BB6807 Data Driven Decision Making, Assignment Two, Kingstone University

Background/Context

Background:

Food & Stuff (F&S) is a UK-based supermarket chain operating in the highly competitive London market. With numerous supermarket options available to consumers in London, F&S is aiming to start using data-driven insights to better understand its customers to: (i) enhance targeted marketing, (ii) product assortment, and (iii) overall brand positioning. These three areas represent F&S’s key business objectives. From 2022 to 2024, F&S has collected extensive data on customer demographics and characteristics, purchasing habits, and transaction patterns.
Without an in-house business analytics team, F&S has partnered with Kingston Advisers (KA), an analytics management consultancy, to explore insights from this data. As a business analyst with KA, your role is to examine F&S’s customer data and deliver data-driven insights to support F&S’s decisions with respect to their business objectives. This case study will require you to explore and analyse the provided data and present findings across three tasks.

Dataset:

Due to General Data Protection Regulation (GDPR) requirements, the dataset shared by F&S with KA has been anonymised, aggregated at the customer level (i.e., each row corresponds to a ‘snapshot’ of information available on a particular customer), and represent a 5% sample of all customers collected between 2022 and 2024. This dataset is called the “Marketing Dataset”, and the accompanying data dictionary is named the “Marketing Data Dictionary”. Both are available as Excel files on Canvas and must be used inform the tasks in this assignment.

Assignment Task

Task A (20%: maximum 600 words)

Formulate three research questions relevant to F&S’s business objectives in marketing, product assortment, or brand positioning. You may choose to focus on one or more of F&S’ business objectives, with either one research question per objective or two or more research questions related to the same objective. For each research question, include a rationale that explains its relevance to the specific F&S business objective(s). You are encouraged to use references or external sources to support your research questions where applicable. Based on each research question, develop a corresponding statistical hypothesis.

Task B (30%: maximum 600 words)

Define a statistical methodology to test each hypothesis proposed in Task A. For each hypothesis, identify an appropriate statistical approach (e.g., regression analysis, t-tests, ANOVA, etc.) and justify your selection based on the hypothesis and variables involved. Describe the statistical evidence each methodology will produce, and how this evidence will be interpreted to test the hypothesis in question. Additionally, outline the assumptions required for each methodology to be valid, and, where appropriate, critically evaluate any limitations or potential biases associated with each approach.

Task C (50%: maximum 1,000 words; tables, charts or figures do not count towards the word limit)

Clearly present all relevant results from the statistical approaches proposed in Task B, ensuring that appropriate statistical procedures are followed. Use tables, charts, or figures as needed to organise and present your findings. For each hypothesis, provide a detailed interpretation of the results in relation to the specific hypothesis being tested.

Discuss the implications of your hypothesis testing findings for each research question, and critically evaluate how these results relate to F&S’s relevant business objectives.