Case study

MLS System for a Major Real Estate Service Provider

MLS system


One of the leading real estate service providers in a specific geographical location.

Client was interested in establishing a MLS system to provide a collaborative platform to all real estate brokers and agents in a specific geographical location.


Business Situation

  • The real estate market is in its evolving phase and is currently comparatively unorganized. There are huge number of websites that have thousands of property listings. Moreover, details in these listings changes dynamically
  • Property Agents and Brokers have to access these websites individually to get information about listed properties. Moreover, data related to these listings keep changing. Hence, it has to be again manually retrieved by agents and brokers.
  • This whole process is costly and error prone.
  • This client’s requirement was to streamline the real estate sector by leveraging the technology to boost networking between the agents and brokers throughout a specific geographical location for creating a multi-listing service that is a centralized database of the real estate market


Benefits and Outcomes of Our Engagement

  • Common real estate platform for agents and brokers to work in collaboration.
  • Quick and accurate property listing information available real time.
  • Savings in operation cost by reducing/removing manual efforts.
  • Analytics engine will provide business-aligned reports to help grow business



  • SGA created a web scraping technology solution that scrapes relevant information about listed properties from 100s of real estate websites. This information is used to build a MLS system for the client. This helps in saving huge operational cost, increasing accuracy, and serving clients (property buyers and sellers) much more efficiently.
  • The solution also has an NLP engine that enriches data by extracting missing metadata from property description. This helps in storing complete property information in the MLS system and also improves web-scraped data by enhancing search criteria on real estate websites.
  • The next business case was to create an Analytics Engine on top of the MLS system to provide useful information about the real estate and help grow client’s business in this space.


SGA Approach

  • SGA’s team of web analytics and technology experts developed an effective solution based on web scrapping using Robotics Process Automation, Python, and NLP.
  • The solution would be augmented with analytics solution to provide business-relevant reports.


Cost Benefits

  • It took 2.5 minutes for an employee to retrieve data of one property listing from a particular website and then save it in Excel. For 700 websites, it took them 29 man hours per day.
  • Our solution does the same thing in 2.5 hours.
  • Previously, the work involved a cost of $11,520 per month. This solution saved $7500 per month.

We bring comprehensive data driven insights to everyone, everywhere

In depth-analysis with simple solutions