Customer Analytics Case Study

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Assessment 1 Information

Subject Code: DATA4700
Subject Name: Digital Marketing and Competitive Advantage
Assessment Title: Customer Analytics Case Study
Assessment Type: Individual Case Study + Statement of Intent
Word Count: 1200 Words (+/-10%)
Weighting: 20 %
Total Marks: 20
Submission: Turnitin
Due Date: 23:55pm AEST, Tuesday Week 5

Your Task
The business question you are to address is:
Which of the customers in your database will you choose to engage with to increase
revenue or reduce churn, and how will you accomplish this goal?
The dataset containing information about customers’ purchasing history can be accessed at
the following link:
https://www.kaggle.com/code/willturnerau/predicting-customer-churn-intelecommunications/data
You will analyse the data to create a market segmentation of your customer base (Topic 4)
You will need to justify the segments that you have created (Topic 1)
You will choose one segment to target, giving thought to RFM Analysis and Customer
Lifetime Value (Topic 4)
You will provide recommendations on how best to engage with the target customer segment
that you have chosen (Topics 2 and 3)
You will write a short statement of intent which addresses: (1) who your target audience is for
the report and (2) what techniques have you used to connect with that audience and improve
the readability of your report for that audience.
Assessment Description
An individual report of 1000 words (+/- 10%)
A 200-word statement of intent (see instructions above)
Analysis of a provided dataset
Based on the analysis, write a report justifying how the customer segmentation was done, which one
customer segment to target, and how to engage best with that target segment
Learning outcomes: LO1, LO2, LO4
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Assessment Instructions
Your report should have the following headings and address the topics below:
1.
Introduction: A brief overview of the dataset and the task that you are conducting
2.
Data analysis: The techniques used and insights arising from the segmentation of the
customer data
3.
Customer segmentation: Explanation of how the customer segments that you have created
differ from each other
4.
Target segment: Indication of which one customer segment to target with your marketing
activities, and a justification of why you chose that segment
5. Recommendations: What tactics you will perform to engage with the customer segment that
you have chosen to target
6.
Statement of Intent: Who is the target audience for your report and what have you done to
try and make your report more accessible for that audience.

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Important Study Information
Academic Integrity Policy
KBS values academic integrity. All students must understand the meaning and consequences
of cheating, plagiarism and other academic offences under the Academic Integrity and Conduct
Policy.
What is academic integrity and misconduct?
What are the penalties for academic misconduct?
What are the late penalties?
How can I appeal my grade?
Click here for answers to these questions:
http://www.kbs.edu.au/current-students/student-policies/.
Word Limits for Written Assessments
Submissions that exceed the word limit by more than 10% will cease to be marked from the point
at which that limit is exceeded.
Study Assistance
Students may seek study assistance from their local Academic Learning Advisor or refer to the
resources on the MyKBS Academic Success Centre page. Click
here for this information.
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Assessment Marking Guide

DATA4700
Assessment 1
Rubric /20
Has demonstrated limited
achievement:
Has achieved all or most of:
Case Study
Introduction
0-9 10-20 /20
(1) Does not summarise the most important
variables used from the dataset to conduct the
analysis
(2) Does not comment about the analytical
techniques used to generate the analysis
(3) Recommendations made are vague or
non-existent
(1) Concisely summarises the most
important variables used from the
dataset to conduct the analysis
(2) Provides a brief comment about the
analytical techniques used to generate
the analysis
(3) Clearly states the recommendation
being made
1
1
1
Data analysis
(1) Poor use of analytical techniques, or
techniques not specified, in generating
insights supporting the final recommendation
(2) Insights are irrelevant to the context of the
business problem being solved
(1) Demonstrates a strong command of
how the analytical techniques were used
on the variables from the dataset to
generate meaningful insights supporting
the final recommendation
(2) Communicates how the insights
make sense in the context of the
business problem being solved
2
1
Customer segmentation

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(1) Does not identify clearly how the various
segments are all plausible and distinct to
others within the customer base
(2) Does not justify the segments in reference
to the business context and dataset
(1) Identifies multiple, non-overlapping
customer segments that are plausible
from the customer base
(2) Supports the justification of these
segments in reference to the business
context and dataset
2
1
Target segment
(1) Ambiguous selections of customer
segment to target
(2) Poor justification of why this customer
segment was selected for targeting over other
segments under consideration
(1) Unambiguously selects only one
customer segment to target
(2) Justifies convincingly why this
customer segment was selected for
targeting over other segments under
consideration
1
2
Recommendations
(1) Does not specify whether the
recommendations are related to increasing
revenue and/or reducing customer churn
(2) Does not propose fully innovative
solutions with the chosen target segment that
reflect a direct approach to addressing the
business problem
(3) Recommendations made are too general,
irrelevant or impractical in their
implementation
(4) Does not outline appropriate metrics to
determine how success of the
recommendations will be evaluated
(1) Clearly specifies whether the
recommendations are related to
increasing revenue and/or reducing
customer churn
(2) Proposes innovative solutions to
engaging with the chosen target
segment that reflect a direct approach
to addressing the business problem
(3) Makes recommendations that can be
practically implemented
(4) Outlines appropriate metrics to
determine how success of the
recommendations will be evaluated
1
2
2
1
Statement of Intent

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(1) Does not identify who the target audience
is for this report
(2) Does not concretely describe how the
report was tailored to meet the technical level
and information needs of the report’s target
audience
(1) Identifies who the target audience is
for this report
(2) Concretely describes how the report
was tailored to meet the technical level
and information needs of the report’s
target audience
1 1

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Assignment Submission
Students must submit their individual analysis via Turnitin on Tuesday of Week 5 at 23:55pm AEST.
This file must be submitted as a Microsoft word document to avoid any technical issues that may occur from incorrect file
format upload. Uploaded files with a virus will not be considered as a legitimate submission. Turnitin will notify you if there is any
issue with the submitted file. In this case, you must contact your lecturer via email and provide a brief description of the issue
and a screen shot of the Turnitin error message.
Students are also encouraged to submit their work well in advance of the time deadline to avoid any possible delay with Turnitin
similarity report generation or any other technical difficulties.
Late assignment submission penalties
Penalties will be imposed on late assignment submissions in accordance with Kaplan Business School’s Assessment Policy.

Number of
days
Penalty
1* – 9 days 5% per day for each calendar day late deducted from the student’s total
Marks.
10 – 14 days 50% deducted from the student’s total marks.
After 14 days Assignments that are submitted more than 14 calendar days after the
due date will not be accepted and the student will receive a mark of zero
for the assignment(s).
Note Notwithstanding the above penalty rules, assignments will also be given
a mark of zero if they are submitted after assignments have been
returned to students.

*Assignments submitted at any stage within the first 24 hours after deadline will be considered to be one day late and therefore
subject to the associated penalty.
If you are unable to complete this assessment by the due date/time, please refer to the Special Consideration Application
Form, which is available at the end of the KBS Assessment Policy:
https://www.kbs.edu.au/wp-content/uploads/2016/07/KBS_FORM_Assessment-Policy_MAR2018_FA.pdf
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