There was a time when data was not such a big deal. Fortunately or unfortunately, that time is gone. Companies and businesses now require an enormous amount of data every day to stay successful and compete fairly in the global market.
However, gathering such an amount of data is not an easy task and a brand that needs to collect a sufficient amount of useful data every day must also invest a vast amount of time and effort. Such demands and the increasing relevance of data have prompted the discovery of several data extraction methods and tools.
A process that once involved traditional methods has now evolved to include Artificial Intelligence (AI). AI web scraping is becoming a more popular phenomenon because tools built with AI can gather data at even greater scales, making web scraping a more interesting and efficient process.
What Is Web Scraping?
Web scraping can be defined as the process of accessing and retrieving large quantities of data from multiple data sources. It generally involves the use of sophisticated tools to find and extract useful data in real-time. The data can be sourced from search engines, servers, websites, and even key marketplaces, and the process is usually repeated or kept in a loop to allow for routine updates of the extracted data.
Once gathering is complete, the data can then be easily retrieved whenever needed and promptly used.
The software or tool you choose to use can be installed on your device or deployed and used directly from the cloud.
Alternatively, you may choose to have a custom software built especially for you. This has the advantage of meeting your company’s needs head-on. However, it can also be more costly to develop and maintain.
How Does It Work?
Although both the traditional and AI web scraping now work in very different ways, web scraping or data extraction generally works in this simplified manner:
- You provide the scraping bot with the URL address of the website or server you intend to scrape
- The request is sent out using a proxy that conceals your information and delivers your request discreetly
- The request reaches the target site and, the scraping bot proceeds to scrape information and create an archive following all embedded links
- Once enough information has been gathered, the results are returned to you via the proxy, which checks to ensure the data has not been compromised
- Once this checking is complete, the results are displayed to you and, you may now proceed to store them in any available storage medium
What Web Scraping Can Be Used For
The main purpose of web scraping is to collect a sufficient amount of relevant data. This data can then be applied in several ways, including the following:
1. Brand Monitoring and Protection
Brand monitoring and protection entails the various processes used in safeguarding a brand and all of its assets. The process spans from observing the corners of the internet to see where your brand is being mentioned to taking the necessary action against imposters and infringers.
Doing all these usually involves collecting data frequently and consistently through web scraping.
2. Market and Competition Monitoring
Knowing how the market is behaving at every point and understanding what your competitors are doing is a strategy that can either break or make a business. It is believed that brands that keep a close watch over these two entities tend to do better than those that ignore them.
Hence, brands take very seriously observing both the market and their competition. And the data they need to do this is usually gotten via web scraping.
3. Customer Satisfaction
In today’s world, “the customer is always right.” This implies that what the customer feels and thinks must be considered very important. Delivering customer satisfaction is key to succeeding as a digital brand; hence businesses need to understand their customers’ thoughts at each turn. This can be achieved by gathering data about customer reviews and discussions.
4. Creating Informed Strategies
Businesses also strive through strategies. A strategy such as dynamic pricing helps brands maximize profit and revenue. But strategies cannot be built blindly and must be done with concrete information. Creating an informed strategy requires a large amount of data collected in real-time.
Artificial Intelligence and How It Can Change Web Scraping
AI can be defined as the capacity of a machine, computer, tool, or software to learn something during regular operations. This means that tools built with AI can easily learn and adapt as they go. This is essentially the job of AI.
The concept of AI covers everything from AI applications to Machine Learning (ML) algorithms and Deep Learning, with all of them working in a way and manner that mimics human intelligence. AI has been successfully used to assure quality data in several fields, including medical diagnosis, remote sensing, and web scraping. To learn more about AI-empowered web scraping, visit the Oxylabs page.
The application of AI in web scraping will revolutionize things in several ways, including the following:
- Building more sophisticated scrapers that can scrape data from virtually all websites despite the differences and regular changes
- For proxy management and infrastructural maintenance with fewer possibilities for error
- For proper data fetching and more reliable data parsing as the AI tools can easily adapt to perform such tasks more reliably
Web scraping is an important business requirement and. AI scraping is even better because it eradicates the time consumption, difficulty, constant maintenance, delays, and errors associated with traditional web scraping.