With data, everything makes more sense – so we gave PropertyGuru agents DataSense.
Launched on 31 March 2021, DataSense is a suite of proptech data tools that we designed for PropertyGuru agents, so they can become even better advisors for property seekers.
With adoption rates growing 3x weekly, about 13% of agents are already using DataSense since its official launch. With adoption rates increasing week on week, more and more agents are expected to benefit from this tool.
Through the successful launch of DataSense, PropertyGuru is empowering agents even more, with our data technology to answer some of the most pertinent questions property seekers go through in their home buying/selling journeys.
“What is the best asking price for my property?”
Probably the trickiest question of all. These numbers could really make or break your deal!
It must be something high enough that is appealing for you to sell, yet also realistic and within the budget of your buyer. Striking this balance is easier said than done and is truly a science.
Good thing we have DataSense to help with this!
DataSense gives our agents PropertyGuru-exclusive data that compares actual transacted prices versus asking prices to make an informed judgement call.
“This exclusive data is incredibly useful and important for property sellers to adjust their price point in accordance to market rates. This is important for 2 big reasons. First, a good price point allows banks to match the property valuation easily and will make the transaction a lot smoother. Secondly, it helps with offloading your property within a comfortable timeframe for your subsequent portfolio progression. Pegging the wrong price tags to your property reduces the number and quality of interested buyers; having the right price helps attract the right buyer with a sincere bid for your property.” – Linda Yang, PropNex
Tip: Ask your agent to find this out for you under DataSense’s Market Insider tool.
“Is this the right time to sell my unit?”
“Is this the best time to buy this unit?”
Thanks to DataSense, PropertyGuru agents can immediately advice property seekers:
- If you’ll get a profit or a loss by selling your unit now
- If you can actually buy a unit below value
- …and much more!
“It’s always good for every client to have transparency on each unit’s purchase price, be it a profit or a loss. A tool like Project Insights will help property buyers and sellers analyse better before any transaction, so they can make a more informed decision. It could also help in the negotiation process.” – Zac Huang, ERA
Tip: This data is available to your agent via DataSense’s Project Insights tool.
“How does my property compare with other nearby properties?”
Whether it comes to buying or selling, it’s always good practice to do a little research around the neighbourhood.
Using DataSense, agents can quickly view comparative charts of one property versus others nearby!
“It is important for property owners to get an idea of how nearby or similar properties are performing, so you get a very realistic and objective perspective of how you can expect your property to perform. This is a big factor to help you decide if it’s the right time to sell and what is the right price for your property.” – Alvin Tay, Huttons
DataSense also empowers agents to advise on surrounding amenities at an instant within radiuses of up to 5KM!
“Your agent should be very familiar with the property and the surrounding area, with important amenities like shops, medical, distance between schools, food – almost like your agent lives in that neighbourhood! Home Report can help agents understand each property faster and better, so we in turn can advise you if this property is truly a good buy for you.” – Andrew Nair, ERA
Tip: Ask your agent to show you around the neighbourhood through DataSense’s Home Report.
With further enhancements to DataSense being rolled out in the coming months including PropertyGuru exclusive data points, the PropTech eco-system and property seekers alike are benefiting from the growing rate of PropertyGuru agents being empowered by data.
