Search engine scraping is a fairly new practice that emerged from web scraping, a young discipline by itself. Web scraping is basically the practice of acquiring large amounts of data from many different websites in an automated manner. Data extraction scripts run headless or headful browsers to go to specific URLs and download the source code which holds all the data that exists in that page.
Search engine scrapers work in a very similar manner as web scraping scripts. Except they generally accept more input from users as search engines rely on user queries to display content. But why use such a tool at all?
Scraping SERPs for fun and profit
Getting large amounts of data from search engine result pages can have a wide variety of uses. From any type of personal or academic research to creating SEO tools that can predict rankings and offer suggestions to improve website performance. The only real limitation is imagination as search engines such as Google are the backbone of the modern internet.
Large businesses use a Google scraper for many reasons. In-house marketing teams can generate a lot more insights than their competitors if they have access to data unavailable to others. They can monitor specific keywords, trends, and changes in rankings in order to be one step ahead of everyone else and keep their prized positions in search engine result pages. Enterprise-sized businesses also use Google scrapers for piracy and counterfeit protection. They can monitor search engine result pages for any malicious entities attempting to create counterfeits of popular products and sell them as the originals.
Even smaller businesses are beginning to utilize SERP scrapers for their own goals. A common use case for a smaller business is to scrape Google results for product reviews. They can then collect a significantly greater amount of product and service reviews than with any other method and adapt accordingly. Simply put, businesses can get a lot more actionable information than ever before by just having a data analysis team.
What does it take to build a SERP scraper?
As SERP scraping is a rather new process, there aren’t many guides out there. Yet, since it’s basically just a sister of web scraping, a lot of the knowledge acquired in that field can be reused to build a SERP scraper.
Web scraping tools go through several basic steps. First, an application that imitates browser activity (or uses an automated browser) is created. A common language used for web scraping is Python as it already has many libraries that make the process significantly easier. These applications then require a list of URLs or at least one primary one as the process of collecting new URLs can be automated. Finally, the page sources from URLs are downloaded and stored.
These page sources are then often parsed to make the information more digestible. A team of data analysts or automated programs create insights from the acquired information.
Yet, building a good SERP scraper is a lot more difficult than it may seem. It’s not just an automated application that goes to URLs and downloads data. As websites do not like bots running on their servers, they often employ anti-bot measures. These can include many things – from delivering CAPTCHAs, to displaying incorrect content to detected bots to simple IP bans. Good Google scrapers need to find ways to avoid all of these.
There are many strategies to sidestep anti-bot measures but the primary one is using proxies. Proxies allow scrapers to change their IP address and rerun the operations as if they were a completely new user. This allows them to reset any information the website might have acquired on their activities.
The difficulties in building a SERP scraper don’t end here. These scripts are often quite fragile and even small layout or design changes can completely break them. They are definitely not a “build-and-forget” type of application. A constant team of developers have to build improvements, monitor activities, and create new workarounds for anti-bot tactics. Then they have to ensure that proxies work consistently, ensure their acquisition and many other aspects.
Building a SERP scraper is definitely a great task. A team of dedicated developers and product owners is required to create a good scraper. It’s definitely worth it for those that have the resources. For those that don’t, is it worth buying one?
Buying a SERP Scraper
There are many services that sell scrapers (e.g. SERPMaster) for business use. Buying a SERP scraper is a lot lighter on resources than developing one and requires much less management and investment into the project.
For example, most SERP scrapers provide an all-in-one-package. Users just send the required requests to an endpoint and the service scrapes, parses, and delivers the data in a timely manner. These businesses take care of everything except data analysis – they manage the proxies, updates, and update their scraper in order to avoid having it break down.
Usually, a little development experience is required as SERP scrapers often come without a GUI and require integration through programming languages (anything from PHP to Node.js to Python). Fortunately, these setups often come with step-by-step guides and the integration is only needed to do once.
Therefore, there are many benefits that come with buying a SERP scraper rather than building one. It’s a much simpler choice for any business with the only caveat being making the correct choice of provider.
Building a SERP scraper definitely has a lot of benefits, especially for larger businesses. Since they get full control over the entire process and are able to customize the scraper to their liking. Yet, developing such a tool takes a considerable amount of time, effort, and resources. Without a dedicated team of developers to create and maintain a SERP scraper, the tool is unlikely to become useful at scale.
Therefore, smaller businesses are recommended to find a good provider and simply buy access to SERP scraping. The process is a lot simpler, cheaper, and quicker. Finding a good provider means looking for a few things – price, reliability, and ease of integration.