List of Applications Where Web Scraping Plays a Massive Role
What Is Web
Scraping?
Web scraping
is the process of extracting and storing data into your local machine. You can
extract any amount of data from a website and store it in your system at ease.
You can export them as a CSV file which gives you the flexibility to transpose
and drill down the data the way you want.
List of
Applications Where Web Scraping Plays a Massive Role
1. Retail
and Manufacturing
2. Financial
Research
3. Data
Science
4. Marketing
and Sales
5. Academic
6.
Journalism
7. Data the
Differentiator
1. Retail
and Manufacturing
A. Price
Monitoring
Pricing
plays a key role in selling your product. You need to be aware of how much your
competitor charges for their product. Even a small difference in the price can
cause you to miss a lot of customers. Therefore you must keep track of your
competitor’s pricing.
Here is an
example: Let’s say you are selling a particular brand of jeans. You analyze
your profits, check competitor sites and then set the price of it as $100. A
few days later, you notice that your competitors have reduced the price of the
same jeans to $95. For you to sell consistently, you will have to re-price the
product. How do you know when your competitors are revising their prices?
Tracking the
pricing manually can be a tedious and excruciating task. With prices changing
often, it is a lot of work to manually check for updates. This is where you
need to take the help of web scraping.
With webscraping, the prices can be automatically extracted from your competitors’
websites. This allows you to deploy new strategies to sell your product.
B.
Monitoring Minimum Advertised Price (Map) Compliance
Minimum Advertised
Price (MAP) is a de facto method for manufacturers to check their retail
partners. With thousands of resellers in the market, the price changes every
day. These manufacturers can only keep an eye on the small number of retailers.
But every manufacturer would want to monitor retailers to see if they comply
with their minimum price.
How do they
do it? There are so many resellers and so many of their products out there.
With Web
Scraping, they can quickly extract humongous information at the fraction of a
second.
C. Product
Descriptions
In case you
are running a B2B site that sells a suite of products, you will be flooded with
the need to write perfect product descriptions that would match your product.
This is extremely important as this is going to be the face that is going to
sell to the customers. Customers will rely on the information mentioned in the
description and decide if they need the product or not.
How do you
get this information? Writing it manually and verifying it is one option. Web
Scraping is another. The manufacturer is not going to just rely on your site to
see his/her product.
You can make the entire process easy if you know which site to look for. Within
seconds, using web scraping you can get the product description and images.
D.
Monitoring Consumer Feedback
What is the first thing that you look for when you want to buy something online? Customer
Feedback. This feedback can be for the same product as mentioned earlier. It
can be spanned across multiple sites.
Let us say,
you have design software that you sell on Amazon, Flipkart, Snap deal and
various other sites. Now you want to curate all the reviews and publish on your site. How do you go about doing that? With web scraping, you
can curate all the customer reviews from different sites. You can also download
it in a spreadsheet and even compare the ratings.
2. Financial
Research
A. Aggregate
News Articles
When it
comes to financing, the primary source of any insight is news. There is ‘N’ a number of news channels available online that telecast day to day information.
Going online and reading every news to find out the day to day activities is
impossible. Even before you assimilate the information, the news would be too
old to consume.
With Web
Scraping, you can easily convert the news to actionable items by
extracting the information you need using keywords.
B. Market
Data Aggregation
Market data
is trade-related information that encompasses a lot of vital information such
as price, quotes, and volume. It is used to report assets distributed across
traders.
Data is
spanned across global markets, stocks and forex. This information is extremely
beneficial in planning the trade, calculating market risk and other impacts
across trading. Market data is a lot of information that is available across
the internet. Web Scraping enables you to slice the data you need by scraping
them from across different sites.
C.
Extracting Financial Statement
Financial
statement determines the health of the company and helps investors decide if it
is worth investing in the company. These statements are audited by the
government agencies to ensure accuracy and for financing, tax, and other
investing purposes.
That said,
it is near to impossible to get financial statements manually from different
companies for different years. Web Scraping
helps in extracting this information and paves way for future analysis.
D. Insurance
Insurance
companies have to frame their terms and conditions carefully to avoid
sanctioning wrong claims. This can be done only by studying the history of
claims and those processed not only by their company but also by their
competitors. Leveraging this amount of historical data is not possible
manually. Even if one has to do so, they will spend more time acquiring this
information rather than understanding them.
Web Scraping
reduces this load on them by getting all the information that they might need
to take calculated and informative decisions.
3. Data
Science
A. Real-Time
Analytics
Real-time is
analyzing the data as soon as it is available on the internet. Users can
rapidly analyze the trend, get insights and draw conclusions in a matter of
seconds. This allows companies to make informed decisions without any delay
enabling them to seize opportunities immediately.
This is
different from the batch style technique where data analysis might take hours
or even days sometimes. For instance, the batch analysis will give you
information on traffic trends in a particular place, traffic hotspot, etc. The Real-time analysis gives you information
on the current traffic so that you can avoid that route.
Financial
organizations rely on this data to take important credit scoring decisions such
as continuing or discontinuing it. For real-time analytics to work hassle-free,
data must be collected in large quantities as quickly as possible. Web Scraping
saves the day when you need something to be extracted and processed quickly.
B.
Predictive Analysis
Predictive
analytics is nothing but the use of historical data to identify future
outcomes. It allows the user to go beyond what happened in the past and predict
what will happen in the future. It, however, cannot accurately forecast the
future but can provide a wide list of possibilities.
It is used
to study customer behavior, and understand the life cycle of similar products
that were released in the past. It is widely used to detect fraud, optimize
market campaigns, improve operations and reduce risk.
Just by the
definition, one can understand the amount of data needed to make this analysis.
Web Scraping is the key to collect such an amount of data easily.
C. Natural
Language Processing
NLP is a technique used to make computers understand human languages. This can have a
long way in the future as computers will be able to interpret human say. One
might no longer have to feed instructions into the system. All that they have
to do is ask the computer to do something and it will be made available.
To perform
These machines will need a lot of information. They need to understand the
different words, contexts in which they are used, slang, etc. They will all and
any data
related to how humans interact and the best way to find that is using social
media.
Web scraping
is one of the many ways to scrape data from social media in a re-usable format.
D. Machine
Learning
Machine
learning
allows the machines to learn and improve on their own without coding. It is an
advanced branch of Artificial intelligence where data is fed into the system
and they learn from it. This can be achieved only if there is enough data for
the model. Web scraping helps in collecting this data making this artificial
advancement possible.
E. Risk
Management
Risks and
business go hand in hand. There are various risks involved in a business, right
from hiring a resource to landing a client. But, What if there is an option to
calculate risk and take careful decisions?
Web Scraping
gives you a way to eliminate these risks. You can leverage it to do a
background check on your customers or employees. You can get end to end
information that is available on the internet about them.
4. Marketing
and Sales
A.
Data-Driven Marketing
When it
comes down to marketing your data in today’s scenario, data plays a key role.
The data you have is what categorizes the success or failure of your campaign.
B. Content
Marketing
Web Scraping
is all about content extraction. It paves a way to extract all the data you
need and compile an engaging content to grow your business.
C. Lead
Generation
Spending a lot of money on outbound leads can burn a hole in your pocket. With web
scraping, you can harness this data directly from the source to generate leads.
This reduces the budget planned for generating leads and
helps in using that resource for other marketing activities.
5. Academic
One can only
imagine the amount of information that will be needed for the Academic
industry. No matter what it is, teaching, research, academics will need a lot
of data and statistics to prove a point. Web Scraping has made this process
easier and simpler.
6. Journalism
Journalism
is all about bolstering new stories. For this, you might need to look upon
historical information for reference. Similar stories and how they have been
handled will help you draft the content that will not only engage but also
enable your readers to understand the complexity involved and how it is
handled.
7. Real
Estate
Investing
your money in properties can be an emotionally driven decision. But where to
invest should be made on empirical data. This involves a lot of time and
understanding. There would be various questions that need to be answered – Who
am I buying this for? Who is going to use this property? Is this going to yield
the rental that I need? These are the answers that can be obtained using web
scraping.
You can
acquire any type of information that you need using web scraping.
Right from the price of similar property, Monthly rental, popular streets, size
of the property, parking space of that property and those provided by similar
properties, the number of views the property has, Is it semi-furnished or fully
furnished, etc.
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