Data Analytics for Sales Optimization in an E-commerce Camera Company

ICT706 Data Analytics

EXECUTIVE SUMMARY
The main aim of this project report is to use the basics of the Data Analytics and some tools
in order to increase the usability of the data model and to help in making an effective solution
that can help in making a decision in order to find out the products priority with the help of
the raw data sets. A dummy dataset is developed that is going to help in making the better
decision analysis with the help of Python Code. The Python Code is going to helpful in
generating the Graphs these graphs these graphs include Test Graphs over the dataset and the
Training Graph over the Dataset. There are other graphs too that are going to be helpful in
depicting the Regression Model Graphs. These graphs will give an insight into the type of
data and the Sales could be predicted using that.
For analysing the dataset, the company is going to need help for understanding the raw data
and make some predictions over it using the Some relations. Board of Directors of the
company need a Data Scientist that could be able to depict the monthly sales data and help in
making a better prediction for their sales and help them in gaining profit using that prediction
model. The Dataset that is going to be used is Camera Dataset.
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Table of Contents
EXECUTIVE SUMMARY........................................................................................................2
ASSUMPTIONS MADE...........................................................................................................5
BACKGROUND........................................................................................................................6
INTRODUCTION......................................................................................................................7
RESEARCH METHODOLOGY...............................................................................................8
QUALITATIVE METHODOLOGY:....................................................................................8
QUANTITATIVE METHODOLOGY:.................................................................................9
ANALYTICAL FINDINGS....................................................................................................10
DATASET:...........................................................................................................................10
CLUSTERING AND DATA MINING:..............................................................................11
DATA TRAINING AND TESTING...................................................................................14
RECOMMENDATION BASED ON ANALYSIS..................................................................17
GEOGRAPHIC REGION THAT SHOULD BE TARGETED TO INCREASE SALES
AND GENERATE PROFIT.................................................................................................17
PRODUCT THAT SHOULD BE PRIORITIZED FOR SALES.........................................18
IMPACT ON SALE AFTER FREE SHIPPING..................................................................18
RECOMMENDATIONS FOR THE COMPANY...................................................................19
IMPLEMENTATION PLAN FOR THE RECOMMENDATIONS.......................................20
IMPLEMENTATION OF THE PYTHON CODE..................................................................21
CONCLUSION........................................................................................................................23
REFERENCES.........................................................................................................................24
APPENDIX..............................................................................................................................25
List of Figures
Figure 1: Camera Dataset in the gadgets.csv file.....................................................................10
Figure 2: Data Analysis............................................................................................................12
Figure 3: Graph Showing the launch year and the Customer who have bought the Camera of
that year....................................................................................................................................12
Figure 4: No of customer who bought the Product versus the Data........................................13
Figure 5: Product Prize versus Monthly Sales.........................................................................13
Figure 6: Training Graph for the Monthly Sales and the Camera Prize..................................14
Figure 7: Test Set implementation of the Dataset....................................................................14
Figure 8: Linear Regression.....................................................................................................15
Figure 9: Final Regression for Prediction................................................................................15
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Figure 10: Recommendations..................................................................................................17
Figure 11: Recommendation....................................................................................................18
Figure 12: main.py...................................................................................................................21
Figure 13: Test and Training plotting Over Dataset................................................................22
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ASSUMPTIONS MADE
There are various assumptions that have been made in order to achieve the clarity over the
data:
 Dataset is developed for the Camera Segment
 Developed dataset is built from Scratch
 Some dummy Geographic location of the places where the Camera had delivered is
added
 A delivery person usage is not calculated
 It consists of various number of Cameras from the previous years that are build till
now
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BACKGROUND
Shopping is the most popular activity on the web. Anyone can display their pages, specific
good, and services. In 1991 internet was opened for commercial use and that time e-
commerce became possible. Since that year millions of business opened their pages for their
specific good and services. At first, e-commerce was only meant process of moneymaking
businesses with the help of innovative methods such as interchange of electronic information
and automated cash transfer (Orderhiven, 2018). Basically, the internet took 4 years to grown
up and in 2000 there are many companies in the US and Europe who represented their
services in the world.
Currently, there are 5 largest internet retailers. Those are:
1. Dell
2. Staples
3. Amazon
4. Hewlett Packard
5. Office Depot
According to the research of 2008, amazon.com have about 615 million users per year and
they like the best thing is their review system. e-commerce history is evolving like customer
advantages’ updating.
The company only sells cameras in limited areas and those areas that very repudiated image
of this company as its main department is camera and unlike other e-commerce company, it
does not indulge with the sellers for the process of delivery. Also, the Customer service of
this company is very supportive.
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