DMP Assessment Brief 2020/21
ASSESSMENT BRIEF
Academic year and term:
2021/22 – Semester S
Module title:
Data and Analytics for Marketers (RBP020L081S)
For further module description, see Module Brief.
1. Group presentation (30%)
2. Individual report (70%)
Type of assessment:
Assessment deadline:
Formative: Outline of individual report 1. Upload on Moodle before
2pm, 30/05/22
Summative:

Group presentation: Prepare a presentation providing 5
customer insights from the Google Analytics Demo Dataset.
To be submitted via Moodle Turnitin before 2pm, (30%).
DATE Slides uploaded by latest: 29/06/22. Presentations
in Week 10 and 11.
 Individual report (3000), involving data analysis of a given
dataset and academic examination of data analytics. (70%).
To be submitted via Moodle Turnitin before 2pm.
 DATE 11/07/22, 2pm
Instructions for assessment
Formative Assessment
In order to allow some feedback on your work before you write the report there is a formative task to
make sure you are well-informed in your preparation for the summative assessment. The formative
task involves producing an outline of your report This should be written on an A4 page and uploaded
onto Moodle. You should give an idea of the structure of your report. The purpose is to check you
understand the assessment requirements and are making progress. See moodle for a template you
could use.
You will receive feedback to use in completing the summative submission.
Summative Assessment
The summative assessment consists of two components:
(i)
A group presentation – You are required to present in the seminars in week 10 and
11.
Presentations need to be around 10-15 min with Q&A. Your group will have to be
allocated according to your seminar. Please note it is your responsibility to ensure
you are in a group. You can self-select your group and if you are not in a group you
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will need to let your seminar tutor by week 4 (or as soon as possible) who will then
be able to allocate you. PLEASE DO NOT LET YOUR SEMINAR TUTOR KNOW AT
THE LAST MINUTE. If you cannot present, this will be regarded as a non-submission.
(ii)
An individual 3000 word report looking at a data analysis and an academic
examination of data analytics (70%).
The increasingly important role of data and focus on data-driven marketing strategies has presented a
number of opportunities to gain better customer insight to digital marketers. The assessments focus
on understanding data, analytics, how data can be used to gather valuable insights and actionable
insights and data analysis techniques. You should use relevant theory, tools, models, etc. from
academic and professional sources to support your arguments where applicable as well as
demonstrate practical skills in data analysis and data visualisation.
1. Group presentation.
You are required to access the Google Analytics Demo site which shows e-commerce data from
the Google Merchandising online store. Prepare a presentation to show 5 meaningful insights and
further recommendations that would drive growth. You can decide how you want to do this e.g
Powerpoint etc. Maximum of 5 in a group.
1. Critically examine the role of Google Analytics in your presentation (what are the key
advantages and disadvantages etc).
See the marking scheme for the presentation.
You are all expected to contribute to the group presentation, if you do not marks may not
be allocated.
Format
Requirements
Additional
Information
You can decide you want to present (eg Powerpoint, Prezzi
etc.) But you need to upload the key points from your
presentation on Moodle.
The slides
should be
professionally
presented.
Consistent
formatting
throughout.
Not too much information or excessively wordy.
Any figures charts should be correctly labelled and all
information correctly referenced and sourced.
.
Data
Google Analytics
Demo Site
You should access the Google Analytics Demo Site.
You will need
a gmail
https://support.google.com/analytics/answer/6367342?hl=en
account to
access the
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You can use the data on the dashboard and/or download to
an Excel Spreadsheet and conduct any further analysis you
see as appropriate.
demo data
account.
The data in the Google Analytics demo account is from the Google
Merchandise Store, an ecommerce site that sells Google-branded
merchandise. The data in the account is typical of what you would
see for an ecommerce site, and includes the following kinds of
information:
You can
access the
demo
account with
the link:



Traffic source data Information about where website users
originate. This includes information about organic traffic,
paid search traffic, and display traffic.
Content data Information about the behaviour of users on the
site. This includes the URLs of pages that users look at, and
how they interact with page content.
Transaction data Information about the transactions that
occur on the Google Merchandise Store website.
You should look at the data and identify 5 key insights that
1. Show 5 Insights
would contribute to growth of the business. You should
and
recommendations. additionally make recommendations in light of these insights
This should be in the date range – 01/01/21 – 01/01/22.
2. Critically Examine
the role of Google
Analytics
You should be able to explain what Google Analytics is, any
advantages/disadvantages, what type of analytics/metrics
does it show etc.
Delivery and
Collaboration
You should be clear and well-paced in your delivery.
Analysis
You should explain how you derived each insight.
Practice and time yourselves. You will be asked to stop if
you exceed 15 min.
For example - Did you use data straight from the
dashboard, did you make a comparison, use filters, did you
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This is the
main focus of
the
assignment.
Explanations
should be
given and
expanded on.
So explain
what do the
numbers
show.
Only a couple
of slides are
needed for
this section
and aimed at
someone
who has not
heard of
Google
Analytics.
Be prepared,
organised
and
professional.
Practice.
Use
charts/visual
diagrams
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download into an Excel spreadsheet and conduct any
further analysis etc.
where
appropriate
2. Individual report (70%) – 3000 words. Data Analysis Report
You are required to prepare an individual report.
Part A: Data Analysis (1500 words). Download the “Shopping.xls” dataset. You are required to
provide 5 key insights from the data. You can analyse the data using any techniques you consider
to be appropriate. You should discuss the type of analysis conducted, approaches/methods
adopted and visually display the results.
Part B: Critically examine the impact of data analytics on digital marketing strategies. Part
of your discussion should include elements related to actionable insights and big data.
(1500 words)
See the marking scheme for individual report in the appendix.
Requirements
Additional
Information
Format
The format of the assignment should be in a
report format and should include a cover page,
contents page, an introduction, main body (part a
and part b), conclusion, bibliography and
appendix.
The report should be
professionally
presented. You could
include a ToC, List if
figures.
Part A: Data
Analysis
You are required to provide 5 key insights from
the dataset and visually display your results. You
can analyse the data using any techniques or
software you consider appropriate (e.g
excel/SPSS, excel chart, tableau etc). You should
discuss the methods and techniques you use.
You can use any
software (e.g excel,
SPSS, Tableau).
This section of the report should contain an essay
type response to the question. This is to show the
reader the scope and application of data analytics
in a digital marketing context. You should include
elements examining actionable insight and big
data. You are free to include any additional
aspects you feel are important in answering the
question.
This is a broad
question and you
should structure your
response in the most
appropriate manner.
(approx. 1500
words)
Part B: Data
Analytics and
Marketing
relationship.
(approx. 1500
words)
Label any
diagrams/charts
properly.
“Critically examine the impact of data analytics on
digital marketing strategies”
Academic Focus
The report should have a strong academic focus
(especially for Part B, use credible sources) and
should incorporate models and theory to support
discussions throughout.
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Aim to use higher
ranking journal
articles (3*-4*) and/or
reputable sources
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Structure and presentation
Your report should be presented using a well-structured academic style. Your writing needs to be
articulate and concise and should not exceed 3,000 words including tables and figures, but excluding
references. In-text citations and references should conform to the Harvard referencing system. All
written work should be proof-read for spelling and grammatical errors, and a contents page should be
included. Do not use various font sizes and colours. Black ink, Arial, size 11, and 1.5 paragraph
spacing is recommended. Use DIN A4 format and page margins of 2.5 cm or 1 inch.
Full reading list
Bibliography
Essential Reading

Field, A. (2017) Discovering Statistics Using IBM SPSS Statistics. 5th edn. London: Sage

Grigsby, M. (2018) Marketing Analytics: A Practical Guide to Improving Consumer Insights Using
Data Techniques. 2nd edn. London: New York: Kogan Page

Gupta, M. and George, J.F. (2016) Toward the development of a big data analytics capability.
Information & Management 53 (8), pp. 1049-1064.

Hemann, C. and Burbary, K. (2018) Digital Marketing Analytics: Making Sense of Consumer Data
in a Digital World. 2nd edn. New York: Pearson Education

Winston, W.L. (2014). Marketing Analytics: Data-driven techniques with Microsoft Excel. John
Wiley & Sons
Further Reading

Mikalef, P., Boura, M., Lekakos, G. and Krogstie, J. (2019) Big data analytics capabilities and
innovation: The mediating role of dynamic capabilities and moderating effect of the environment.
British Journal of Management 30, pp. 272-298.

Stephenson, D. (2018) Big Data Demystified: How to use big data, data science and AI to make
better business decisions and gain competitive advantage. Harlow: Pearson Education

Svilar, M., Chakraborty, A. and Kanioura, A. (2013) Big data analytics in marketing. OR/MS
Today 40 (5), pp.22-25.

Spiller, L. (2020) Direct, Digital & Data-Driven Marketing. 5th edn. London: Sage

Verhoef, P.C., Kooge, E. and Walk, N. (2016) Creating value with big data analytics: Making
smarter marketing decisions. Abingdon-on-Thames: Routledge.

Verhoef, P.C., Spring, P.N., Hoekstra, J.C. and Leeflang, P.S. (2003) The commercial use of
segmentation and predictive modeling techniques for database marketing in the Netherlands.
Decision Support Systems, 34(4), pp.471-481.

Wedel, M. and Kannan, P.K. (2016) Marketing analytics for data-rich environments. Journal of
Marketing, 80(6), pp.97-121.
Relevant Journals and Databases




British Journal of Management
Journal of Business Research
Journal of Information and Management
Journal of Marketing
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


Journal of Marketing Analytics
Journal of Marketing Science
Harvard Business Review
Useful Sites
www.smartinsights.com
https://www.kaushik.net (Occams Razor)
www.hubspot.com
www.econsultancy.com
www.clickz.com
www.kissmetrics.com
How will your work be assessed?
Your work will be assessed by a subject expert who will use either the marking criteria provided in the
section “Instructions for assessment” or the Marking rubric enclosed in the Appendix, as appropriate for
this module. When you access your marked work it is important that you reflect on the feedback so that
you can use it to improve future assignments.
Referencing and submission
You must use the Harvard System.
The Business School requires a digital version of all assignment submissions. These must be submitted
via Turnitin on the module’s Moodle site. They must be submitted as a Word file (not as a pdf) and must
not include scanned in text or text boxes. They must be submitted by 2pm on the given date. For further
general details on coursework preparation refer to the online information at StudentZone,
http://studentzone.roehampton.ac.uk/howtostudy/index.html.
Mitigating circumstances/what to do if you cannot submit a piece of work or attend your
presentation
The University Mitigating Circumstances Policy can be found on the University website: Mitigating
Circumstances Policy
Marking and feedback process
Between you handing in your work and then receiving your feedback and marks within 20 days, there
are a number of quality assurance processes that we go through to ensure that students receive marks
which reflects their work. A brief summary is provided below.

Step One – The module and marking team meet to agree standards, expectations and how
feedback will be provided.

Step Two – A subject expert will mark your work using the criteria provided in the assessment
brief.

Step Three – A moderation meeting takes place where all members of the teaching and marking
team will review the marking of others to confirm whether they agree with the mark and feedback

Step Four – Work at Levels 5 and 6 then goes to an external examiner who will review a sample
of work to confirm that the marking between different staff is consistent and fair

Step Five – Your mark and feedback is processed by the Office and made available to you.
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Additional instructions for Re-sit
The same assignment task as for the main assignment (individual report 1 and individual report 2)
period applies to the re-sit, with an additional reflective section, see further instructions below.
Re-sit deadlines will be published via Moodle. Visit the module’s Moodle site and check your
Roehampton email account on a regular basis. The school is not obliged to check whether you have
noticed re-sit deadlines.
You are required to improve and resubmit your original work as well as adding a further reflective
commentary in form of a 500 words Essay. You must resubmit your work using the specific re-sit
Turnitin link on Moodle. This additional word count can be added on top of the original word count of
this assignment, if you used the full word count.
The original marking criteria will still apply (see marking grid in Appendix) except that the 10%
weighting for Presentation will be awarded instead to your additional Reflective Essay section. That is,
a statement demonstrating how you learnt from the feedback and what you did differently the second
time.
If you did not submit work at the first opportunity, you cannot reflect on your feedback. However, in
such case, your Reflection Essay section should reflect upon how the module’s concepts are applied
in a real world context.
If you were deferred at the first assessment opportunity you do not need to include the reflective piece
as this is a first submission at a later date, not a re-sit.
The Reflective Essay is marked based on the criteria of Criticality and Evidence-based Logic of
arguments. It is an independent writing task and no supervision will be provided for conducting the
essay.
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Appendix: Marking rubric 1. Group Presentation (30%),
Presentation
Visuals (25%)
Insights and
Recommendations
(25%)
Quality of
Analysis
(25%)
Outstanding
Excellent
Very Good
Good
Satisfactory (50-
Adequate
Marginal Fail
Fail
Not done
100
(80-89)
(70-79)
(60-69)
59)
(40-49)
(30-39)
(20-29)
0
Material is
imaginatively
presented
resulting in
clarity of
message and
information to
an
exceptional
standard.
Insights given
are
outstanding
and flow
seamlessly
from the data
and analysis.
Outstanding
discussion on
Google
Analytics
showing
exceptional
levels of
insight and
understanding
Outstanding
level of data
analysis and
understanding
of data
shown. A
wide range of
advanced
techniques to
interpret the
Material is
imaginatively
presented
resulting in
clarity of
message and
information to
an excellent
standard.
Material is
imaginatively
presented
resulting in
clarity of
message and
information to
a very good
standard
Material is
imaginatively
presented
resulting in
clarity of
message and
information to
a good
standard.
Material is
presented in a
satisfactory
manner with
some structure
and visual
elements.
Material
included is
relevant to the
topic and has
been
structured.
Visual aspect of
presentation is
limited
Material
presented is
mostly
irrelevant and
lacks structure
or visual impact
Material is
nearly entirely
irrelevant
and/or is
presented in a
highly
disorganised
manner
Missing.
Wholly
incorrect or
not
attempted.
Insights given
are excellent
and flow
exceptionally
well from the
data and
analysis.
Excellent
discussion on
Google
Analytics
showing and
excellent level
of insight and
understanding
Insights given
are very good
and flow well
from the data
and analysis.
Very good
discussion on
Google
Analytics
showing a
very good
level of insight
and
understanding
Insights given
are good and
flow easily
from the data
and analysis.
Good
discussion on
Google
Analytics
showing a
good level of
insight and
understanding
Insights given
are satisfactory
and flow from
the data and
analysis.
Satisfactory
discussion on
Google
Analytics
showing
understanding.
Insights given
are adequate
and show some
relation to the
data and
analysis. Some
elements may
be missing.
Adequate
discussion on
Google
Analytics
showing basic
understanding
Insights given
are weak and
show a weak
relationship to
the data and
analysis. Some
elements are
missing. Weak
discussion and
understanding
shown on
Google
Analytics.
Insights given
are poor and
show little or
no relationship
to the data and
analysis. A
number of
elements are
missing.
Limited or no
understanding
of Google
Analytics
shown.
Missing.
Wholly
incorrect or
not
attempted.
Excellent
level of data
analysis and
understanding
of data
shown. An
excellent
range of
techniques to
interpret the
A very good
level of data
analysis and
understanding
of data
shown. A very
good range of
techniques to
interpret the
data evident.
A good level
of data
analysis and
understanding
of data shown.
A good range
of techniques
to interpret the
data evident.
A satisfactory
level of data
analysis and
understanding
of data shown.
A satisfactory
level of
techniques to
interpret the
data evident.
An adequate
level of data
analysis and
understanding
of data shown.
Basic or limited
techniques
used to
interpret the
data which may
A weak level of
data analysis
and
understanding
of data shown.
Techniques to
interpret the
data a weak
and not entirely
successful.
A poor level of
data analysis
and
understanding
of data shown.
Techniques to
interpret the
data are not
evident or
applied
Missing.
Wholly
incorrect or
not
attempted.
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Delivery of
Presentation and
collaboration
(25%)
data evident.
data evident.
Cannot be
improved on.
The team
collaborated in
their presentation
in an excellent
manner.
Excellent delivery
overall.
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unsuccessfully.
not always be
successful.
The team
collaborated in
their presentation
in a very good
manner. Very
good delivery
overall.
The team
collaborated in
their presentation
in a good manner.
Good delivery
overall.
The team
collaborated in their
presentation in a
satisfactory
manner.
Satisfactory delivery
overall.
The team
collaborated in their
presentation in an
adequate manner.
Adequate delivery
overall.
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The team
collaborated in a
manner below the
basic level required.
Inconsistent
delivery.
The team
collaborated in
their presentation
in a manner
substantively
below the basic
level needed.
Missing or
wrong.Doesn’t
meet the
basic
assessment
criteria.
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Appendix: Marking rubric 2. Individual report (3000 words)
Outstanding
Excellent
Very Good
Good
Satisfactory (50-
Adequate
Marginal Fail
Fail
Not done
100
(80-89)
(70-79)
(60-69)
59)
(40-49)
(30-39)
(20-29)
0
Part A
Data Analysis
(30%)
The level of data
analysis is
outstanding and
provides superior
insight.
The level of data
analysis is excellent
and provides
excellent insight.
The level of data
analysis is very
good and
provides very
good insight.
The level of data
analysis is good
and provides
good insight.
The level of data
analysis is
satisfactory and
provides a
reasonable level
of insight.
The level of data
analysis is
adequate and
provides limited
insight.
The level of data
analysis is poor
and provides
limited to basic
insight.
Limited or no
data analysis
provided.
Missing.
Wholly
incorrect or
not attempted.
Part A
Visual
Representation
(20%)
Data is visually
represented in an
outstanding
manner and
provides clear
and creative
information.
Data is visually
represented in an
excellent manner and
provides clear and
creative information.
Data is visually
represented in a
very good
manner and
provides clear
and creative
information.
Data is visually
represented in a
good manner
and provides
clear and creative
information.
Data is visually
represented in a
satisfactory
manner and
provides a
reasonable
amount of clear
data.
Data is visually
represented in an
adequate manner
and provides the
basic levels of
information with
limited creativity.
Data is visually
represented in a
weak manner
and provides
limited
information.
Limited or no
data
represented
visually.
Missing.
Wholly
incorrect or
not attempted.
Part B
Insight and
Understanding
An outstanding
discussion
reflecting the
highest level of
insight and
understanding.
An excellent
discussion reflecting
an excellent level of
insight and
understanding.
A very good
discussion
reflecting a very
good level of
insight and
understanding.
A good
discussion
reflecting a good
level of insight
and
understanding.
A satisfactory
discussion
reflecting a
satisfactory level
of insight and
understanding.
An adequate
discussion
reflecting an
adequate level of
insight and
understanding.
A weak
discussion
reflecting a weak
level of insight
and
understanding.
Limited or no
discussion.
Very poor
understanding
of the question.
Missing.
Wholly
incorrect or
not attempted.
The quality of
sources used is
from highly
relevant
professional and/
or academic
sources.
Integration of the
secondary
research into the
discussion is
outstanding.
The secondary
research is
conducted from
relevant professional
and/ or academic
sources. Integration
of the secondary
research into the
discussion is
excellent.
Secondary
research is
conducted across
a range of
relevant sources.
Integration of the
secondary
research into the
discussion is
generally good.
Secondary
research is
conducted across
a reasonable
range of relevant
sources.
Integration of the
secondary
research into the
discussion is
reasonable.
Some limited
evidence of an
attempt to conduct
secondary
research.
Integration of the
secondary research
into the discussion
is fairly weak.
Poor attempt to
conduct
secondary
research.
Sources are not
adequate or that
relevant to the
assignment.
Weak integration
is evident in the
discussion.
The attempt on
this part of the
assessment
does not
address the
main
assignment
requirements.
The research is
either sparse or
non-existent.
Missing.
Wholly
incorrect or
not attempted.
Clear, articulate
and concise
structure,
Excellently edited
and presented piece
of work in an
Very good
secondary
research that is
based on
relevant
professional and/
or academic
sources.
Integration of the
secondary
research into the
discussion is very
good.
A very good and
well-written piece
of work that uses
A well-presented
and structured
piece of work.
Adequate
structure and
presentation. The
Poor structure and
presentation.
Requires proof-
Very poor
structure and
presentation.
Lacks a clear
structure and
presentation.
Missing.
Wholly
incorrect or
(30%)
Part B
Quality of sources
(10%)
Quality of
presentation
(10%)
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presented and
written in a
professional
format. There are
no spelling or
grammatical
mistakes. A
perfect use of
Harvard notation.
appropriate academic
style. There are no
spelling or
grammatical
mistakes. Clearly
referenced using
Harvard notation.
a coherent
academic style.
Very well
structured. There
are hardly any
spelling or
grammatical
mistakes. Most of
the work is
clearly
referenced using
Harvard notation.
The writing style
is articulate but
there are a few
spelling or
grammatical
mistakes. Most of
the work is
clearly
referenced and
conforms to
Harvard format
but there are a
few references or
citations do not
conform to
Harvard’s
notation.
writing style is
adequate and
requires proofreading. Look
again at the
exemplars and
try to read more
journal articles to
develop a more
coherent and
integrated
academic style.
Adequate attempt
at referencing
according to
Harvard
conventions but
there are some
errors.
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reading. Look again
at the exemplars
and try to read
more journal
articles to develop
a more coherent
and integrated
academic style.
Referencing is poor
and does not
conform to Harvard
standards.
Requires
substantial proofreading. Look
again at the
exemplars and
try to read more
journal articles to
develop a more
coherent and
integrated
academic style.
Your referencing
is very poor and
hardly conforms
to the Harvard
conventions.
Requires a
major revision
to become a
reasonable
piece of work.
Look again at
the exemplars
and try to read
more journal
articles to
develop a more
coherent and
integrated
academic style.
Referencing is
sparse or nonexistent.
not
attempted.
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