A retail organisation has recently been investigating customer spending patterns
ID: 3273165 • Letter: A
Question
A retail organisation has recently been investigating customer spending patterns at two of its stores, Store A and Store B, and has obtained the following data: Using these statistics, and any others you can derive, draft a short management report summarising the implications of this data.
Store A (£s)
Store B(£s)
Mean spending per customer
12.25
30.05
Median spending per customer
10.88
29.91
Standard deviation
7.79
7.77
Lower quartile
6.34
25.04
Upper quartile
17.43
35.32
The Store A figures were based on a representative sample of 500 customers and the Store B figures on 350 customers.
Store A (£s)
Store B(£s)
Mean spending per customer
12.25
30.05
Median spending per customer
10.88
29.91
Standard deviation
7.79
7.77
Lower quartile
6.34
25.04
Upper quartile
17.43
35.32
Explanation / Answer
The distribution of spending pattern at store A is right skewed (mean spending>median spending). Therefore, standard deviation alone cannot describe the variability. The median spending at store A is $10.88 and because the distribution is skewed, the third quartile (Q3=$17.43) is farther above the median than first quartile (Q1=$6.34). Similarly, the expenditure at store B is also right skewed (mean spending>median spending), and therefore, alongwith standard deviation quartiles need to be included to explain the variability. The median spending at store B is $29.91 and the distribution being skewed, the the third quartile (Q3=$35.32) is farther above the median than first quartile (Q1=$25.04). From the summary statistics, store A shows slightly higher variability (IQR=Q3-Q1=17.43-6.34=$11.09) than store B (IQR=$10.28) in terms of spending by customers.
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