“Deep beneath everything, there’s data.”
The power of data cannot be stressed enough. Anything that is today, and there will be in the future all started somewhere at some granular level with the insights drawn upon data.
With just data, there’s nothing much you can do. Essentially, data with quality is out of which remarkable insights are born.
Digital innovations born out of this data has been disrupting every industry. The ways and means of doing business have been transformed incredibly in the past decade or so.
Is the real estate market any different?
As pointed out by. Online research is the most convenient and easy form of acquiring instant information and it does not limit to just that. Moving from traditional classifieds to websites or app or digitizing anything for that matter, offers some broad benefits – effective community outreach, curating real-time updates, indexed listings, and exposure to exhaustive data points.
“Online real estate business draws buyers and sellers closer, promotes transparency, and unleashes the power of progress”
The meaty role of data in real estate business
A good, credible, and informative real estate website is one that has a huge database of real estate listings covering wide points of information like – property details, buyer and seller information, and agent information. It is the presence of such huge amount of data that helps smarter decision-making an absolute ease.
A large pool of information that is authentic and credible will help buyers make a more informed decision. To acquire this kind of data from across the internet, real estate data extraction will help in getting all the information that is essential for successful real estate business.
How to get this real estate data?
When it comes to large volumes of data that is lying around the web in different formats and different sources, there’s no other best solution like scraping that brings all the data hidden almost anywhere. Particularly for real estate data scraping, people search for various aspects – real estate listings, agent information, the price of the property, plot information, seller profiles and a lot more.
To provide the best real estate services, you need to have a repository of data that covers vast data point spread. Also, constantly refreshing this information will make you more reliable. This data could be stuck in websites, classifieds or any other digital source. Scraping this information will help you own the most exhaustive and authentic information that your clients can trust in terms of quality and in making informed decisions.
Some valuable data points to scrape:
- Agent information
- Property data
- Price data
- Property size
- City/State/Zip code
- Rent price
Here’s a quick example of scraping of the Zillow webpage
This is a use case of scraping the Zillow website for extraction of some essential data points like address-price-sqft-bedrooms-bathrooms-pets-laundry-deposit fees in the Washington region.
The code for scraping Zillow web page would go like this:
#navigation part homeLinks = tree.xpath('/*[@id="yui_3_18_1_1_1544120891543_603"]/a/@href') for links in pdpLinks: print links #processing the details page res1 = sess.get(links) data1 = res.content tree1 = html.fromstring(data1) #extracting attributes using Xpath address=tree1.xpath('/*h1[@class="zsg-content_collapsed"]/text()') price=tree1.xpath('/*[@id="yui_3_18_1_1_1544121633041_992"]/text()') sqftdetails=tree1.xpath('/*[@id="yui_3_18_1_1_1544121633041_2678"]/text()') bedrooms=tree1.xpath('/*[@id="yui_3_18_1_1_1544121633041_1003"]/text()') bathrooms=tree1.xpath('/*[@id="yui_3_18_1_1_1544121633041_2690"]/text()') pets=tree1.xpath('/*[@id="yui_3_18_1_1_1544121633041_2696"]/text()') laundry=tree1.xpath('/*[@id="yui_3_18_1_1_1544121633041_412"]/text()') deposit=tree1.xpath('/*[@id="yui_3_18_1_1_1544121633041_2671"]/text()') #output preparation with open ("Zillow_Sample.xls", "a") as fh: fh.write ("%s"%address+"\t"+str(price)+"\t"+str(sqftdetails)+"\t"+str(bedrooms)+"\t"+str(bathrooms)+"\t"+str(pets)+"\t"+str(laundry)+"\t"+str(deposit)"\n")
The extracted output will be in a structured format thus enabling quick analysis:
The Scraping process: The path to a more rewarding real estate business.
Scraping real estate listings would mean setting up web crawlers to scrape the desired data points held in real estate websites and other sources like digital classifieds. The bots would fetch this data and the information will be transformed into a structured format that enables analytics.
This data can be integrated using different formats or through any preferred database options. It could be integrated through FTP/AWS in CSV, XML, and text files.
Apart from having the basic property details, you portals should have details of agents, legal teams for real estate business, brokers, value assessment providers etc. Such data will help you stand out competition and attract more visitors to your site considering the vast amount of information you offer.
Data becomes stale over a period of time due to constant changes and updates. You can also stay updated with the changes by getting notified about it through periodic scraping that can span over a week, month, or beyond.
The Millennial momentum
The main target for the real estate business must hands down be the millennials – as the kids who rode their bikes on the suburbs a decade back, now fall under the main investor groups in the real estate market. The reason being – moving or shifting houses due to frequent job changes, moving to new cities, investment as an option etc.
This clan is known for its online presence, and most of the deals conclude as a result of apartment hunting through online searches. Also, they are on the lookout for plenty of information covering a broad spectrum of questions like:
-Previous owners of property
-Restaurants close by
-Who else is interested ( in order to explore roommate options)
-Proximity to the workplace ( Transit facility)
So to be able to cover tons of questions, you need to have enough data. Though you cannot accommodate oceans of data points on your site, you must never have shallow content that
Innovate with information: The age of apps
To get more close with the users and give a more personalized experience, there’s a need to innovate. The real industry is just warming up with innovation and the next area AI is eyeing on is this industry and Zillow is one of the first ones to adapt to these changes.
An evolution from a website to the app would ideally be adding intelligence to elevate the experience by getting a step closer with your customer by understanding the search patterns and giving suggestions parallel to their choices. For instance, if the buyer’s search is aligned to a feature, say in-house laundry unit, then Zillow would basically recommend houses with similar facilities.
Some interesting innovations like 3D house feature that will enable a google street view to take a glimpse of the inside of the house is also something Zillow has introduced.
Apart from this, tons of features like connecting to agents, live chatbots, notifying when a new property is listed that closely aligns with search and taste, analyzing search patterns and giving recommendations and a lot more.
The entire process is immense efforts, investment on resources, trial and error, research, and accommodation for risks.
But what is the one major barrier?
Hands-down, building the foundation for this very thought needs data. Getting this data that forms the basis for all the savvy innovations you are ready to put out in the market is already out there.
The process of scraping will help you build a strong database from where some tremendous evolutions will take place. As you look back, there will be data that has enabled you to triumph by walking you through the path to innovate.
Every Real estate business needs scraping solutions
Real estate industry is blossoming with vast opportunities day after day. Staying relevant with the online search trends is paramount to success. There is no better solution than scraping information to offer the best service to your customers in the form of quality data. Also, using the same information as the foundation to disrupt the industry with newer technology and innovations in the form of highly intelligent apps.
You can set your parameters for the scraping requirements and we can deliver the data that you want.