Data Analytics for E-commerce Profit Enhancement: A Case Study of a Book Segment

ICT706

Executive Summary
Electronic commerce or e-commerce is a business model which helps an organization to do
business on an electronic network or commonly known as the internet. E-commerce has almost
all the product or services like books, music, financial services and plane tickets.
This report mainly covers how to cover those aspects which are going to give a hike to the
performance of the company. And those aspects are going to be stated by the data scientist to
ensure success in the performance of the company.
All the useful information about the company is going to be collected through a SWOT analysis
method. To know about the current business operations and the solution provided by the
company in more depth qualitative data analysis method will be taken in use.
To increase the performance of the company it is necessary to have an information architecture
which is customer centric which is productive. The content and SEO should be integrated to
bring your business in front.
The product should be advertised in such a way that it becomes easy for the consumer to search
the product on the e-commerce sites. There should also be a relaxation for the consumer on the
shipping charges of the product to improve the business of the organization.
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Table of Contents
Executive Summary.........................................................................................................................1
List of Assumptions and Abbreviations..........................................................................................3
Background......................................................................................................................................4
Introduction......................................................................................................................................5
Research Methodology....................................................................................................................6
Descriptive or Analytical:............................................................................................................6
Applied or Fundamental:.............................................................................................................6
Quantitative or Qualitative:..........................................................................................................6
Conceptual or Empirical:.............................................................................................................7
Analytical Findings..........................................................................................................................8
Dataset..........................................................................................................................................8
Data Mining:................................................................................................................................9
Divisive method:........................................................................................................................10
Agglomerative method:..............................................................................................................11
Recommendation for the Company:..............................................................................................14
Implementation plan:.....................................................................................................................15
Code Implementation.....................................................................................................................16
Conclusion:....................................................................................................................................18
References:....................................................................................................................................19
Appendix........................................................................................................................................20
List of Figures
Figure 1: Books Dataset Snippet.....................................................................................................8
Figure 2: Training the Data using the Linear regression.................................................................9
Figure 3: Testing the data using the Linear Regression................................................................10
Figure 4: Sales Graph for Different Region..................................................................................11
Figure 5: Region Recommendation...............................................................................................12
Figure 6: Product Recommendation..............................................................................................12
Figure 7: Code for Data Prediction................................................................................................16
Figure 8: Final Prediction Over Dataset........................................................................................17
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List of Assumptions and Abbreviations
The Abbreviations that are used in this report are:
 Comma Separated Value – CSV
 Tab Separated Value – TSV
Assumptions for this report:
 A test dataset is developed for this process
 The Test Dataset will be divided into the Training Set and the Test Set
 Geographic Locations is added with it
 The Products are unique in this
 The need for a Delivery Person
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Background
This E-commerce company has been set up a long time back. At the beginning as it was not very
recognized it used to deals in very fewer regions and had a less amount of products to start with
but after some time passed it expanded its business from very few regions to a lot of regions and
not only with regions but it also expanded in the products because of which the company start
getting recognition .
This company works on almost all the domains which include Gadgets, Books, Toys, Clothes
and household items. Thinking about its customers the company delivers the product on the
doorsteps of the customer.
After having a successful glorious year for so long the company has hit the rocks and is an
immediate need for the strategies to expand its business like before or more than that. And to do
that the company has thought of taking in use the data analytics to get back its position in the
market. Through data analytics, the company will know about the regions from where they can
attain the highest performance.
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Introduction
As the Current scenario is where everything revolves around the e-commerce all the companies
are just competing with each other by surpassing other to be on the top but since the requirement
of the market changes every time. It is not very easy to cope up with the situations.
In this report, it mainly highlights an e-commerce organization who is searching for methods to
enhance the profit of the company with the help of data analytics. Its main aim is to know the
estimate of the monthly sales data for the segments of the book of the company. This report
stores the details about the products which has been sold in the books segment by the company
in the last few months.
The main agenda of this report is to work on the possibilities which are going to increase the
profit of the company by taking help of the Python programming to work on that possibility.
This report also contains the method which is going to produce the output.
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