Greg Metcalf works for a national credit card company, and he is performing a customer value analysis on a subset of credit card customers. In order to perform the RFM analysis on the customers, Greg has compiled a data set that contains the dates of the last transaction (LastTransactionDate), total number of transactions in the past two years (Frequency), and total spending during the past two years (Spending). A portion of the data set is shown in the accompanying table.

a. Greg wants to calculate the number of days between January 1, 2019, and the last transaction date. Create a new variable “DaysSinceLast” that contains the number of days since the last transaction. What is the average number of days since the last purchase for all the customers? 

b. Create the RFM scores for each customer. How many customers have an RFM score of 555? What is their average spending? 

c. Create a new variable called “LogSpending” that contains the natural logarithms for the total spending during the past two years. Bin the logarithm values into five equal-interval groups. Label the groups using numbers 1 (lowest values) to 5 (highest values). How many observations are in group 2? 

d. Create a new variable called “AverageOrderSize” that contains the average spending per order. This is calculated by dividing total spending (Spending) by total number of transactions (Frequency) in the past two years. Bin the values of AverageOrderSize into five equal-interval groups. Label the groups using numbers 1 (lowest values) to 5 (highest values). How many observations are in group 2? 

e. Compare the groups in parts c and d. Are the groupings the same or different?

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LastTransactionDate 5/20/2017 8/16/2018 8/14/2017 Frequency 407 454 ⠀ 49 Spending 41903 35918 ⠀ 27918