NBS8604 Marketing Analytics Luna7 Assessment Second Semester 2026 | Newcastle University

NBS8604 Marketing Analytics Assessment

You will be assessed on individual work through the following two items:

• Project Proposal. This is an optional, formative assessment and worth 0% of the mark for the module. You will provide a short (500-word) description and justification for your chosen marketing analytics data set, research problem and selected method of investigation.
• Individual Report. This is worth 100% of the mark for the module. The project will consist of a final 2,000-word report detailing your research problem, analysis and results.

Luna7: Clothing and Home Items Retailer

Luna7 is a fictitious retailer that sells clothing and home items (similar to Zara) in the US. The retailer is seeking various ways to grow its business. It has launched a few promotional campaigns recently and it is exploring the potential to launch a clothing rental service (e.g., it ran a short survey to examine people’s intentions); it is also open to ideas to extend the business to other product categories or services. In this project, your task is to use marketing analytical tools to aid in future decisions about the company. You cannot do everything so that you must be selective about the topic, techniques and data used.

The dataset for Luna7 has been posted to the module webpage. Two versions of dataset (SPSS and Excel) are available. You can find the details about each variable in the SPSS file. The data includes a representative sample of customers with information integrated from several sources (e.g., survey, transaction records, and information from third parties). Part of your task is to examine what information is available in the dataset and then to decide on your research topic. You do not have to make use of all the variables but rather only those that you believe are useful for your research topic.

There may be many research topics that you can explore. The following are only a few examples, and you are encouraged to explore other creative ideas:

• Segment customers to identify those who are most valuable for products.
• Identify factors related to product selection or revenue.
• Predict why customers are leaving (e.g., inactive for long).
• Predict customer future purchases for new offers.
• Develop new product ideas, e.g., related to lifestyle, technology or media.

Formative Project Proposal (optional)

You may submit a 500-word project proposal. This will enable you to obtain feedback before the project report. To complete the proposal, you must become familiar with the data and think about the potential topics that the dataset enables you to explore. Your proposal will include the following:

(1) Describe the basic features of the dataset. For example:

• How many consumers are included in the dataset?
• What aspects of consumers are described?
• How are the variables measured?
• Are there any missing values and will they create any problem?
• Does the data need any pre-processing before further analysis?

(2) State several possible issues that the dataset enables you to investigate. For example:

• What are the potential dependent variables for analysis and what managerial questions can they address?
• You may want to generate some initial descriptive statistics or tables/graphs to get a better idea of the data (e.g., consumer profile, company performance, etc., to detect any major issues).

(3) Select and discuss a specific marketing problem for your project. 

• Which issue(s) have you decided to focus on and why is it important (you may cite some prior research/reports/news to support your idea)?
• If addressed, how would your findings help Luna7’s marketing decisions?
• What variables will you use for analysis (e.g., dependent and independent variables).

(4) What techniques could you apply for investigating the problem? Why are these techniques appropriate? What are their benefits and limitations?

Students should submit the project proposal by 4pm on the 25th of March, 2022. The proposal must be submitted online via Canvas. The brief will be evaluated on how well it answers questions 1 to 4 above and meets the marking criteria.

Written Report

The assignment requires you to follow-through with your proposed analysis. The document should be written in Microsoft Word in the style of a report aimed at senior managers. It should be no more than 2000 words (+/- 10%), double-spaced, in a font size no less than 11-points. You must cite and reference all sources used in the report. The report should consist of the following: 

• Executive Summary (approximately 150 words): a non-technical summary of the report, including the aims, methodology used and major findings/implications.
• Introduction (approximately 300 words): Explain the business problem and context of the study, including a clear statement of the aim and objectives. Explain why the study is needed and what it will deliver. You may consider background on the market (including sources). 
• Methodology (approximately 450 words): There are several key elements to mention. First, data selection and data preparation should be explained. Which aspects of the data set will you use in the report? Is any data cleansing or preparation needed, e.g. recoding of variables? Second, the analytical procedures must be explained. Describe the analytical techniques that you have used and explain why you have used them. How will you evaluate the quality of your models? Third, think about how the results of your analysis should be visualised.
• Results (approximately 700 words): This should indicate, for each research objective, the main findings of your analysis. A preliminary section may be used to provide any descriptive statistics on the data set. The main body of the section will provide the results of applying your marketing analytics techniques to the data set. Interpret and discuss the findings that you describe, rather than merely reciting the numbers. You must indicate, where appropriate, whether your findings are statistically significant. You must also evaluate the quality of your modelling and analysis. Note any limitations that you are not able to address in the report.
• Business Implications and Recommendations (approximately 400 words): Based on your results you will make recommendations to management. Provide a brief action plan with the steps you recommend taking to reach this goal. In terms of measurement and monitoring, how will you ensure that you reach/have reached the goal? You can integrate your knowledge and learning from other modules to do this.
• Appendices (not included in word count): Focus on the main points and key supporting tables and figures in the main body of the report to maintain the flow. Supplementary content may be added in appendices.
• References (not included in word count): Include the sources used to create your report in Harvard format.

The report will be marked on the Specific Marking Criteria for Marketing Analytics– see module outline. Please pay attention to:  (i) idea, method and design; (ii) quality of data analysis and interpretation of results; (iii) quality of recommendations; and (iv) readability (clarity of writing and organization of material). Plagiarism is a serious offence that can lead to you failing the module and your suspension from studies.

Some hints on effective report writing:

1.Make the report clear, professional and well designed.
2.Number the pages.
3.Divide the report into sections with appropriate headings.
4.Include a table of contents with page numbers.
5.Avoid using technical language unless needed. This is particularly important when writing the executive summary.
6.Write the document for a senior manager. Thus, they will be most interested in your research findings and their implications for business.

Submission

The individual report must be submitted no later than 4pm on the 16th of May, 2022.

The assignment must be submitted online via Canvas

Assessment Surgeries

A PIP lecture will discuss the assignment in week 29 and give the opportunity for all students to ask questions. 

An assignment workshop will be offered in the computer lab in week 36.