In a world where decisions are powered by data, access to data becomes critical. At QL2, we strive to turn data into information, knowledge, and ultimately wisdom for e-commerce companies to base pricing decisions on. But it all starts with the ability to acquire data in a consistent, efficient manner.
The data acquisition space has evolved significantly over the last five years. Some of this evolution has been very positive for acquiring data, but some changes have made data acquisition very, very difficult.
I’ll start with the legal environment. This remains squarely on the side of data acquisition. Cases such as LinkedIn v. hiQ and the United States v. Van Buren continue to move in a direction favorable to data acquisition, setting precedents for the industry by which to work. With LinkedIn v. hiQ headed back to the 9th Circuit Court, we should expect even more clarity in the coming years.
The bad news is that even though data acquisition is winning the legal battles, the amount of investment in anti-bot technology continues to rise. One source claims that there has been over $21 billion invested in the Cybersecurity space last year alone (source: Crunchbase). That is a tremendous amount of investment to fight against. They are quickly moving past IP and header fingerprinting, and now seem focused on complex browser fingerprinting and mouse movements.
The good news is that the number of useful libraries available for data acquisition continues to grow. Python is still at the forefront of data acquisition frameworks. BeautifulSoup and Scrapy have become very popular amongst developers. Headless browser solutions, such as Puppeteer and Playwright, have aided significantly in deeper data acquisition.
Overall, the future is bright for the flow of critical data so that companies can make fast, effective business decisions. However, the hard work of acquiring data will not be going away any time soon.
Written by: Carl Wartzack, CEO