top of page
  • Writer's pictureBhagyeshwari Chauhan

How Data Scraping in Real Estate Will Transform the Housing Industry?

Updated: Feb 12, 2021

With the advancement of big data analytics and machine learning algorithms in day to day lives, a modern company today spares no expense in utilizing them for their betterment. From e-retailers, healthcare, tourism, and travel to name a few, each industry is open to exploring the prospects of a data-driven functioning for a profitable business. In this epoch of data-driven disruption, how could the real estate industry stay behind?


One of the most competitive industries today, real estate has begun to realize the importance of data-driven decision making. Any geographical area has a ton of contenders, a superior knowledge, and timely service can get you the desired sales. To be profitable, one doesn’t only need to grasp the current market but also predict how it would perform in the future


Enter Data Scraping

The influx of big data analytics in industries has transformed the way businesses operate. They can now make informed decisions, predict market conditions, provide better services and increase sales. With no exception in the real estate industry, big data has shown a multitude of aspects real estate agents had no access to earlier.


Real estate agents benefit by determining the competitive price for a property by monitoring sale/offer price of similar properties in the area on a per square foot basis. This involves finding an average by dividing the sale price by the number of square feet and then comparing this against other similar properties to get an average price per square foot ratio.


A Multiple Listing Service database, referred to as MLS, withholds this kind of information which provides a working knowledge of agents, listings, plots, and prices. It’s cumbersome to gather and process this information on a large scale.  One of the most useful and quick ways to collect, analyze and interpret the various forms of data needed to excel in the real estate business is data scraping.


Data scraping in real estate provides services to get the comps, current market values, exhaustive agent information, buyer and seller details, etc. Using this information can allow you to see where the market is currently at and where it is trending. Scraping data from relevant websites can process this information and break it down so that you can understand current, as well as future market values in your geographical area.


Gaining an edge in the marketplace

Enter data scraping and you shall have that advantageous edge in the marketplace.

Data Scraping in real estate not only gives actionable insights into current market scenarios

but also aids in predicting where the market is going. Information like listings and agent information as well as emails arms real estate agents develop proper, competitive marketing strategies and gain a more secure position in the real estate industry.


The following information is a must to have your real estate company function properly.

  •         Real estate listing

  •         Buildings details

  •         Buyer and seller profiles

  •         Details on reputable real estate agents


Gathering and analyzing this information will enable your company to make informed decisions with the aid of good quality information.


While manually scraping from listings and investor websites can be a cumbersome task, 3rd party data scraping services provide accurate, time-saving and credible information. Data scraping services crawl the web to gather relevant data pertaining to the parameters it is programmed to abide by. This ocean of information is then broken down into easily understandable information in databases to be directly consumed by the customer.


Why Data Scraping in Real Estate is a Real Game Changer

Why Data Scraping in Real Estate Will Transform the Housing Industry

Data scraping can provide that differentiating aspect to your retail business by presenting accurate and apt information for both clients and agents to make profitable decisions. While a buyer wishes to know extensive details about the prospective property, the seller wants to ensure a profitable pricing in the market.


This could be done in 2 ways:


1. Gathering up-to-date strategic information 

Strategic information useful for a real estate agent includes collecting a large amount of information from the internet, accumulate that info in a desirable format and store it in a

database for systematic use. This information can be obtained by setting basic search

parameters like location, size, prices, reviews, etc. While manual scraping can be essentially tedious, lacking in data and inefficient, web scraping scours the vast web based on these search parameters. And giving customers access to such extensive information can be a game changer

for your company. Scrapping for data manually can risk in acquiring outdated data. Whereas

web scraping ensures property listing to remain updated by notifying whenever a change occurs. Moreover, web tools scan the web for property images which can be beneficial for a sale.


2. Scraping agent details from the Internet

Web scraping can help to extract agent details from the internet for the real estate company, thus making businesses even more profitable. To top it off, data scraping for real estate can also provide agent websites, chat rooms, profiles, communities to get hold of vast amounts of detailed data on real estate agents. A lot of real estate companies are resorting to 3rd party web crawlers to cut down cost and effort.


There is no denying the fact that data scraping for real estate has brought in tremendous growth and endless possibilities for the real estate industry. How else can web scraping prosper the real estate business? Let us know in the comments below.


Looking for a highly scalable web scraping service to meet your business’s needs?

Contact us at Datahut.


122 views0 comments

Do you want to offload the dull, complex, and labour-intensive web scraping task to an expert?

bottom of page