24 April, 2024
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| Due Date: Tuesday, 15th August, 4pm (uploaded to SurreyLearn) | Assessment Weighting: 60% | Format: Individual report (2,000 words) | |||
| Assignment Topic: Marketing Analytics Report | Individual Assignment Brief Assignment: Individual report; maximum 2,000 words; no +/- 10%. Penalty for exceeding the word count is a reduction of 10 marks. An executive summary is not requested. For the individual report you will be required to apply marketing analytics techniques to address a marketing issue. Please download the Resit dataset. The dataset contains population data for 192 countries in 2022.Out of the 10 variables (population, yearly population change, net population change, …), select 5 segmentation criteria. Briefly justify, why you have selected these 5 variables/why they are relevant to your analysis.Perform a three-/four-/five-cluster analysis with Excel (you will find the material for this including detailed instructions for the Excel analysis in teaching week 6). Please submit both the individual report AND your Excel file on SurreyLearn. Please include a separate tab for the three-/four-/five-cluster analysis you have performed in the Excel file. Your report should include the following sections: Introduction that summarizes your report.Variable selection (5 out of 10) and your justification.Results summary table of three, four, and five cluster solution (check the instruction file – task 13).Justification of the most suitable number of clusters.Discussion of each cluster attributes in your selected solution.Marketing implications (should be relevant your selected solution and its discussed attributes) References (e.g., theoretical support from textbooks/articles or credible news resources) is expected, with proper referencing style (e.g., Harvard style). General information This is an individual assignment. Submission deadline: Tuesday, 15th August, 4pm (uploaded to SurreyLearn) Electronic submission only through Turnitin on SurreyLearn. Please note that the time of submission is logged once the file has been successfully uploaded and confirmed – this may take more than five minutes during busy periods. Please ensure the document/file has uploaded successfully before 4pm. Word count SBS policy The word count policy is a max. word count followed by a 10 points penalty. The penalty will be applied by the module leader and addressed in the individual student feedback. The word count includes everything (i.e., main text, headings, and sub-headings). The word count does not include abstract/summaries, table of contents, tables, figures or images, and bibliographies. Contribution to final mark for the module: 60% Aims The aim of the assignment is to test your ability to apply and communicate knowledge and skills acquired in the lectures, seminars and computer labs to provide data-driven recommendations. | ||||
Introduction to Marketing Analytics (MANM317)
Assignment #2 – Individual Report
Marking Criteria | Below Requirements (<50, fail) | Meeting Requirements (50-59, pass) | Meeting Requirements (60-69, merit) | Above Requirements (≥ 70, distinction) | Mark |
| Knowledge (25%) Ability to analyse, interpret, use and evaluate the data provided in order to deduce insights. | Demonstrates an incomplete understanding of the subject and little awareness of the limitations of knowledge. | Demonstrates a broad understanding of the subject, and an awareness of the limitations of knowledge. | Demonstrates a systematic and broad understanding of the subject, and an understanding of the limitations of knowledge. | Demonstrates an excellent breadth and depth of knowledge, and a good understanding of the limitations of knowledge. | / 25 |
| Application (25%) Capability to apply learned skills to analyse data. | Limited and inconsistent ability to apply learned skills to analyse data and does not reflect the complexity of the subject matter. | Is able to apply learned skills to analyse data in a way that offers adequate conclusions but may not always reflect the complexity of the subject. | Is able to apply learned skills to analyse data in a way that offers robust interpretations and insights and demonstrates good judgement on the basis of evidence when tackling complex problems. | Is able to apply learned skills to analyse data in a way that offers some perceptive interpretations and insights, and demonstrates sound judgement on the basis of evidence when tackling complex problems. | / 25 |
| Independent study (15%) Ability to use appropriate, independently selected sources to inform arguments. | Limited use of independently selected sources, which may not be carefully selected for appropriateness or accuracy. | Evidence of some use of a range of appropriate, independently selected sources to inform arguments. | Often uses appropriate, independently selected sources to inform arguments. | Consistently uses an extensive range of appropriate, independently selected sources to inform arguments. | / 15 |
| Development of arguments/conclusions (20%) Critical use, integration and synthesis of the data analysis and a range of sources to develop new insights and conclusions. | Underdeveloped ability to critically engage with the analysed data and sources, leading to overly simple conclusions and arguments that lack coherence. | Use of the analysed data and other sources to develop adequate arguments and some insights. | Critical use of the analysed data and a range of sources to develop coherent arguments and new insights, and to identify problems. | Critical use and synthesis of the analysed data and a range of sources to develop some insights and valid conclusions. | / 20 |
| Presentation & style (15%) Quality of writing, appropriate referencing, and presentation of the analysis. | Underdeveloped ability to present data and conclusions adequately. | Exhibits adequate skills to present data and conclusions. | Exhibits good technical and professional skills to present data and conclusions. | Exhibits excellent technical and professional skills to present data and deduced conclusions. | / 15 |
| Total | / 100 | ||||
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