Property hunting has become a lot easier nowadays with the omnipresence of real estate listing portals which cut down the tedious task of finding a good broker or agency. Not only has this boosted the real estate market but is also helping investors and individuals looking for their perfect home.
Real estate listing sites like Zoopla.co.uk have hundreds of thousands of listings on any given day and this huge number of available choices can be intimidating for anyone looking for the best property deals. An easy solution and hack to make your property hunt all the more easier and efficient is to incorporate web crawling techniques.
Michael Doyle, who works as analytics manager at a betting company has been in the real estate market for more than 18 months before he decided to make use of web crawling to find the best deal on his first home.
He had a budget of €650,000 for the property and the real estate portals he was using had about 27,000 listings across the nation. He then went on to create a simple formula that takes into account the cost per square metre, price, noise pollution, proximity to schools, quality bus-corridors etc., to spot the best deals from the lot.
Doyle’s simple web scraping project to find the best property in Ireland was a small glimpse of what the web crawling assisted real estate property hunting is truly capable of.
Let’s look at how the whole process would work if you are looking to find the best property deals in any given location given that there is an online real estate portal with adequate listings that allows web crawling.
Web scraping for real estate
Real estate portals are websites where users directly post their properties for sale with a listing price along with the other details of the property. To export all these listings available on a real estate portal, manual methods fall short of efficiency. This is where web scraping comes in the picture. With the help of an automated web crawler, it’s possible to extract all the property listings under any given geography where you are looking for the property. Here are some of the data points typically found on real estate listing pages.
- Posting date
- Address of the property
- Zip code
- Property description
- Number of rooms
- Year built
- Parking spaces
With a dedicated web scraping service, the data extracted will be in a clean and structured format and ready for analyses. The crawls can be run on a daily basis to fetch and include the newly added listings. The scraping activity can be run on more than one real estate portal to get better results from the property hunt. Adding more source sites is always a good web scraping practice which improves the overall results.
Analyzing real estate data to discover the best deals
With the real estate listing data at your disposal, it’s up to you to decide how you want to analyze it. If you are an investor or property dealer looking to buy properties to sell, you can use market value as the key factor for your property hunt.
You can define the best property as the one with the best market value. Once clean data get delivered, a simple calculation can be done to look for the property that offers the best price and ticks all the essential or required facilities.
These are the facilities you can factor in:
- The popularity of the location
- Distance to important landmarks
- Number of rooms
- Flooring type
- Other amenities
Once you have defined the key points to be considered, the mathematical formula can be used to find a match. To add a human layer, you can have the system find the best 10 listings and then manually evaluate each one to decide which one best suits your requirement. This approach is best suited for people who are looking at real estate as an investment for profit. You can easily find the best deals in any location by analyzing the real estate listings data and thus make perfect investment decisions that are sure to give great returns.
If you are not into investing in real estate and are looking to find your perfect home, you can follow a very similar methodology to achieve this. The only difference here would be that you have to give more weightage to the things you care about rather than the market value of the property. For example, instead of looking for a property which is close to a popular landmark, you could instead look for the property which is closest to your workplace, has a friendly neighborhood, proximity to a hospital etc.
Irrespective of your use case, web crawling can help you extract large amount of real estate listings from property listing sites which you can creatively use to get an edge in your investment decisions or find your first home.
A dedicated web scraping service provider like PromptCloud can be of great help to get clean data from the web in an automated manner. Of course, further processing of the data needs to be done via analytical techniques. Essentially, web scraping in conjunction with data analysis can take your hunt for the best property deals to advanced level and make great profits as well as save a lot of resources (both time and money).