Web scraping typically extracts large amounts of data from websites for a variety of uses such as price monitoring, enriching #machinelearning models, #financial #data aggregation, monitoring consumer sentiment, news tracking, etc. Browsers show data from a website. However, manually copy data from multiple sources for retrieval in a central place can be very tedious and time-consuming. Web scraping tools essentially automate this manual process. In this article List of Applications Where Web Scraping Plays a Massive Role
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
7. Real Estate
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 web scraping, 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’ 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 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.
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 Crawlingis 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 this, 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.
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.
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.
These are just a few examples of how web scraping is beneficial. There is so much more that it can do. If you are looking to make informed decisions, it is high time you consider web scraping.