Using Data to Make Intelligent Real Estate Investment Decisions
Think of a city you know like the back of your hand.
Now think about your favorite block in your favorite neighborhood in that city.
What makes the block so nice? Is it particularly picturesque? Close to transportation? Near parks, upscale shops and great restaurants?
Take it a step further and think about what is the best location on that block and think about why it’s the best. Is one end of the block more quiet? Near a more desirable cross-street?
Now consider which building on that block is the nicest. Why is that? Better architecture? Nicer views? A more recently renovated lobby?
It’s clear: real estate investment is a hyperlocal business.
As this short exercise demonstrates, a multitude of factors go into every investment decision. If it takes this many internal calculations to evaluate a market you know well, imagine trying to make an informed decision in an area you’re less familiar with.
Traditionally, this knowledge has been provided by real estate brokers.
When sifting through listings, there has been almost no substitute for an experienced broker’s guidance. A broker who has covered the same neighborhood for decades knows the nuances of every block, every building and every home. He or she knows exactly which units have the best views, which floors have the best light, which buildings are in the best school district, and which blocks are the quietest — along with hundreds of other data points.
A great broker intuitively processes that data and can then use it to offer better investment advice.
Smart real estate investing depends upon this ability to analyze hundreds of data points, some of which are easily measurable — unit size, price per square foot, or distance from public transportation, for example — and others which are more instinctive, like which neighborhoods will change or be gentrified, which units will rent most quickly, and whether some inexpensive cosmetic changes can make a unit more valuable.
Historically, brokers have developed this knowledge by seeing thousands of apartments, observing trends, and building this instinctive feel for how and when real estate will trade over time. A broker’s ability to discern these trends can often have an enormous impact on the performance of a real estate investment.
The Age of Big Data
No matter how experienced a broker might be, with the proper data sources, an algorithm can improve returns when compared to the traditional calculus.
At Compound, we’re building just this: a proprietary algorithm of more than 50 points that integrates both traditional and unorthodox data sources to enable us to find the absolute best investment opportunities in each market we enter.
Public city records, local MLS data, in-house expertise and more are incorporated into our algorithm. By constantly refining our model to hone in on the data points that track or outperform the market our team is most familiar with — Manhattan — we are creating a scalable algorithm that can be easily adapted to perform in markets around the nation and world.
We can’t give away all of our secrets, but here’s the gist:
- We analyze opportunities on a block-by-block, building-by-building, unit-by-unit basis.
- Each data point is assigned a numerical value.
- We compare all investment opportunities on a relative basis, assigning a score to each.
- This score determines which investments to pursue, when to bid, and how to price them.
Our methodical approach helps to ensure that our investments consistently track or outperform the market. Learn more here.
