For more than eight years, iProperty.com has operated a group of property portals with a strong presence in Asia Pacific. The company offers a platform for property buyers and investors to search for their dream home, while offering real estate agents and property developers an avenue to effectively showcase their listings and developments. The site also allows for third party vendors such as financers and legal service providers to share information and services that assist property buyers and investors in making informed decisions.
With over 4 million unique site visitors each month, iProperty sits on a large amount of data. The team behind the portals knew that there were valuable insights to be found.
The newly-founded big data team initially tackled their data with Excel and then Power Map, a Microsoft product. They soon found that these tools could not effectively handle iProperty’s large amounts of data. The two-person team was spending far too much time slicing and dicing data manually. Worse, the output was “old school” and lacked visual appeal.
After discovering Tableau, the team was immediately sure that they found the right solution. The now six-person team delivers interactive visualizations to customers and the response has been gratifying.
Additionally, divisions across the company are beginning to use Tableau to drive improvements internally.
Experimenting with data
iProperty was sitting on a large amount of data—approximately 1.5 million data points per day—which they had collected over eight years.
This data held the answers to many pertinent questions from developers, property agents, as well as property buyers and sellers. Questions like ‘What is the right price for a property in a certain market?’; ‘What type of properties do consumers want to buy?’; ‘What sort of development would be suitable for a specific land parcel?’
iProperty saw an opportunity to develop a new services arm that could provide consultation and projections to help customers make informed decisions. They knew that they could take disparate data—location information, search terms from their websites, and more—to develop truly valuable insights.
iProperty Group’s Chief Information Officer (CIO) Harmit Singh formed a big data analytics team to look into the use of data. Initially, the team started working with Excel, but they soon found it to be limiting, as they could only work with a certain number of rows of data.
Harmit commented: “We had to do a lot of slicing and dicing of data manually to fit our data into Excel and this took a lot of time. Also, the charts that we could create using Excel were rather ‘old school’ and not visually exciting.”
The team then tried to use Microsoft’s Power Map. They also found it challenging to present the data visually, and the results they got were not as exciting as they would have liked them to be. People consuming the data also could not interact with it to ask more questions.
The big data analytics team decided to look for a better solution. They knew that engaging, interactive visualizations are critical if they want to truly excite customers with these insights.