Data or web scraping is a software technique designed to extract information from the World Wide Web. This method locates and collects targeted, usually unstructured data stored in HTML and transforms it into a manageable form. Data scraping simplifies the process of acquiring information at the scale and allows you to take only what you need, without spending hours on checking each web page manually.
If you know how to code, you can try scraping tools that require your involvement as a software user in the process (ad-hoc solutions), or proceed with fully automated scraping to get the content and type of data you need. In that case, a bot (web crawler) does all the work for you. The ever-imaginative internet offers open source projects to help you with data scraping, and some developers even provide web scraping as a service. From Google Chrome extension to various applications, data scraping tools will be of use in any field, as comprehensive data collection is required in all kinds of research. In the world where new products and services pop out every week, the necessity to be up-to-date with the Big Data becomes as urgent as ever, and web scraping advances your research in three crucial ways: it covers as much information as possible, does it quickly and hands it to you in an organized format. Let’s see how that works in industries that arguably depend on fast positioning more than others.
Competition is easy nowhere, but the retailing industry faces a lightning quick change of trends in addition to common challenges of business. For that reason, data scraping is the solution for research in retail first and foremost thanks to the speed it ensures. We can boil directions of retail research down to two main points: customers and competitors. It’s vital for any retailing business, including online stores, to know what their current and potential customers want to buy and how much they are ready to pay for it, what they already bought for what cost and if they are satisfied with the purchase.
For instance, scraping data from social networks and blogs can give you a clear understanding of customers’ preferences. Feedback will be as welcome, and you’ll be able to see if a new type of product or service is actually successful and deserves investment before you join in the trend. Armed with that knowledge, you’ll find decision-making much easier.
Of course, your research won’t be comprehensive if you don’t bring together studying customers and crawling your competitors’ websites. The data and statistics on promotions, prices and customer service they provide are a crucial part in developing the best strategy for your business. When it comes to price comparison, you ought to be informed on how much your competitors charge for the same product that you sell, so you can adjust your pricing policy to attract buyers and avoid demanding more from shoppers that they can or are willing to give. Scraping competitive websites (if they have a comment section, the better for you), blogs and social networks will let you know what your competitors charge and if their customers believe it to be a fair bargain. Once you know that, you can not only include that vital information into your strategy but also organize your sales schedule to attract the highest possible number of shoppers.
By the way, sales are such an integral part of commerce that the mere fact a store doesn’t have them is often enough to disappoint buyers and make them seek a more customer-oriented retailer. But how often is enough? You won’t know that until you get to data scraping and form a complete picture of current offers on the market and clients’ response to them.
Popular social networks, blogs, and news sites are the sources of valuable data on your reputation too. You need to know whether people recognize your brand. Recommendations and warnings, fake bad reviews, poll results – all that information is out there, and you can get it in a quick, effective manner with the help of web crawlers.
Keeping up with market trends plays a significant part in tourism as well. Travel agencies need detailed information on every destination, and covering multiple types of accommodation or ticket prices is tedious work.
Scraping tour agents’ sites, travel sites and blogs is the path to a reliable collection of data on which destinations are more or less popular, which kind of transportation customers prefer and what tour package would be successful this season. Let’s not forget about weather monitoring too. It can make a great effect on your agency’s program as you’ll be able to withdraw certain tours, if necessary, in time and replace them with destinations that won’t spoil vacation for your clients with the risk of hurricane or earthquake.
Another use for data scraping, which isn’t specific for travel industry but is often the core of tours, is targeted research. We’ve all heard of eco tours, family tours, relax tours and dozens of other variations that aim to attract a particular group of customers. Web crawlers are great in targeted research, allowing you to study the market and the feedback as well as pricing strategies across the globe.
Journalism is a data-driven industry. You could be doing research on school food quality or animal rights protection, or trying to unfold the truth about corruption among tax inspectors. Regardless of the topic, any journalist meets the same obstacle – trouble with access to information.
Perhaps, research of that kind hasn’t been done before so you have to collect all necessary data by yourself, or the existing researches don’t satisfy the scope or direction of your research and thus cannot be a base for your story. Oftentimes people just don’t want to share sensitive information with you. That obstacle is particularly evident in investigative journalism.
Data scraping will help you get information even from the sources that don’t allow copying and downloading, and the more serious the matter, the more data you might need to scrape, for example, criminal records or information on results of official investigations. The growing influence of web crawling even produced such branch as data journalism. That is both a new source of data, already structured and analyzed and a proof of the efficiency of data scraping.