Have Scraper Bots Outstayed Their Welcome on Real Estate Listing Sites?
Alex McConnell, Cybersecurity Content Specialist
3 minutes read
Real estate is just one of many industries that was forced to quickly adapt to an increasingly online-first world in the wake of the COVID-19 pandemic. Virtual viewings are now the norm, and real estate businesses are scrambling to keep up with how their competitors have changed approach.
When looking for a property to buy or rent, we are now likely to search online and look through online listings in the first instance. Real estate listing websites aggregate properties from various sources, saving time and effort for buyers and renters.
Bots are shaking the foundations of the real estate industry
Real estate listing websites want to make their listings as accessible to visitors as possible. The information needs to be easy to find, clear and descriptive. Realtors invest time, effort and money into producing creative, enticing listings to post online in a very competitive, often commission-based sales environment.
Unfortunately, bots (non-human web traffic programmed to undertake specific tasks) are risking the profitability of these carefully crafted property listings. The most common bot type in real estate is scraper bots.
What is a real estate scraping bot and how does it work?
Real estate scraper bots work in much the same way as any other scraper bot. Although not all web scrapers are unwanted or necessarily bad, malicious web scraping is a common attack seen by the travel, media, retail, and gambling industries, among others.
In the case of real estate sites, firstly the bot operator decides what information they wish to scrape; this could be data such as prices, property size, location, and any other basic details about the property for sale or rent. Content such as images and videos are valuable assets, and thus also typical targets.
Bots are programmed to scrape the pages of the site to rapidly gather all this information. As real estate listings are frequently added and updated, bots are aggressive in how often they scrape their targets, looking to always keep their own database up to date.
Why do we need to stop bots targeting real estate listing websites?
Scraping activity can be detrimental to real estate websites for two main reasons.
Firstly, scrapers can be used to steal listings, almost like putting another “for sale” sign up in front of the original. Listing theft is particularly damaging when a site is listing unique properties or has a high profile, as all the hard work in compiling the listing can be quickly duplicated on other marketplaces, snatching away views and potential sales. SEO also can be damaged by duplicate content appearing elsewhere, hurting organic search rankings and further reducing the chance of closing the sale.
Secondly, aggressive bot activity puts pressure on web infrastructure. Scraper bots can account for as much as 60-70% of all web traffic during a spike in activity. Not only can this slow down the website’s performance for legitimate visitors but serving these unwanted requests costs significant amounts of money.
How you can protect your real estate site against malicious bots
The benefit of identifying and blocking these scraper bots is not only protecting listings from theft, but also customers from poor user experience and your tech team from the woes of costly infrastructure.
Many web service providers have products aiming to block such traffic, such as WAFs or IP range blocking tools.
However, bots use sophisticated means to avoid detection, sometimes emulating human behavior to bypass defenses or generating their requests from multiple IP addresses to avoid attracting attention.
Advanced bot detection with Netacea Bot Management
Netacea Bot Management uses Intent Analytics™ to examine not just the origin of each request, but also its behavior and objective. Using highly tuned machine learning techniques and several patented technologies, Netacea accurately detects malicious scraper bots in real time, mitigating the risk to businesses.
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