A Case Study on Business Assignment

Data Analytics: A Business Case Study
Executive Summary
In Today’s world, eCommerce becoming very popular in all over the world. As the
people got interest in the buying through eCommerce platform, it increases the challenges to
the service provider. It mainly consist of customer satisfaction and increased competition. For
the service provider, it is mandatory to satisfy the customer and compete in the market.
In this case study, we develop the data sets regarding to computer and computer
accessories for the 1000 products. We considered the attributes as Product, Price, Shipping
Type (Free or Customer Paid), Sale Price, Customer Type (New or Existing), Number of
customers, Region (NSW, QLD, VIC, ACT, SA), Profit and Average Rating. We have
calculate some other variables.
We summarised the profit percentage on total sale and profit per item for shipping
type, customer type and region. We test the difference between considered variables for
shipping type, customer type and region. We did correlation and regression analysis.
Analytical findings are reported with conclusion. Recommendations to the company with
implementation plan is also given.
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Table of Contents
Sr. No. Topic Page No.
1 List of Abbreviations and assumptions made 3
2 Introduction – What is the problem? 4
3 Research Methodology 6
4 Analytical Findings 6
5 Recommendations to the company 24
6
An implementation plan based on the recommendations you
have provided
24
7 Conclusion 25
8 List of References 26
9 Appendix 27
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List of Abbreviations and assumptions made
NSW : New South Wales
QLD : Queensland
VIC : Victoria
ACT : Australian Capital Territory
SA : South Australia
Min : Minimum
Max : Maximum
Q1 : First Quartile
Q3 : Second Quartile
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Introduction – What is the problem?
In Today’s world, eCommerce becoming very popular in all over the world. In
Australia, eCommerce market generates about US $ 11789 Million revenue in 2018 and
expected to rise in near future.
eCommerce provides the online platform to the end user to buy the products directly.
This service is very useful for the people who are very busy in their work. eCommerce also
provides offers to the customers which attract the more people. In eCommerce platform,
consumers have more choice in quality, brand, color, price etc.
As the people got interest in the buying through eCommerce platform, it increases the
challenges to the service provider. It mainly consist of customer satisfaction and increased
competition. For the service provider, it is mandatory to satisfy the customer and compete in
the market.
About Data:
In this case study, we develop the data sets regarding to computer and computer
accessories for the 1000 products. We considered the following attributes
i) Product
ii) Price
iii) Shipping Type (Free or Customer Paid)
iv) Sale Price
v) Customer Type (New or Existing)
vi) Number of customers
vii) Region (NSW, QLD, VIC, ACT, SA)
viii) Profit
ix) Average Rating
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x) Total monthly sale amount
xi) Total monthly profit
xii) Profit Percentage
We define following variables as
Total Monthly sale amount= Sale Price × Number of customers
Total monthly profit= Profit × Number of customers
Profit Percentage= Total monthly profit /
Project Problem:
We are interested to know the following things
i) Profit analysis by shipping type, customer type and region wise.
ii) Whether there is any association between shipping type and region.
iii) Whether there is any association between customer type and region.
iv) Whether there is any association between shipping type and customer type.
v) Whether the price is significantly different for different shipping type.
vi) Whether the sale price is significantly different for different shipping type.
vii) Whether the profit is significantly different for different shipping type.
viii) Whether the rating is significantly different for different shipping type.
ix) Whether the price is significantly different for different customer type.
x) Whether the sale price is significantly different for different customer type.
xi) Whether the profit is significantly different for different customer type.
xii) Whether the rating is significantly different for different customer type.
xiii) Whether the price is significantly different for different region.
xiv) Whether the sale price is significantly different for different region.
xv) Whether the profit is significantly different for different region.
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xvi) Whether the rating is significantly different for different region.
xvii) Correlation analysis of variables
xviii) Regression analysis for total monthly sales
Research Methodology
Statistical tools and techniques are the necessary for analysis. In the analysis,
selection of proper statistical tools and techniques is very important. For profit analysis, we
summarised the profit percentage on total sale and profit per item for shipping type, customer
type and region. We have used the Chi-square test of association for testing the associations
of attributes. We have used independent two sample t-test for the testing the mean price, sale
price, profit and rating for shipping type and customer type. We analyzed the mean price, sale
price, profit and rating of region using one way ANOVA technique. We test the significance
of correlation between two variable. We tried to fit regression model for the monthly profit
and monthly sales.
Analytical Findings
Profit Analysis:
In profit analysis, we have given the total sales amount, total profit, profit percentage
on total sale amount and profit per item. Larger the value of profit percentage on total sale
amount and profit per item would be considered better for increasing the profit.
Table 1 gives the profit analysis according to shipping type. Both the shipping type customer
paid and free have no much difference in the average profit percentage. Still total monthly
sale and profit seems to be large for paid shipping customer than free shipping customer.
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