This post originally appeared on Marketplace Partner, RealMassive News Blog and is republished with permission. Find out how to syndicate your content with theBrokerList.
Businesses have been developing predictive analytics since the beginning of commerce. Haberdashers forecasting shifting tastes in fashion, or financiers developing strategies to trade stocks, are two of the classic examples.
As you already know, developing sound predictive analytics has always been a key competitive advantage in commercial real estate. And it’s something that won’t change: we will always be using data from the past to predict future results.
What will change is the speed at which you can gather information, interpret results, and make informed decisions on what will happen next in your market. And while 21st century Predictive Analytics may seem a little magical to some, when you pull back the curtain you can see the full picture. To do that, let’s break it into its main three components that explain how to use commercial data to predict future results.
Put simply, if you don’t have good data you can’t make sound predictions. This is exactly why we’ve spent the better part of the past five years developing our system and gathering as much data as we can on every individual Commercial Real Estate market in the United States, and currently have over 6 billion square feet of property listings on our site.
Next, you have to look at the correlation of variables between properties both on the market and on deals that just closed (the most common are price per square foot, location, and a property’s amenities). Once you have enough good data, you can see how much each variable affects a deal and then accurately quantify what features are driving the market.
And this is why, while we’ve been laboriously gathering the data, we’ve been building customized software that allows for you to search through the market data based on whichever variables you care to research and ensures you are able to cross-reference the results based on multiple variables.
The main aspect that is overlooked is the idea that certain variables aren’t factored correctly: most importantly, that the future will be similar to the past. While it is true for the most part, the dramatic market shifts are very different to what happened in the past (see: the Great Recession) and are rarely predicted accurately. And this is why having data that is as recent as possible is vital. With real-time data, you can see the market shifts before your competition does and make adjustments…which is why we’ve built our platform to give you the most recent, and thus accurate, data on the market.
Want to learn more about how you can use our data to build better predictive analytics than your competition has? Check out our website to find out how we can help you.