Question: Marketing & Strategy Analytics: Imagine that you are approached by a chained apparel shop where it would like to know more about its customers.

Question 1 (40 points):

Imagine that you are approached by a chained apparel shop where it would like to know more about its customers. To this end, you are provided with the 'Apparel_Chain.csv' dataset (available on my.wbs). The dataset has one-year information on customers of the respective chained apparel shop who bought products in-store and online. The dataset includes the following list of variables, collected via loyalty card of their customers:

The marketing department is now asking you to answer the following specific research questions by analyzing the dataset provided:

A. Find the number and the portion (i.e., %) of single customers (5 points). B.    Draw a boxplot for 'age' and interpret your boxplot (5 points).

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C.    Draw a histogram for the overall satisfaction score of respondents. Interpret your histogram (including a discussion about the mean, standard deviation, and the number of observations) (5 points).

D. Draw a scatterplot for the following variables and interpret your plots: (15 points)

1. The number of online visits by the customer andthe amount (i.e., in £) spentonline. 2. The number of online visits by the customer and the distance from the shop.

3. Thenumber of onlinevisits by thecustomerandthe amount(i.e., in £)spentoffline. E.   Find the correlation between the following variables and interpret your results: (10

points)

1. The number of online transactions by the customer andthe amount (i.e., in£) spent online.

2. Income of the customer and the number of offline transactions.

Notes that you should consider in your answer:

•    Include your R code and its respective results in your solution.

•    Make sure 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 build all your arguments and implications (based on all your results) for the chained apparel shop management team.

•    The only part NOT counted in your word limit is your output from the RStudio’s console. Everything else (e.g., your code, tables, and words in your figures) counts.

Question 2 (35 points):

Imagine that a friend of yours runs a family restaurant. Your friend is now asking for your advice on their family business. Your friend puts together the information about a sample of their customers, including the following list of variables:

Based on the dataset 'iDine.csv,' answer the following questions:

A. Try to help the family business of your friend by finding what drives the customer’s current food value (hint: run a linear regression, where your dependent variable is: 'amount') (20 points).

B. Based on the provided dataset and your results in part A, evaluate the following statement by your friend: "To increase our revenue, I think we should provide more discount to our customers" (15 points).

Notes that you should consider in your answer:

•    Include your R code and its respective results in your solution.

•    Make sure 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) and link them to your suggestions.

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

•    The only part NOT counted in your word limit is your output from the RStudio’s console. Everything else (e.g., your code, tables, and words in your figures) counts.