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Web scraping, also known as data mining, is the process of collecting large amounts of data from the web and then placing it in databases for future analysis and later use. Web scraping offers insight into price data, market dynamics, prevailing trends, practices employed by your competitors and the challenges they face. This is readily available data if you know how to get it. What many marketers don't know is how useful it can be to them. In this article, we will explain the advantage of Web Scraping technique and provide a practical example that can be beneficial for e-commerce businesses and online marketers.
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HKCorporation IT Official Journal January 2021
1
Importance of web scraping in e-commerce
and e-marketing
Kasereka Henrys
MSc in Software Engineering
Bugema University
Published January 2021, HKCorporation
arisjokov@gmail.com
Abstract
Web scraping, also known as data mining, is the
process of collecting large amounts of data from
the web and then placing it in databases for
future analysis and later use. Web scraping offers
insight into price data, market dynamics,
prevailing trends, practices employed by your
competitors and the challenges they face. This is
readily available data if you know how to get it.
What many marketers don't know is how useful
it can be to them. In this article, we will explain
the advantage of Web scraping technique and
supply a practical example that can be beneficial
for e-commerce businesses and online
marketers.
KEYWORDS web scraping, e-marketing,
e-commerce, python.
INTRODUCTION
Websites are an ocean of limitless information
which anyone and everyone can access. The new
trend of technology put us to change the way
we’re doing our business. The Internet now is
the new place for business. Knowing how to use
the Internet and the different opportunities that
can bring us can be one of the keys to success in
e-commerce and e-marketing.
Data crawling or web scraping or data harvesting
has been into the existence for as long as the web
itself. It is always associated with web content
extraction, at the begin it wasn’t always served
this purpose. Web scraping can be considered as
a method of retrieving or extraction content from
a website for Web scraping is the method of
retrieving or extracting content from a website
HKCorporation IT Official Journal January 2021
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for the purpose of using it for purposes beyond
the control of the website owner.
The first use of web scraping was to create links
with test frameworks. Using tools like Selenium,
companies like IP-Label have created products
that allow web developers and webmasters to
monitor website performance on a daily basis
(xbyte, 2021). In the early times, extracting web
data meant copying the text available on a web
page to a local file, manually this approach was
extremely inefficient and could not be used for
business application. Spreadsheet software like
Microsoft excel and google sheets have some
basic web scraping capabilities and they were
mainly used for extracting HTML tables from
webpages (Slideshare, 2021).
In a world of fierce competition, every business
tries to exceed itself. The question that probably
worries all other entrepreneurs. In an industry
where everything is customer-centric,
competitor analysis is not a choice but a
necessity. Having access to so much data can
provide a competitive advantage in the field to
which you belong (Samanta, 2021).
Since a huge amount of mixed data is constantly
being generated on the web, web scraping is
widely recognized as an efficient and powerful
technique for collecting big data (Judit, 2001).
This concept of web scraping is not new to most
data scientists, but is in fact becoming
increasingly well-known due to the mass of data
we can find on the internet and new startups that
don't want to spend time collecting data where it
can be found quickly on the internet.
OVERVIEW OF CONCEPTS
What is Ecommerce?
Ecommerce, also known as electronic commerce
or internet commerce, refers to the buying and
selling of goods or services using the internet,
and the transfer of money and data to execute
these transactions (Shopify, 20121). According
to Wikipedia e-commerce Electronic is the
activity of buying or selling products
electronically on online services or on the
Internet (Wikipedia, E-commerce, 2021).
Type of e-commerce:
Business to business
Business to consumer
Consumer to consumer
Consumer to business
What is e marketing?
E-marketing (or electronic marketing) refers to
marketing carried out on the Internet. Two
HKCorporation IT Official Journal January 2021
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synonyms of E-Marketing are Internet
Marketing and Online Marketing which are
frequently interchanged. Electronic marketing is
the process of marketing a brand (business,
product or service) using the Internet through
computers and mobile devices
(Conversionpipeline, 2020). Encyclopedia.com
defines e-marketing as a process of planning and
executing the design, distribution, promotion
and pricing of products and services in a
computerized and networked environment, such
as the Internet and the World Wide Web, to
facilitate exchanges and respond to customer
requests (Encyclopedia, 2020).
What is Web Scraping?
Web scraping is automatically retrieving (and
processing) information from websites (Bosch,
2021). Matthew define web scraping as a
process of making a semi-structured document
from the internet, usually in the form of web
pages like HTML or XHTML, and analyze the
document to take certain data from the page to
be used for other purpose (Mathew, 2010).
BENEFITS OF WEB SCRAPING
Web scraping has emerged as an important
strategy for e-commerce businesses, especially
in delivering rich data-based insights.
Practices of web scraping in e-commerce
Price-monitoring and Product Research
Online price comparison
Better Customer analysis
Market Analysis
Better advertisements
Influences Marketing and Sales Strategy
Brand monitoring
Extract business details from business
directory
Helps in Future analysis
Etc.
Advantage of using web scraping
An online presence can be tracked. It is
also an important aspect of web scraping
where company profiles and reviews on
websites can be removed. This can be
used to see product performance, user
behavior, and reaction.
Personalized analysis and curation. This
one is mainly for new websites / channels
where the retrieved data can be useful for
channels to know viewer behavior. This
is done for the purpose of delivering
targeted news to the public. So, what you
watch online sets the pattern for the
website to behave so that the business
HKCorporation IT Official Journal January 2021
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knows its audience and can deliver what
the audience actually likes.
Online reputation. When the company
plans its ORM strategy, the data
extracted helps understand which
audiencescompanies are most hoping to
have an impact and which areas of
responsibility may most expose the
brand to reputation damage. By
understanding these areas of
vulnerability, the business can use them
to its greatest advantage.
Provide better targeted advertising to
customers. Scrapping not only gives
numbers, but also sentiment and
behavioral analysis, so the business can
know what audience types and choice of
ads they want to see.
To bring together public opinion.
Monitor specific company pages on
social media to gather updates on what
people are saying about certain
companies and their products. Data
collection is always useful for product
growth.
Search engine results for SEO tracking.
By scraping off organic search results,
you can quickly find your SEO
competitors for a particular search term.
You can determine the title tags and the
keywords they target. So you get an idea
of what keywords drive traffic to a
website, what categories of content get
links and user engagement, what kind of
resources it takes to rank your site.
Scratch Leads: This is another important
use for the sales-oriented organization in
which lead generation is done. Sales
teams are always hungry for data, and
using web scraping technique, you can
pull leads from many directories and
then contact them to do an introduction
to selling. The data can be extracted in
any format you want and can be used for
lead generation, brand development, or
other purposes.
To create vertical specific search
engines. Even though this is a new thing
that is popular in the market, but also
requires a lot of data, so web scraping is
done for as much public data as possible
because this volume of data is practically
impossible to collect
Challenges of web scraping
It is not always easy to know which site
to scrape. Sometimes choose between
scraping the data owner or an aggregator
site.
The internet is dynamic. Each web site
has a particular structure, which may be
subject to changes anytime.
Data is volatile.
Legal issues and informing web site
owners.
HKCorporation IT Official Journal January 2021
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HOW DO WEB SCRAPERS WORK?
First step, robots.txt: One of the most
important and overlooked step is to
check the robots.txt file to ensure that we
have the permission to access the web
page without violating any terms or
conditions.
Secondly, the web scraper will be given
one or more URLs to load before
scraping. The scraper then loads the
entire HTML code for the page in
question. More advanced scrapers will
render the entire website, including CSS
and JavaScript elements.
Then the scraper will either extract all the
data on the page or specific data selected
by the user before the project is run.
Ideally, the user will go through the
process of selecting the specific data they
want from the page. For example, you
might want to scrape an Amazon product
page for prices and models but are not
necessarily interested in product reviews.
Lastly, the web scraper will output all the
data that has been collected into a format
that is more useful to the user.
Figure 1: Architecture of web scraping
Most web scrapers will output data to a CSV or
Excel spreadsheet, while more advanced
scrapers will support other formats such as
JSON which can be used for an API.
Figure 2: Overview of web scraping system
HKCorporation IT Official Journal January 2021
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WEB SCRAPING TECHNIQUES
There are many techniques use for scraping
data on internet (wikipedia, 2021).
Traditional copy and paste
Text grapping and regular expression
Hypertext Transfer Protocol (HTTP)
Programming
Hyper Text Markup Language (HTML)
Parsing
Document Object Model (DOM)Parsing
Web Scraping Software
Vertical aggregation platforms
Semantic annotation recognizing
Computer vision web-page analyzers
As you can see we have many techniques that
can be used but the target is to use a technique
that supplies us a correct result in a reasonable
time and the best one is web scraping software.
Web scraping software
You have a choice between using an existing
software or build your own script. There are
many software tools available that can be used
to scrape data on internet. Therefore, there are
two well-known and popular methods that can
be used to scrape data on the web namely the use
generic web scraping software and write code.
Use generic web scraping software
Web Scraping software falls under 2 categories.
First, which can be locally installed in your
computer and second, which runs in cloud
browser based.
Visual Web Ripper
Helium Scraper
Screen Scraper
OutWit Hub
Mozenda
WebSundew
Web Content Extractor
import.io
etc.
Writing code
You can hire a developer to build custom data
extraction software for your specific
requirement or do it by yourself. The most well-
known language use in web scraping include:
R programing (rvest,Rselenium)
Python (BeautifulSoup, Selenium)
Ruby
NodeJS
Java
HKCorporation IT Official Journal January 2021
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Advantage and disadvantage
Generic web scraping
Programming language
Closed source
Open source
Expensive
Free
Limited
Extremely powerful
Easy to learn
Steep learning curve
Figure 3: Advantage and disadvantage between
generic software and writing code for web
scraping.
The problem with most generic web scraping
software is that they are very difficult to set up
and to use (webharvy, 2021). Based on the
challenge of web scraping can face it will be
recommended making your algorithm for web
scraping.
PRACTICAL EXAMPLE
One of the advantages of web scraping in e-
commerce is market analysis. In our practical
example, we will show how to get data from
Amazon. The section that will interest us will be
to obtain the Amazon Best Sellers data in our
case we will get the bestselling phone in amazon.
These details can be useful to anyone who wants
to start selling or manufacturing phones. Having
the big picture of the market will help you
improve your business and plan well.
Python
The reason we choose Python it is because it is
popular, high-level programming language.
Python can run on many different platforms and
has a simple syntax similar to the English
language, therefore, it is easy to code.
First of all, the goal of web scraping is to collect
web data that would be in HTML format or Json.
Python provides a library called Requests, which
is a simple HTML library that allows you to
integrate your Python programs with web
services.
Once you find the relevant data for your project
on the webpage, you can download it for
valuable insight. To do this, Python provides
another library called BeautifulSoup, which
helps you retrieve particular content from a web
page, remove HTML tags, and save the
information.
The last step in web scraping is to save the
collected data in a structured form. With the help
of Python Pandas Library, you can store the data
in the desired format.
Amazon.com
Amazon.com, Inc. is an American multinational
technology company based in Seattle,
Washington, which focuses on e-commerce,
cloud computing, digital streaming, and artificial
HKCorporation IT Official Journal January 2021
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intelligence. It is considered one of the Big Five
companies in the U.S. In e-commerce amazon is
leading in that domain how we can benefit of the
huge date which we find on its website which
can help us for price comparing or other aspect
in e-commerce (Wikipedia, wikipedia, 2021).
Implementation
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Mon Jan 18 15:57:26 2021
@email : arisjokov@gmail.com
@author: henryskas
"""
import requests
import pandas as pd
import matplotlib.pyplot as plt
import numpy as np
from bs4 import BeautifulSoup
from datetime import datetime
headers = {"User-Agent":"Mozilla/5.0 (Windows NT 10.0;
Win64; x64; rv:66.0) Gecko/20100101 Firefox/84.0", "Accept-
Encoding":"gzip, deflate",
"Accept":"text/html,application/xhtml+xml,application/xml;q=
0.9,*/*;q=0.8", "DNT":"1","Connection":"close", "Upgrade-
Insecure-Requests":"1"}
result = requests.get("https://www.amazon.com/Best-Sellers-
Cell-Phones/zgbs/wireless/7072561011", headers=headers)
#result = requests.get("https://www.amazon.com/best-sellers-
books-Amazon/zgbs/books", headers=headers)
print(result.status_code)
if result.status_code < 500 :
src = result.content
soup = BeautifulSoup(src,'lxml')
links = soup.find_all('span',{'class' : 'aok-inline-block zg-
item'})
#define dataframe
df =
pd.DataFrame(columns=['tittledata','pricedata','linkdata'])
#Get all data
for link in links :
linkdata = link.find('a',{'class':'a-link-normal a-text-
normal'})
pricedata = link.find('span',{'class':'p13n-sc-price'})
tittledata = link.find('div',{'class':'p13n-sc-truncate-
desktop-type2'})
# Check empty link
if linkdata is not None and linkdata['class'] is not None:
df2 =
pd.DataFrame([[tittledata.text.strip(),pricedata.text.strip(),linkd
ata['href'].strip()]],columns=['tittledata','pricedata','linkdata'])
df = df.append(df2,ignore_index=True)
else :
print("Link doesn't exist")
now = datetime.now()
current_time = now.strftime("%H%M%S")
#Split price to get a numeric number
df["pricedata"] = df["pricedata"].str.replace('$', '')
df["pricedata"] = df["pricedata"].str.replace(',', '')
df['price'] = df['pricedata'].apply(lambda x: x.split('.')[0])
df['price'] = df['price'].astype(int)
#Add a new column
df['currency']='$'
#Let's find out 10 product which have the highest-priced
data = df.sort_values(["price"], axis=0,
ascending=False)[:10]
data['tittledata'] = data['tittledata'].str.slice(0,20)
#Plot
y_pos = np.arange(len(data['tittledata']))
# Create horizontal bars
plt.barh(y_pos, data['price'])
# Create names on the y-axis
plt.yticks(y_pos, data['tittledata'])
#
plt.xlabel('Amount in dollars')
plt.ylabel('Labels')
plt.title('10 products with the highest prices')
plt.legend()
# Show graphic
plt.show()
#Generate a csv
df.to_csv('result' + current_time + '.csv')
else:
if "To discuss automated access to Amazon data please
contact" in result.text:
print("Page was blocked by Amazon. ", result.text)
else:
print("Page must have been blocked by Amazon as the
status code was ", result.text)
Figure 4: Web scraping algorithm to retrieve
the bestselling products on amazon.com
(Author)
Result
Figure 5: Histogram of 10 best-selling phones
at the highest prices January 18, 2021
HKCorporation IT Official Journal January 2021
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Table 1: 10 best-selling phones at the highest
prices January 18, 2021
Table 2: Amazon Phone Best Selling List
January 18, 2021
CONCLUSION
“If programming is magic, then web scraping is
wizardry(Mitchell, 2015) Said Ryan Mitchell.
The presence of the Internet led to increasing
source of information that can be accessed so
that information seeking activities become the
most common activities performed and became
one of the activities that took quite a bit (Adam,
2012). The Internet will be remembered as the
first place where we can collect huge amounts of
data without spending a lot of energy or money.
Whether in e-commerce or e-marketing, the use
of the technique of web scraping will be the key
to success as it will provide insight into the
targeting market and help decision makers.
ACKNOWLEDGMENT
The author would like to thank Mr. Ricky
Muhindo (Ph.D. Computer science candidate at
Northcentral university) for his support.
REFERENCES
Adam, R. (2012). Task-Specific Information
Retrieval System for Software
Engineers. Journal of Computer and
System Sciences, 78.
Bosch, O. t. (2021, 01 13). Uses of web
scraping for official statistics. Retrieved
from circabc.europa.eu:
https://circabc.europa.eu/sd/a/5e250346-
44a9-471b-87f1-
5b5ddb59aa77/1_Big%20Data%20Sour
ces%20part3-Day%201-A%20Use.pdf
Conversionpipeline. (2020, 01 13).
conversionpipeline. Retrieved from
conversionpipeline:
HKCorporation IT Official Journal January 2021
10
https://conversionpipeline.com/what-is-
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marketing
Judit, B.-I. (2001). Data collection methods on
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Mitchell, R. (2015). Web Scrapping Using
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https://towardsdatascience.com/data-
scraping-how-to-leverage-it-for-your-
ecommerce-business-7320e8f82358
Shopify. (20121, 01 13). what-is-ecommerce.
Retrieved from shopify:
https://www.shopify.com/encyclopedia/
what-is-ecommerce
Slideshare. (2021, 1 10). the history of web
scraping. Retrieved from slideshare:
https://fr.slideshare.net/promptcloud/the
-history-of-web-scraping
webharvy. (2021, 13 01). what is web scraping.
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commerce
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company)
xbyte. (2021, 1 10). the history of web
scraping. Retrieved from xbyte:
https://www.xbyte.io/the-history-of-
web-scraping.php
BIOGRAPHY OF AUTHORS
Kasereka Henrys, he
received his B.Sc.
Degree in Computer
Science from the
University of Kinshasa.
He completed his Master
of Computer Science
degree from Bugema
University in software
engineering. Got an online specialization in Data
Science on coursera provided by Johns Hopkins
University. He is interested in the field of data
science, mobile and web programming.
... Access to these data can provide a competitive advantage to a user in the field to which s/he belongs. Since a huge amount of mixed data is constantly being generated on the web, web scraping is widely recognized as an efficient and powerful technique for collecting big data [4]. ...
... Some of these programs are free, whilst others are purely commercial and charge a one-off or regular subscription fee. Such web scraping software are (1) Visual Web Ripper, (2) Web Content Extractor and (3) WebSundew amongst others [3,4]. Asides web scrapping software, there are programming languages with in-built powerful web scrapping libraries use for building a custom web data extractor with a specific requirement. ...
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Websites are regarded as domains of limitless information which anyone and everyone can access. The new trend of technology has shaped the way we do and manage our businesses. Today, advancements in Internet technology has given rise to the proliferation of e-commerce websites. This, in turn made the activities and lifestyles of marketers/vendors, retailers and consumers (collectively regarded as users in this paper) easier as it provides convenient platforms to sale/order items through the internet. Unfortunately, these desirable benefits are not without drawbacks as these platforms require that the users spend a lot of time and efforts searching for best product deals, products updates and offers on e-commerce websites. Furthermore, they need to filter and compare search results by themselves which takes a lot of time and there are chances of ambiguous results. In this paper, we applied web crawling and scraping methods on an e-commerce website to obtain HTML data for identifying products updates based on the current time. These HTML data are preprocessed to extract details of the products such as name, price, post date and time, etc. to serve as useful information for users.
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... Access to these data can provide a competitive advantage to a user in the field to which s/he belongs. Since a huge amount of mixed data is constantly being generated on the web, web scraping is widely recognized as an efficient and powerful technique for collecting big data [4]. ...
Preprint
Full-text available
Websites are regarded as domains of limitless information which anyone and everyone can access. The new trend of technology put us to change the way we are doing our business. The Internet now is fastly becoming a new place for business and the advancement in this technology gave rise to the number of e-commerce websites. This made the lifestyle of marketers/vendors, retailers and consumers (collectively regarded as users in this paper) easy, because it provides easy platforms to sale/order items through the internet. This also requires that the users will have to spend a lot of time and effort to search for the best product deals, products updates and offers on e-commerce websites. They have to filter and compare search results by themselves which takes a lot of time and there are chances of ambiguous results. In this paper, we applied web crawling and scraping methods on an e-commerce website to get HTML data for identifying products updates based on the current time. The HTML data is preprocessed to extract details of the products such as name, price, post date and time, etc. to serve as useful information for users.
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This paper discusses the development of task-specific information retrieval systems for software engineers. We discuss how software engineers interact with information and information retrieval systems and investigate to what extent a domain-specific search and recommendation system can be developed in order to support their work related activities. We have conducted a user study which is based on the “Cognitive Research Framework” to identify the relation between the information objects used during the code development (code snippets and search queries), the tasks users engage in and the associated use of search interfaces. Based on our user studies, a questionnaire and an automated observation of user interactions with the browser and software development environment, we identify that software engineers engage in a finite number of work related tasks and they also develop a finite number of “work practices”/“archetypes of behaviour”. Secondly we identify a group of domain specific behaviours that can successfully be used as a source of strong implicit relevance feedback. Based on our results, we design a snippet recommendation interface, and a code related recommendation interface which are embedded within the standard search engine.
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Data collection methods on the web for
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Judit, B.-I. (2001). Data collection methods on the web for. Springer.
Guide to web scraping with PHP
  • Mathew
Mathew. (2010). Guide to web scraping with PHP. Marco Tabini & Associates, Inc.
Web Scrapping Using Python
  • R Mitchell
Mitchell, R. (2015). Web Scrapping Using Python, First Edition. Orilley.
Data scraping: How to leverage it for your eCommerce business?
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Samanta, J. (2021, 01 13). Data scraping: How to leverage it for your eCommerce business? Retrieved from towardsdatascience: https://towardsdatascience.com/datascraping-how-to-leverage-it-for-yourecommerce-business-7320e8f82358
01 13). what-is-ecommerce
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Shopify. (20121, 01 13). what-is-ecommerce. Retrieved from shopify: https://www.shopify.com/encyclopedia/ what-is-ecommerce