Before big data, real estate investors had to fend for themselves in the figurative wilderness, relying on an incomplete mixture of gut feeling and the limited traditional data available to them. That’s where you get the conventional cliché of an investor barking “buy” and “sell” into their phone as they run their finger along a basic financial chart. Luckily, things are more sophisticated now.
With the emergence of big data (and its essential wingman, artificial intelligence), investors can now access actionable insights culled from hoards of traditional and non-traditional data. Basically, big data is a massive data store defined by “the three Vs”: Velocity (how fast the data comes in), Variety (how diverse the data is) and Volume (the sheer size of the incoming data). We’ve only recently been capable of storing and analyzing big data, thanks to advancements in artificial intelligence and predictive analytics. Check out Lendai for more real estate info as well.
And even more recently, real estate investors have clued into the benefits. To help you make educated investments, this article explores four distinct ways that you can capitalize on big data to mitigate risk, pre-empt investment opportunities and put your money behind likely winners.
Table of Contents
Non-Traditional Data for CRE Investment
Commercial real estate investors were probably the first to realize big data’s potential.
A couple of years ago, McKinsey published a white paper lauding the advantages of big data in incorporating non-traditional data; they pointed out that these non-traditional data sets fleshed out a clearer picture of investment opportunities. Since then, commercial investors have increasingly leveraged big data for CRE acquisitions through cutting-edge income trusts.
Big Data Vetting for Real Estate Representation
Having quality representation is the bedrock of sound residential real estate investment. A buyer needs to trust that their realtor or real estate agent can sniff out the right opportunity and vet it thoroughly.
The question then becomes: how do you, the investor, find and vet the right real estate representative? Once again, big data has a compelling solution. Take it from Regan McGee, the founder and CEO of Nobul, a tech-enabled digital marketplace that leverages big data and AI to match investors and agents. “The average realtor sells four homes or less a year,” McGee tells Medium. “Their track record is not available to the public except on Nobul.” Investors can use Nobul to leverage AI in their hunt for quality representation.
Striking While the Iron’s Hot with Open-Source Data
Once you’ve found the perfect real estate agent, big data can help you pinpoint the perfect property by capitalizing on open-source data.
Bright Data offers Manhattan’s Meatpacking District as an illustrative example; investors looked to open-source data from social media that hinted at the neighborhood’s upcoming trendiness and were able to invest money prior to the area’s complete gentrification. By following big data from real estate insights companies (like EY or Dealpath), investors can get in on the ground floor of the next significant investment opportunity.
As the technology becomes a routine part of the industry, expect to see the widespread application of big data on other facets of investment: lending, property management, etc. It’s an exciting time to be a real estate investor.