.University

Abstract

The case study analyzes data from 50 sample internet transactions of Heavenly Chocolates from a latest month and tries to find patterns using descriptive statistical tools among the online purchases based on variables such as number of webpage visited, time spent on the Heavenly Chocolates website, days in which transactions were made, and type of browser used by the customer. It was identified that the more webpage online shoppers visited, the more the purchase they are like to make and vice versa. Similar positive relationship was identified, though relatively at a lesser degree, between times spent on website and amount of online purchases. In addition, it was identified that online shoppers are most active in purchase on Friday and Monday, respectively, compared to other days of the week. Finally, types of browser used by online shoppers don’t seem to have much effect on the amount they spend.

Keywords: quantitative variable, qualitative variable, website, transactions, mean, median, skewed, correlation, histogram

Heavenly Chocolates, a manufacturer and retailer of chocolate products, has developed a website two years ago began selling its products over the internet. Since inception, website sales have surpassed the company’s expectations. Now the company wants to find out strategies to increase online sales even more. This case study has analyzed data collected of a sample of 50 Heavenly Chocolates transactions by different customers selected from the previous month’s online sales to learn more about the website customers. Using descriptive statistics, the study identified variables which can affect the strategies for further online sales growth. The study will identify and explain trends in variables and their relationship and pattern with Amount Spent on the website.

There are 6 variables in the sample data set of 50 online transactions by customers. The variables and their types are as follows:

1. Customer Number: Qualitative Variable

2. Day of the Week: Qualitative Variable

3. Browser Used by Customers: Qualitative Variable

4. Times (Minutes) Spent on the Website: Quantitative - Continuous Variable

5. Pages (nos.) Viewed by Each Customer: Quantitative – Discrete Variable

6. Amount ($) Spent by Each Customer: Quantitative – Continuous Variable

In the following, explanation of major statistical measures of quantitative variables and relationship with qualitative and quantitative variables is provided.

Summary of Quantitative Variables

1. Times Spent (minute):

- A maximum portion (40%) of the customers spent about 10- 15 minutes [Table 1] on the website. About 74% of the 50 customers spent between 1 to 15 minutes on the website [Table 1], in which one customer spent a maximum of 32.9 minutes. The shape of the histogram [Figure 1], and relationship between mean and median (mean > median) [Table 2] indicate that the variable’s distribution is positively skewed.

2. Pages Viewed (nos.)

- About 50% of the customers visited about 2 – 4 pages of the website [Table 3]. The shape of the histogram [Figure 2] and relationship between mean, median, and mode (mean>median>mode) [Table 4] suggest the distribution is positively skewed.

3. Amount Spent ($)

- Of the 50 customers, about 74% of the customers spent less than or equal to $80 [Table 5]. Mean and median amount spent by customers is $ 68.13 and $ 62.15 respectively [Table 6]. The shape of the histogram [Figure 3] and relationship between mean and median (mean>median) [Table 6] suggest that the distribution is positively skewed.

Relationship between Amount Spent ($) and Other Quantitative Variables

1. Pages Visited and Amount Spent ($):

The scatter plot of pages visited and dollar amount spent shows a relatively strong positive relationship [Figure 4]. The correlation matrix suggests that the correlation coefficient between pages visited and amount spent on purchase by customers through the website is 0.72 [Table 7]. So the company can look to add web pages of more products to broaden the choice list for customers.

2. Time Spent (min) and Amount Spent:

The scatter plot of time spent and dollar amount spent shows a positive relationship, though not a very strong one [Figure 5]. The correlation matrix does suggest that the correlation coefficient between time spent by customers and amount spent on purchase by customers through website is 0.58 [Table 7].

Relationship of Amount Spent ($) with Other Variables

1. Day of the Week and Sales:

- In terms of average money spent per transaction on each day, more money is spent on Monday ($90.38), followed by money spent on Friday ($85.95) [Table 8]. Thus average money spent per transaction on Monday and Friday is significantly higher than that on other days. That is People tend to spend more in these two days per transaction compared to other days of the week.

2. Type of Browser and Sales:

- No. of users with Internet Explorer as browser is the highest among the sample data set - 52% [Table 9]. Internet Explorer users also spend more in total compared to users of other browsers (Firefox and Other). On average, transaction amount spent by internet explorer users is lower than that by Firefox and other browser users [Table 9], although the difference of averages isn’t significant. Overall browser type used by online shoppers during each transaction doesn’t provide much meaningful insight into the amount spent by online shoppers.

Conclusion

Given the analysis of the quantitative variables, it can be said that number of web pages viewed by online customers has a higher impact on the actual amount spent by customer on online purchase than times spent on the website by customers. The company may look to attract customers with more attractive web pages and increase list to choose from for customers. As time spent also has a positive relationship with Amount spent, then Heavenly Chocolates will benefit from keeping shoppers interested accessing its website.

Of the qualitative variables, day of the week in which the sample transactions were made have a significant impact on the amount spent. Online shoppers tend to purchase significantly more on Friday and Monday than on other days of the week. So in these two days, Heavenly Chocolates should make it easier for customers to access online portal of chocolates and may look to provide some discount offers to bolster sales in these two days. Finally, the sample data of browsers suggests that Internet Explorer users are the highest among shoppers using different browsers. Other than that, the sample data on browsers doesn’t tell much about the impact of browser choice on amount spent.

Bibliography

Lind, D. A., Marchal, W. G., & Wathen, S. A. (2005). Statistical Techniques in Business & Economics. McGraw-Hill.

Appendix

1. Tables

2. Figures

Abstract

The case study analyzes data from 50 sample internet transactions of Heavenly Chocolates from a latest month and tries to find patterns using descriptive statistical tools among the online purchases based on variables such as number of webpage visited, time spent on the Heavenly Chocolates website, days in which transactions were made, and type of browser used by the customer. It was identified that the more webpage online shoppers visited, the more the purchase they are like to make and vice versa. Similar positive relationship was identified, though relatively at a lesser degree, between times spent on website and amount of online purchases. In addition, it was identified that online shoppers are most active in purchase on Friday and Monday, respectively, compared to other days of the week. Finally, types of browser used by online shoppers don’t seem to have much effect on the amount they spend.

Keywords: quantitative variable, qualitative variable, website, transactions, mean, median, skewed, correlation, histogram

Heavenly Chocolates, a manufacturer and retailer of chocolate products, has developed a website two years ago began selling its products over the internet. Since inception, website sales have surpassed the company’s expectations. Now the company wants to find out strategies to increase online sales even more. This case study has analyzed data collected of a sample of 50 Heavenly Chocolates transactions by different customers selected from the previous month’s online sales to learn more about the website customers. Using descriptive statistics, the study identified variables which can affect the strategies for further online sales growth. The study will identify and explain trends in variables and their relationship and pattern with Amount Spent on the website.

There are 6 variables in the sample data set of 50 online transactions by customers. The variables and their types are as follows:

1. Customer Number: Qualitative Variable

2. Day of the Week: Qualitative Variable

3. Browser Used by Customers: Qualitative Variable

4. Times (Minutes) Spent on the Website: Quantitative - Continuous Variable

5. Pages (nos.) Viewed by Each Customer: Quantitative – Discrete Variable

6. Amount ($) Spent by Each Customer: Quantitative – Continuous Variable

In the following, explanation of major statistical measures of quantitative variables and relationship with qualitative and quantitative variables is provided.

Summary of Quantitative Variables

1. Times Spent (minute):

- A maximum portion (40%) of the customers spent about 10- 15 minutes [Table 1] on the website. About 74% of the 50 customers spent between 1 to 15 minutes on the website [Table 1], in which one customer spent a maximum of 32.9 minutes. The shape of the histogram [Figure 1], and relationship between mean and median (mean > median) [Table 2] indicate that the variable’s distribution is positively skewed.

2. Pages Viewed (nos.)

- About 50% of the customers visited about 2 – 4 pages of the website [Table 3]. The shape of the histogram [Figure 2] and relationship between mean, median, and mode (mean>median>mode) [Table 4] suggest the distribution is positively skewed.

3. Amount Spent ($)

- Of the 50 customers, about 74% of the customers spent less than or equal to $80 [Table 5]. Mean and median amount spent by customers is $ 68.13 and $ 62.15 respectively [Table 6]. The shape of the histogram [Figure 3] and relationship between mean and median (mean>median) [Table 6] suggest that the distribution is positively skewed.

Relationship between Amount Spent ($) and Other Quantitative Variables

1. Pages Visited and Amount Spent ($):

The scatter plot of pages visited and dollar amount spent shows a relatively strong positive relationship [Figure 4]. The correlation matrix suggests that the correlation coefficient between pages visited and amount spent on purchase by customers through the website is 0.72 [Table 7]. So the company can look to add web pages of more products to broaden the choice list for customers.

2. Time Spent (min) and Amount Spent:

The scatter plot of time spent and dollar amount spent shows a positive relationship, though not a very strong one [Figure 5]. The correlation matrix does suggest that the correlation coefficient between time spent by customers and amount spent on purchase by customers through website is 0.58 [Table 7].

Relationship of Amount Spent ($) with Other Variables

1. Day of the Week and Sales:

- In terms of average money spent per transaction on each day, more money is spent on Monday ($90.38), followed by money spent on Friday ($85.95) [Table 8]. Thus average money spent per transaction on Monday and Friday is significantly higher than that on other days. That is People tend to spend more in these two days per transaction compared to other days of the week.

2. Type of Browser and Sales:

- No. of users with Internet Explorer as browser is the highest among the sample data set - 52% [Table 9]. Internet Explorer users also spend more in total compared to users of other browsers (Firefox and Other). On average, transaction amount spent by internet explorer users is lower than that by Firefox and other browser users [Table 9], although the difference of averages isn’t significant. Overall browser type used by online shoppers during each transaction doesn’t provide much meaningful insight into the amount spent by online shoppers.

Conclusion

Given the analysis of the quantitative variables, it can be said that number of web pages viewed by online customers has a higher impact on the actual amount spent by customer on online purchase than times spent on the website by customers. The company may look to attract customers with more attractive web pages and increase list to choose from for customers. As time spent also has a positive relationship with Amount spent, then Heavenly Chocolates will benefit from keeping shoppers interested accessing its website.

Of the qualitative variables, day of the week in which the sample transactions were made have a significant impact on the amount spent. Online shoppers tend to purchase significantly more on Friday and Monday than on other days of the week. So in these two days, Heavenly Chocolates should make it easier for customers to access online portal of chocolates and may look to provide some discount offers to bolster sales in these two days. Finally, the sample data of browsers suggests that Internet Explorer users are the highest among shoppers using different browsers. Other than that, the sample data on browsers doesn’t tell much about the impact of browser choice on amount spent.

Bibliography

Lind, D. A., Marchal, W. G., & Wathen, S. A. (2005). Statistical Techniques in Business & Economics. McGraw-Hill.

Appendix

1. Tables

2. Figures