Marketing Analytics, Campaign Evaluation, Customer Clustering, and Predictive Modeling in Business

Question 1: Marketing Analytics for a Car Rental Company

Question 1
Choose a car rental company (of your choice) that is active in the UK:
A. Briefly describe the business.
B. Identify and evaluate the role of 'marketing analytics' in the current activities of the focal business in delivering value to its customers.

C. Critically discuss other opportunities (e.g., collaboration with other businesses) that can provide the focal business to deliver (even more) value to its customers. If you had the opportunity, what other information (i.e., variables) would you collect about your customers?

D. In your answer, discuss the potential ethical issues that may arise from the implementation of 'marketing analytics' for the focal business.

Note: your answer (including arguments, discussions, recommendations, etc.) have to be realistic, coherent, and flow logically.

Question 2 
Imagine that you are the head of the marketing department of a chained beauty salon, namely, Galaxy Fashion. The recent global situation has significantly affected Galaxy Fashion’s business. In this regard, and to help the business, the CEO decided to run the following campaign: The CEO decided to randomly distribute 25% (discount) vouchers to its followers both on social media platforms (on Instagram, TikTok, Facebook, and Twitter) and through email. The CEO of Galaxy Fashion is now done with the campaign and is asking you to evaluate the results. In  rticular, the CEO would like to understand:

First Question (15 points): Overall, did the 25% (discount) voucher increase the number of transactions? By how much?
Second Question (10 points): Which channel(s) should be considered for the distribution of the 25% (discount) voucher in future campaigns?

Third Question (15 points): Overall, did the 25% (discount) voucher increase the revenue? To this end, you use the same dataset as above and replace the variable ‘transac_after’ with ‘reven_after’ (i.e., the revenue the customer generates after the campaign; see 'Galaxy_Fashion_b.csv' dataset).

Notes that you should consider in your answer:
• Include your R code and its respective results in your solution.
• Make sure that you clearly explain, justify, and detail all the assumptions and steps in your solution. These might include data cleaning (e.g., dropping variable(s), observation(s), changing type of variable(s), etc.) or any other assumptions or steps.
• Carefully and completely interpret your results (including all your coefficients).
• Critically evaluate the implications (based on all your results) for Galaxy Fashion. Make sure that you use specific and concrete examples in your solution.

Question 3 
A car insurance company, Drive Safe, is trying to increase its next year’s revenue by adjusting the fee that it charges from its insurers. To this aim, the CEO is asking you to:

Question: identify and group its current insurers into meaningful clusters that individuals within a cluster are similar to each other but different than those individuals in other clusters 

Notes that you should consider in your answer:
• Based on the structure and the information in the dataset (i.e., 'Insurance.csv' file), apply your suggested method using R. Include your R code and its respective results in your solution.

• Make sure that you clearly explain, justify, and detail all the assumptions and steps in your solution. These might include data cleaning (e.g., dropping variable(s), observation(s), changing type of variable(s), etc.), your decision (and justification why!) on the number of clusters, or any other assumptions or steps.

• Carefully and completely interpret your results.
• Critically evaluate the implications (based on your results). Make sure that you use specific and concrete examples in your solution.

Question 4 
The CEO of a broadband provider, Always Connect, claims that a customer's satisfaction score is a good indicator of whether or not the respective customer renews its contract. Therefore, The CEO is asking you to:

Question: come up with a model that allows the company to predict the customer’s satisfaction Based on the structure and the information in the dataset (i.e., 'Always_Connect.csv' file):
A. Draw a boxplot for the variable 'dist' and interpret it.
B. Suggest a tree-based method that is appropriate for answering the CEO’s question.
C. Apply your suggested method in part B. using R and explain your results.
D. Evaluate your model performance in C. (note that you are not required to split your dataset into train and test).
E. Do you agree with the following statement by the CEO? (explain why) “The customer’s home distance to the nearest city center is always highly and positively correlated with their satisfaction – as those that are far from city centers should be happy by just having access to the Internet”

Notes that you should consider in your answer:
• Include your R code and its respective results in your solution.
• Make sure that you clearly explain, justify, and detail all the assumptions and steps in your solution. These might include data cleaning (e.g., dropping variable(s), observation(s), changing type of variable(s), etc.) or any other assumptions or steps.
• Carefully and completely interpret your results. 

• Critically evaluate the implications (based on all your results) for Always Connect. Make sure that you use specific and concrete examples in your solution.