Over recent years, web scraping has become an incredibly popular practice, the rise of this field being largely attributed to the vast amounts of data that are produced and distributed every single day. To cut through that data, web scrapers – tools that comb through internet web pages, pull out certain information, and store it in accessible databases – have become the primary method for web data extraction.
With over 2.5 quintillion bytes of data being produced each day, a number that is continually growing at exponential rates, it would be impossible for a human user to rapidly pull information. Where human efficiency fails, computerized web scraping programs take over, being able to access pages, find the relevant information, and transport it to an Excel spreadsheet in a matter of milliseconds.
Considering the importance of data for businesses, with companies that rely on data-driven decision-making growing 27% faster per year and earning up to 23x more customers, it’s no wonder that web scraping is now found in practically every industry. If a business needs to rapidly find data to conduct analysis on, web scraping is going to be their go-to method.
Web scraping is found in every field, from eCommerce and aviation to real estate and banking. To get to grips with the most common uses of this incredibly useful data tool, we’ve collated five frequent uses of this technology. We’ll be covering:
- Dynamic Pricing
- Web Scraping in Combination with Natural Language Processing (NLP)
- Search Engine Optimization (SEO) Statistics
- Stocks and Average Pricing
- Lead Generation
Let’s get right into it.
Web Scraping: Dynamic Pricing and MAP Adherence
Within the United States, in order to ensure that different vendors have a level playing field when it comes to selling their products, brands must adhere to something known as the Minimum Advertised Price (MAP) policy. MAP dictates that brands cannot sell a product under a certain value, as this would upset the balance and lead to certain companies getting a huge percentage of the market for that particular product.
Typically, there are MAP policies set for the vast majority of different products, with manufacturers and brands having to follow these guidelines when advertising online. If a business was advertising and selling a product online that fell below the MAP, it could potentially be sued for doing so.
Alongside monitoring other companies to check if they’re breaking MAP laws, web scraping is also used to check competitor prices and adjust store prices to match or beat them. When using a web scraping tool, a company is able to compile a database of all the products a company is selling, and exactly how much they’re selling each product for.
If your business is a competitor that sells the same products, this information gained from a web scraper can help you decide what you should be charging. This is most commonly used in industries where consumers have lots of choices for the same service – like flights or hotel stays.
Within the flight industry, airlines will continually scrape the price of other companies, checking their flight costs and adjusting them to stay in line with the general average. This is also how flight checker tools like Google Flights or Skyscanner work, with web scraping collecting all the flight information into one location for consumers to compare.
Equally, hotels can check the prices that other similarly-sized hotels in their area are currently offering. With this, they’re able to position themselves as a competitive option, capturing as many travelers as they can by actively updating their prices.
Fluctuating prices within these industries are directly related to web scraping, with the ability to do pricing research being founded on this central data tool.
Web Scraping: Natural Language Processing
Natural Language Processing (NLP) is an application of corpus linguistics in which natural language and speech patterns are analyzed. This ever-evolving field mixes linguistics and computer science, allowing users to understand aspects of language like tone, subtly, humor, sarcasm, and general sentiment. While the vast majority of its applications fall into the world of academia, the past few years have seen the field of NLP come face to face with web scraping in the world of business.
As NLP can discover and analyze the sentiment behind a written comment, businesses have begun using it to determine how the public feels about a certain brand. For example, thousands of comments on social media can be collected using web scraping, with NLP then combing through them in order to analyze and comment upon user sentiment.
Leveraging NLP and web scraping turns social media from a thunder dome of endless comments into a tool that can accurately and frequently update you on how the public currently feels about your brand.
Equally, these tools, in tandem, can be turned towards reviews of a product, correlating certain ratings with specific phrases. For example, an eCommerce t-shirt selling company could use NLP and web scraping to discover that the vast majority of the time, anyone that gives the product 2 stars or below uses the words ‘cheap materials’ or ‘tight’ in their reviews.
From this, companies can work backward to effectively fix the problems with their products that are garnering these low reviews. Additionally, when using analysis on social media, brands can discover what is turning the public’s sentiment against them, and then work towards changing what brands don’t enjoy.
Web Scraping: Search Engine Optimization Statistics
Search Engine Optimization (SEO) is one of the most important factors to consider when launching any company’s public profile. Most commonly known by its acronym, SEO is the efforts of a company to move up the search engine rankings pages by creating content that Google can find, index, and vouch for as being great content.
There are many moving parts to SEO, but the main threat that people start with is keyword research. Keyword research for SEO is the act of collecting words or short phrases that are related to a business. When typed into Google, these keywords will return a range of different pages. A company that has focused on creating a great base of SEO for that specific keyword is much more likely to rank on the first page for that keyword.
Landing on the first page is vital for businesses, with over 90% of people never going past the first page of Google results. Quite simply, if your business isn’t ranking on the first page for the search terms that define what you do, then you’re going to struggle to get natural traffic.
Web scraping is integral to the processes that help businesses understand their own SEO strategy. Thinking back to keyword research, web scraping tools will pull information about the number of searches per month for that keyword, the main locations of those users, which devices are most common, how many other businesses are trying to rank for this keyword, the competitiveness score, and so on.
Equally, when comparing the online footprint of two businesses for SEO purposes, web scraping is used to detect how many backlinks a business has, where its pages are ranking, and further statistics that give a concrete level of analysis to something that was once thought of as fairly unknown.
Due to the power of web scraping, SEO has now become an accessible industry, with tools like Google Keyword Planner, Ahrefs, SEMrush, and SurferSEO all relying on this technology to provide information to their clients.
Web Scraping: Stocks and Average Pricing
The entire finance and banking industry relies on, in part, the daily efforts of web scraping programs. As a continually updating machine in which a few minutes can see the price dramatically alter, updating and pulling information from the stock exchange is one of the most common uses of web scraping.
By using web scraping tools, banks, and other financial institutions can analyze current movement within finance, uncover trends, monitor news that may have an impact on the stock exchange, and pull all this information into one easy-to-read application. From news data to direct stock market data, this has become vital for the billions of people around the globe that actively use the stock exchange.
Humans simply aren’t fast enough to conduct effective and instant analyses on thousands of different stocks, which is why they turn to web scraping tools. Bright Data, for example, can run millions of web scrapers at a time.
Without such web scraping tools, this industry would be far too slow at analysis, leading to huge inefficiencies. Combing through the stock exchange, lifting information about certain assets, and relaying it all back within seconds is vital in this fast-paced world. What’s more, this use of web scraping has become so commonly used that many forget its presence. For example, on every single iPhone, the Stocks application comes preloaded, yet serves as an example of an application that’s the whole function is based on web scraping.
Web Scraping: Lead Generation
The final use of web scraping that we’re going to discuss further exemplifies how convenient this tool makes for what would be tedious processes. The act of lead generation, finding new clients or potential investors for a product, service, or business, is wholly reliant on farming information on a mass scale.
When a business wants to conduct outreach, they can make a list of sources that they would target. Popular sources include Linked In, the Yellow Pages (when finding other businesses), as well the plethora of Google-connected resources, and any popular social media site. However, instead of having to comb through these sites themselves, looking for any post or mention that they could use to potentially strike up a sales conversation, they merely set up a web scraper to do the job for them.
In minutes, a web scraper can move through pages, pulling out names, locations, job titles, and specific needs of a person. With this information, a salesperson can reach out, using the information that the web scraper collected, to then launch a pitch. This streamlines a salesperson’s job, allowing them to focus more time on actually creating sales for their company and less time on endless lead generation research.
Considering that 61% of B2B marketers consider lead generation amongst their biggest challenges, it’s no wonder that the mass movement to web scraping for this function has already become popularized. Over time, this has become one of the leading uses of web scraping, and one can save huge amounts of time while streamlining company sales.
Over time, using a web scraper for lead generation can save a business time, boost sales, increase conversions, and help companies to shift into a new era of productivity.
The Many Use Cases for Web Scraping
Web scraping is an incredibly useful field of technology, which has become entrenched in a range of different areas of business. As the vast majority of industries need a continual flood of information in the works, web scrapers rise to the challenge, providing real-time information on demand.
While the five areas that we’ve discussed are frequent uses of web scraping, this is far from an exhaustive list. The reality is that web scraping has quickly become more mainstream, being adopted into a range of business models around the world.
In our modern age of continuous data, if you’re not capitalizing on the streams of available data, your business will be left behind. With web scraping tools available for practically any industry, this tech and the data it brings are now vital for success.
