If you’re involved in online business, you know the priceless value of data. The internet is a bountiful source of information, but how do you find the right data quickly and efficiently? And how do you process it so that it becomes useful? The key concepts around data gathering are crawling, web scraping, and parsing. Let’s find out how they differ. Crawling Crawling refers to the large-scale browsing of websites. A crawler navigates to pages, finds URLs in hyperlinks of those pages, copies them to a browser, and repeats the sequence. Web crawling is what search engines such as Google, Yahoo, and Bing do. It’s a process designed to capture generic information for indexing and ranking purposes. You’ll usually combine crawling and scraping when gathering data online. First, you’ll use a web crawler to discover relevant URLs and download HTML files. Then, you’ll scrape your data from those files and process it for practical use. While the terms crawling and web scraping are often used interchangeably, there are some key differences. Web Scraping This concept refers to the automated gathering of data from publicly-available sources. Web scraping is a much more targeted process than crawling and is most commonly used for marketing and research purposes. Businesses are increasingly using no-code web scraping tools to find relevant data for reasons like: Businesses can acquire valuable information by scraping websites commonly frequented by their customer demographic. For example, Quora and Reddit host lively discussions about a wide variety of topics. Gaining access to this data helps to identify trends and understand customer needs and expectations. Market research: Keeping tabs on competitors allows businesses to put their performance into perspective. Things like competitor prices, user reviews, and product releases are useful for comparison. Competitor analysis: Social media sites such as Facebook and LinkedIn are excellent places to scrape data on potential customers and employees. Not only can businesses extract relevant data and contact details, but they can also reach out directly to potential leads based on what they’ve found. Lead generation: While web scraping is incredibly beneficial, there are some challenges. Certain sites forbid web scraping to protect their data. To determine whether a site allows scraping, check its “robots.txt” file by typing “robots.txt” after the URL. Other sites install IP blocks to stop high numbers of requests from the same device. In this case, you can either use a reliable proxy service, build your own scraping tool, or try an alternative site with similar information. After crawling and scraping your data, it’s time to make sense of it. This is where parsing comes in. Parsing Gathering vast amounts of raw data is only useful if you know how to process it effectively. Parsing transforms unstructured data into understandable information which you can use to gain actionable insights. Efficient parsing requires a good data parser, software that converts input data like raw HTML into a readable format like a CSV file, chart, or table. Using a parser rather than manually processing scraped data will save you time and money. It’ll also provide you with more accurate databases free of human error. The best solution is to find a tool that combines web scraping and parsing. That way, you’ll locate your selected targets, gather the information you’re looking for, and have it seamlessly exported into a readable format of your choice. Final Thoughts Gathering and processing data for marketing, brand protection, and research purposes has become a crucial strategy for many businesses. Knowing the differences between these key concepts will help you to understand which one applies to your use case.

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