Web scraping has been a known concept and practice for a while now, and while it has changed the way businesses accumulate information, there’s still a lot of room for improvement. Artificial intelligence and machine learning are two technologies that have been buzzing around for a long while and have just recently reached new heights.
Today, a lot of the world is automated through the use of artificial intelligence. Processes that used to take a lot of time, money, and effort are now streamlined and simplified.
AI has found its way into more than a couple of technologies and practices, one of which is web scraping. In this article, we’ll explore web scraping, why it’s suitable for companies, and define how through the use of AI, the whole technology can face a second renaissance, thus improving substantially.
What is web scraping?
Web scraping is the process of collecting information from the internet through the use of a scraper bot. This practice is also known as data harvesting. It’s done by deploying a web spider and aiming it at data sources such as websites or particular queries.
After a web spider is deployed, it will roam the internet collecting relevant information and data. This data can later be refined into viable data used for anything from corporate research to marketing.
Think of web scraping as the process of extracting data from websites. The data can be easy to abscess by a regular user or locked behind a proxy or firewall. Companies and individuals can collect vast amounts of data from other websites through the use of data harvesters, allowing them to build their immense databases.
Data harvesting is the premier way to gain access to structured web data in a simple, streamlined, and, most importantly, automated manner.
Why do companies use scraping?
Businesses are always looking to gain an edge over their competitors, and in this day and age, there’s more competition than you can imagine. We live in the age of startups, and all those companies, no matter how big or small, are competing with each other for their fair slice of the market.
As always, information is power, but the way that we access information has changed drastically. No longer do we have to hire people to collect, assess, and compartmentalize data, as solutions such as data harvesting do that for us. Businesses use data harvesting for a multitude of reasons, the most popular of which are:
- Creating in house databases
- Accumulating consumer data
- Monitoring competition
- Generating leads and marketing
- Service optimization
- Product development
Aside from these, there are many, many more business-specific reasons why particular corporations use data harvesters.
Sadly, data harvesting isn’t nearly as sophisticated enough to always give us the best possible data at the smallest amount of time. While data harvesting bots can be pretty sophisticated, the data they collect will have to pass through an intricate and intensive refinement process before it turns from raw data into something businesses can use.
That doesn’t necessarily mean that the future of web scraping relies solely on programming, as artificial intelligence promises to help scraper bots become more sophisticated than ever.
Through the use of AI, scraper bots can learn from their web scraping on an individual level, so companies can have a unique piece of software that knows what they want, how they want it, and when they want it.
How AI improves scraping?
Next-generation web scraping bots are going to use machine learning and artificial intelligence solutions to improve their operation. Through the use of machine learning, web scraping can contribute even more to the business intelligence of companies all across the globe.
Faster scraping, more accurate data, and built-in analytics tools are all the features that AI web scraping brings to the table, and that’s not all.
AI web scraping could finally allow smaller businesses that can’t afford to develop their spider bots the chance to get in on the web scraping action, allowing them to contribute massively to their database without having to break the budget. Another example, Oxylabs has launched Next-Gen Residential Proxies in order to give their users complete peace of mind and smooth scraping without getting blocked. In such cases, clients can focus more on data analysis rather than its collection.
The web scraping bots of tomorrow are all going to be far more sophisticated, better equipped to deal with business-specific requirements, and most importantly, far more affordable.
The AI revolution has just started, and it has already found its way into more than a few technologies, practices, and processes. Data harvesting has proven to be one of the essential tools in any company’s business intelligence arsenal because it provides a way to automatically collect vast amounts of data, saving money, effort, and time.
Through the use of AI web scraping, companies can gain an edge on their competition, spend a lot less money doing so, and can have far more sophisticated data-gathering projects.