Pelican Stores, a division of National Clothing, is a chain

Pelican Stores, a division of National Clothing, is a chain of women’s apparel stores operating throughout the country. The chain recently ran a promotion in which discount coupons were sent to customers of other National Clothing stores. Data collected for a sample of 100 in-store credit card transactions at Pelican Stores during one day while the promotion was running are contained in the file PelicanStores. Table 3.9 shows a portion of the data set. The proprietary card method of payment refers to charges made using a National Clothing charge card. Customers who made a purchase using a discount coupon are referred to as promotional customers and customers who made a purchase but did not use a discount coupon are referred to as regular customers. Because the promotional coupons were not sent to regular Pelican Stores customers, management considers the sales made to people presenting the promotional coupons as sales it would not otherwise make. Of course, Pelican also hopes that the promotional customers will continue to shop at its stores.

Most of the variables shown in Table 3.9 are self-explanatory, but two of the variables require some clarification.

Items  The total number of items purchased

Net Sales    The total amount ($) charged to the credit card

Pelican’s management would like to use this sample data to learn about its customer base and to evaluate the promotion involving discount coupons.

Managerial Report

Use the methods of descriptive statistics presented in this chapter to summarize the data and comment on your findings. At a minimum, your report should include the following:

1. Descriptive statistics on net sales and descriptive statistics on net sales by various classifications of customers.
2. Descriptive statistics concerning the relationship between age and net sales.

 Initial post prompt: Your Managerial Report serves as your initial post to the discussion forum. After responding to the requirements posed by the Managerial Report, also provide an example in your career in which you believe one of the lessons learned from the Case has been/could be applicable. Alternatively, if you don’t have/foresee direct experience relevant to your current position, what type of scenario can you anticipate occurring where you can utilize one of the lessons learned from examining this case?

Response post prompt: Consider Managerial Reports posted by two of your peers. One or both of your responses may be to Managerial Reports for a case problem different from your own. Think critically and ask open-ended questions. If you agree, consider their position and expand upon their ideas. Provide an additional perspective. If you disagree, provide your reasoning. Always be professional and courteous in your responses. 

Post by classmate 1

For this week’s discussion, I chose to answer the managerial report for Pelican Stores once again. Pelican Stores, a division of National Clothing, is a chain of women’s apparel stores operating throughout the country. The store ran a promotion and compared sales of 100 transactions weighed between either a credit card or promotional card purchase.

-The most common purchase price is 31.60, and the most items purchased at once is 17.

-The promotional card was used most often for purchases, beating out other credit cards 70 purchases to 30. The average amount paid using a promotional card was $84.29, and $62.00 when using other credit cards only.

-Using information from the bar chart, we can ascertain that most spend by a specific age range was $620.17 from the 30-39 range. The most spend was also by the 30-39 range, having spent $2347.13

-This information can be worthwhile for Pelican Stores when they choose to utilize another promotional program in the future. They can use the insights gained from this one, and potentially advertise even more so to the 30-39yr old range, knowing they accounted for the most sales by group. At my organization, we would use this bar chart for retooling our marketing across our website. We would want to be attuned to the results of any surveys or data taken from this age range so we can tailor the website’s experience to the group that most frequently visits it.

Reference

Anderson, D. R., Sweeney, D. J., Williams, T. A., Camm, J. D., Cochran, J. J., (2021). Modern Business Statistics with Microsoft Office Excel (7th ed.) Cengage Learning – Mindtap. March 16th, 2022.

Post by classmate 2

Managerial Report

1. To analyze net sales, I calculated the mean, weighted mean, median and mode. The values are as follows:
   1. Mean: $77.60 – this is a sample mean, as we are calculating the mean from a sample representation of the entire customer population for the day.
      1. Weighted mean: $112.96 – this is important to calculate because different numbers of items were purchased in the transactions, affecting the amount of the net sale per transaction.
   2. Median: $59.71 – because there are an even number of observations (100), the median is the average of the two middle values (59.50 and 59.91).
   3. Mode: $31.60 – while this value occurred the most frequently with a total of four times, is it not a good representation of the data since it is much lower than both the mean and median.

With calculating the mean, weighted mean, median and mode, I believe the weighted mean most accurately depicts the net sales because it factors in the different number of items purchased with each transaction.

1. To analyze net sales by various classifications of customers, I first figured out the following data facts to start:
   1. Comparing male vs. female – 93% of the customers were female; 7% were male.
   2. Comparing married vs. single – 84% of the customers were married; 16% were single.
   3. Comparing types of cards used – 2% used American Express; 4% used Discover; 14% used Mastercard; 70% used the Proprietary card; 10% used Visa.

Knowing these simple figures, we can conclude that most customers shopping on this day were married females in their 40s using a proprietary card. Taking it a step further to factor in how net sales were affected by this data, I calculated different measures of variability, as shown below:

1. Range in the amount females spent vs. the amount males spent
   1. Females’ range – $274.36
   2. Males’ range – $89.30

We can see there is obviously much greater variation in what the females spent, which makes sense since there were far more females shopping that day than males.

1. IQR of married sales: Q3 – Q1 = 101.90 – 39.60 = $62.30

   The IQR of the net sales of married people is important to note since we already know that 84% of the people shopping were married. Of those 84%, range of the middle 50% was $62.30.

2. To compare the relationship between age and net sales, I first calculated the mean, median and mode age breakdown:
3. Mean: 43 (rounded to the nearest whole number)
4. Median: 42
5. Mode: 46
6. I then created a bar chart to show the distribution net sales per age group, grouped by decades for age and in increments of 20 by sales (see attached spreadsheet, sheet labeled bar chart). From this chart, we can see that most money was spent by people in their 30s and 40s. The highest group of net sales came from people in their 30s spending between $53-73 per transaction.    
7. Relating this to my work, we can use these kinds of descriptive statistics to analyze the types of customers we are reaching in our marketing campaigns. I work for a company that works with colleges and universities by helping them service applicants through the marketing and application process. By looking at age, male vs. female, country of residence, and type of program they are applying for, we can better focus our efforts to reach the most effective audience for each college.