Any submitted after 16:00 on the deadline date will be subject to the standard University late penalties (see below), unless an extension has been granted, in writing by the Senior Tutor, in advance of the deadline.

This assessment relates to the following module learning outcomes:

3

Coursework Brief:

Assume you are a marketing executive of a multinational supermarket chain. Your team has recently sent some vouchers by post to around 1,800 randomly selected customers who are already registered for the loyalty club, to promote kitchenware. The result of this campaign will be used to inform the decision of your team in order to extend the campaign to a wider group of customers.

Your manager would like to get insights and practical advice about this campaign and some other future marketing activities. After discussing with your colleagues, you are going to prepare a report which will include the following:

Task 1 (40 marks)

Carefully pre-process the dataset for the purpose of building a response model, by considering activities including (but not limited to):

· Pre-processing (e.g. checking whether there are any missing values and treating them)

· Conducting some basic descriptive analysis to understand the performance of the campaign (e.g. overall response rate, response rate by gender/age/class, etc.)

· Splitting the resulting data set into a training and test set.

Task 2 (50 marks)

Using the pre-processed data from Task 1, build response models with (a) logistic regression and another with any other classification approach. Discuss the following (but not limited to):

· Basic idea/formulation of the response models (i.e., briefly discuss the methods and provide references to support your discussion);

· Variable selection;

· Model interpretations;

· The predictive performance of the models (using suitable performance measures/charts).

Requirements/Notes:

· Please refer to the coursework grade descriptor document for a more detailed marking scheme.

· You could use either SPSS Statistics or Python to conduct the analysis. If you are using SPSS Statistics, please provide the screenshot of some essential outputs (note: No need to show all steps, just the key final outputs). If you are using Python, please provide the programming codes and the outputs.

· There is no fixed word count for each task. You can use the relative mark for each task to get an indication of how many words to write for that section.

Nature of Assessment: This is a SUMMATIVE ASSESSMENT. See ‘Weighting’ section above for the percentage that this assignment counts towards your final module mark.

Word Limit: +/-10% either side of the word count (see above) is deemed to be acceptable. Any text that exceeds an additional 10% will not attract any marks. The relevant word count includes items such as cover page, executive summary, title page, table of contents, tables, figures, in-text citations and section headings, if used. The relevant word count excludes your list of references and any appendices at the end of your coursework submission.

You should always include the word count (from Microsoft Word, not Turnitin), at the end of your coursework submission, before your list of references.

Title/Cover Page: You must include a title/ cover page that includes: your Student ID, Module Code, Assignment Title, Word Count. This assignment will be marked anonymously, please ensure that your name does not appear on any part of your assignment.

References: You should use the Harvard style to reference your assignment. The library provide guidance on how to reference in the Harvard style and this is available from: http://library.soton.ac.uk/sash/referencing

Submission Deadline: Please note that the submission deadline for Southampton Business School is 16.00 for ALL assessments.

Turnitin Submission: The assignment MUST be submitted electronically via Turnitin, which is accessed via the individual module on Blackboard. Further guidance on submitting assignments is available on the Blackboard support pages.

It is important that you allow enough time prior to the submission deadline to ensure your submission is processed on time as all late submissions are subject to a late penalty.  We would recommend you allow 30 minutes to upload your work and check the submission has been processed and is correct. Please make sure you submit to the correct assignment link.

Email submission receipts are not currently supported with Turnitin Feedback Studio LTI integrations, however following a submission, students are presented with a banner within their assignment dashboard that provides a link to download a submission receipt. You can also access your assignment dashboard at any time to download a copy of the submission receipt using the receipt icon. It is vital that you make a note of your Submission ID (Digital Receipt Number). This is a unique receipt number for your submission, and is proof of successful submission. You may be required to provide this number at a later date.  We recommend that you take a screenshot of this page, or note the number down on a piece of paper.

The last submission prior to the deadline will be treated as the final submission and will be the copy that is assessed by the marker.

It is your responsibility to ensure that the version received by the deadline is the final version, resubmissions after the deadline will not be accepted in any circumstances.

Important: If you have any problems during the submission process you should contact ServiceLine immediately by email at [email protected] or by phone on +44 (0)23 8059 5656.

Late Penalties: Further information on penalties for work submitted after the deadline can be found here.

Special Considerations: If you believe that illness or other circumstances have adversely affected your academic performance, information regarding the regulations governing Special Considerations can be accessed via the Governance and Policies landing pages: Regulations Governing Special Considerations (including Deadline Extension Requests) for all Taught Programmes and Taught Assessed Components of Research Degrees 2023-24 | University of Southampton

Extension Requests: : Extension requests along with supporting evidence should be submitted to the Student Office as soon as possible before the submission date. Information regarding the regulations governing extension requests can be accessed via the Governance and Policies landing pages: Regulations Governing Special Considerations (including Deadline Extension Requests) for all Taught Programmes and Taught Assessed Components of Research Degrees 2023-24 | University of Southampton

Academic Integrity Policy: Please note that you can access Academic Integrity Guidance for Students via the Quality Handbook: http://www.southampton.ac.uk/quality/assessment/academic_integrity.page?. Please note any suspected cases of Academic Integrity will be notified to the Academic Integrity Officer for investigation.

Feedback: Southampton Business School is committed to providing feedback within 4 weeks (University working days).  Once the marks are released and you have received your feedback, you can meet with your Module Leader / Module Lecturer / Personal Academic Tutor to discuss the feedback within 4 weeks from the release of marks date. Any additional arrangements for feedback are listed in the Module Profile.

Student Support: Study skills and language support for Southampton Business School students is available at: http://www.sbsaob.soton.ac.uk/study-skills-and-language-support/.