Web scraping,” also called crawling or spidering, is the automated gathering of data from an online source usually from a website and Scraping is a great way to get massive amounts of data in relatively short timeframes.
Some of the typical applications of web scraping
Real estate investors often want to know about promising neighborhoods they can invest in. While there are multiple ways to get this data, web scraping travel marketplaces and hospitality brokerage websites offer valuable information. This includes information such as the highest-rated areas, amenities that typical buyers look for, locations that may be upcoming as attractive renting options, etc.,
Machine learning models need raw data to evolve and improve. Web scraping tools can scrape a large number of data points, text and images in a relatively short time. Machine learning is fueling today’s technological marvels such as driverless cars, space flight, image and speech recognition. However, these models need data to improve their accuracy and reliability.
Social Media Sentiment Analysis
The shelf life of social media posts is very little, however, when looked at collectively they show valuable trends. While most social media platforms have APIs that let 3rd party tools access their data, this may not always be sufficient. In such cases scraping these websites gives access to real-time information such as trending sentiments, phrases, topics, etc.
Many eCommerce sellers often have their products listed on multiple marketplaces. With scraping, they can monitor the pricing on multiple platforms and make a sale on the marketplace where the profit is higher.
Web Scraper Case Study - Gain a Competitive Edge
What gives your company a sustainable competitive advantage in the era of increasing digitalization, where several new technologies arise, where the walls that kept new entrants away are collapsing, where transaction as well as communication costs are decreasing, where computational power is almost available to everyoneand where more and more powerful algorithms are forged?
The answer is straightforward: data is the main factor that will determine whether you will be able to keep up with your competitors. The more data you have that your competitors cannot gain access to, the stronger the competitive advantage. One specific instance is the business problem of how to stay abreast of the competitors pricing strategy and product development so the you are able to stay one step ahead of your competitor and capture more market share.
Web scraping is the process of automating the data extraction from the World Wide Web in an efficient and fast way. This is at the heart of market research and business strategy, for instance when you want to compare the prices of your online store to the prices of the competitors regularly.
Depending on the strategy of your company, the goal of the web scraping and the complexity of the website to be scraped, different forms of web scraping might be preferable. If your business is working on a pricing strategy, web scraping could help you extract the pricings of your competitors.
Furthermore, you could track all moves of your competitors on the news, the development of the competitors as well as their discounts and pricings on a regular basis. If you need the customer ratings on platforms like Amazon or the product descriptions, then web scraping is also a valid option.
We have made a web scraping solution which uses AI and can be customized to any business needs. We have used latest technologies to create a web scraping framework which will let you scrape any website and get the product prices and product reviews for your business needs. These will serve your business needs to give you fodder for improving your product pricing strategy as well as improving your product mix based on customers reviews.
In the backend, you automate all the steps that you would usually do manually on your browser (for example type in the URL and then press enter, click on the first link in the navigation, copy the values from a certain area and paste them into an local excel sheet). The written script will then execute all your instructions by opening a browser and simulating each step as if a human was behind the steps. At the same time you can undergo several security measures because from the other side it will look like a normal human is accessing the homepage.
Web Scraper Case Study - Resume Screening
In any HR department engaged in recruiting people, the major problem is how to check which resumes are relevant for the position being filled. The HR people cannot rely on traditional approach to manually review each resume for relevant portions or relevant keywords to pass it to the potential interviewers. First challenge is to collect all the resumes from the company’s website and then to manually review those resumes. These twin problems of retrieval and review needs an technology based automated approach.
There are two parts to the problem of HR being not able to cope up with the large no. of resumes received for any position now a days. First part is to retrieve all the resumes from the company’s website and the second part is to parse all the resumes to choose the relevant ones.
Traditionally, the HR department has been using the manual review approach to do the sifting of resumes to separate out the relevant ones. This approach may lead to some relevant resumes being left out on account of the HR executive not being able to read properly or read all the resume content. This may have a lasting effect on the quality of people recruited ultimately leading to affecting the business efficiency.
The problem of resume parsing is a big one and any HR professionals will tell you how much it vexes them. One solution is to have a technological automated tool which can download the resumes from company’s website and sift through the resumes to separate out the relevant words based on some keywords or some key content. Web Scraper along with features to parse text of each document and search for relevant keywords can be the solution.
We have designed a web scraper tool which combines the ability to download pdf or docx documents from a website link with the ability to parse the documents downloaded to separate out certain documents having certain keywords.
You can put the website link into the tool and put relevant keywords which you want searched in the documents. This tool will download all the resumes whether in pdf or docx forms and parse each resume to search for the relevant keywords entered by you in the tool.
The tool will output those resumes which match the relevant keywords pertaining to the role description of the position candidates have applied for.