3
C_SmartphoneSpend
Range: min: 0, max: 2000
Total Spending on smartphones via the e-store app.
4
C_TabletSpend
Range: min: 0, max: 1950
Total Spending on tablets via the e-store app.
5
C_AccessoriesSpend
Range: min: 0, max: 650
Total Spending on accessories via the e-store app.
6
C_Gender
M=Male, F=Female
Customer gender
7
C_Age
Age in years (18-60)
Customer age
8
C_State
WA, VIC, QLD, NSW, TAS, NT, QLD, SA
Location of customers in respective states/territories of Australia
9
C_Region
Urban, Rural
Urban represents city and rural represents countryside
10
C_Gender
M=Male, F=Female
Customer gender
11
C_WhenUseApp
12:00 AM – 6:00 AM
6:00 AM – 12: PM
12:00 PM – 6:00 PM
6:00 PM – 12:00 AM
Time slot of the day
12
App_DeviceType
Phone or Tablet
Customer’s type of device used for the app
13
App_OperatingSystem
IOS or Android
Operating system used for the app
14
App_PromoOffered
Yes or No
Promotional offers on the app
15
App_EmailCommunication
Daily, Weekly, and Monthly
Frequency of email Communication by customer
16
App_WasReferred
Yes or No
Referral from friends for the app
14
App_Satisfaction
H=High, M= Medium, L =Low
Customer satisfaction rating on the Apps used
15
App_Tenure
Range: min: 0, max: 30
Number of months since registration of the account.
16
App_AverageDailySessionTime
Range: min=0, max=60
Average daily time in minutes spent by the user on the application.