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The Guide to Predictive Analytics In Commercial Real Estate

Although no one knows exactly what the future holds, using historical data to predict future trends has been a method used for thousands of years. Ancient Babylonians used to study cloud patterns to forecast the weather. Of course, data collection and analysis have changed dramatically since then, but some industries are still unlocking the potential of new advancements in predictive analytics technology.

The ability to use data to predict trends is a critical process for many industries, so it’s no wonder that predictive analytics is gaining momentum. Innovation in sophisticated algorithms and analytics has led to accurate forecasting for many data-driven businesses and allows companies to formulate strategies, make informed decisions, and gain an edge over their competitors. 

In commercial real estate (CRE), predicting how various markets will change over time is a principle challenge. The ability to spot investment opportunities is key to CRE success. The ability to prepare for situations that used to be unpredictable makes predictive analytics a tool is also paramount to success. At BlueSuit, we use predictive analytics to help the real estate industry stay on top of the data movement.

Here’s an overview of what predictive analytics is and how it benefits the commercial real estate industry.

What you’ll find in this guide:

Predictive Data Analytics: What is It? 

It may sound like a fancy phrase meant only for high-tech professionals, but predictive data analytics is actually a concept that anyone can grasp. In a nutshell, it simply means to use information from the past and present to predict what will happen next. IBM defines it this way: “Predictive analytics brings together advanced analytics capabilities spanning ad-hoc statistical analytics, predictive modeling, data mining, text analytics, optimization, real-time scoring, and machine learning. These tools help organizations discover patterns in data and go beyond knowing what has happened to anticipating what is likely to happen next.”

One example is how Amazon displays personalized advertisements on your account. The online retail giant uses machine learning to aggregate and analyze data from your past purchases and browsing history to identify products you may be interested in. It applies past information (what you’ve already bought or searched) to tailor ads specifically for you to affect your purchases in the future.

The same principle applies to Commercial Real Estate, except regarding properties.

Types of Predictive Analytics in Commercial Real Estate

In CRE, predictive analytics can be used in many different ways and is extremely beneficial for all corners of the CRE industry. Here are some of the ways it helps.

  • Track consumer buy/sell behavior 
  • Identify attractive qualities and amenities in a property
  • Predict up and coming geographical spots 
  • Decide where to invest
  • Decide where to build 
  • Better match homebuyers with properties 

How Predictive Analysis can Help Investors

The whole point of an investment is to bet on the future success of something. But without key insights, investments are risky. Predictive analysis allows CRE investors to make more informed decisions on where and when to invest, providing a safer, more efficient strategy. Additionally, it gives investors a better chance of increasing their return on investment (ROI).

Because of advancements in machine-learning technology, predictive analysis aggregates telling insights on a market or property faster and more accurately than ever. Investors can learn what consumers or tenants are moving towards, what they look for in a property, how a neighborhood is projecting growth, and other future factors in the market that will affect real estate. 

Everyone that works adjacent to investors can use predictive analysis too. Advisors and industry leaders can present accurate predictions to advise investors. 

How Commercial Real Estate Agents Benefit from Predictive Analysis 

Commercial real estate agents can use predictive analytics to identify which off-market properties might be listed in the next year. This knowledge translates to leads that other agents may not be privy to. 

One piece of data that is used to predict future real estate outcomes are looking into missed loan payments of property owners. This may mean that the property owners want to avoid financial repercussions and will want to sell soon. Tenants moving out is another piece of data that may mean owners are more likely to sell. 

This type of data is not unique to predictive analytics though. Anyone can input and analyze raw data–but that takes a huge amount of energy and time. Software can see potential trends that are beyond the trends that humans can easily recognize, and it does it automatically. Some patterns are too complex for any individual to glean from several data points. What’s more, is that computers are also able to adapt over time, using artificial intelligence to constantly learn and evolve as it collects and processes data.

Predictive analytics can help real estate agents to:

  • Reduce the length of time a property remains on the market
  • Understand the buyer’s perspective –what consumers are currently looking for
  • Have a finger on the pulse of the market
  • Determine the best price for the properties they are selling
  • Create better solutions for future issues of their customers
  • Use digital marketing to suit the specific needs of their clients

How Property Technology (PropTech) Companies Use Predictive Analysis

It’s a no-brainer: CRE PropTech companies are built on strong data and analytics to offer the best possible experience to their users and customers. PA, in particular, can be a type of data analysis that will set a platform apart from the rest–especially in commercial real estate vs. residential. Focusing on future trends and providing an accurate, comprehensive outlook on properties matched up with those looking to invest in them is what makes the PropTech realm function.

How Predictive Analysis Benefits Everyone Else 

As previously noted, the unpredictability of the future is one of the biggest hurdles for any CRE professional. Predictive analysis is a way to harness the power of Big Data and seamlessly gather important insights. Consumers and those who use their commercial RE properties benefit too because the industry can better understand and predict their needs in a space.

At BlueSuit, we are big believers that machine learning and data analysis can solve the major issues across a vast number of industries, especially in commercial real estate. Predictive analysis moves us toward better efficiency in which all parties involved in commercial real estate benefit.

How to Start Using Predictive Analysis in Your CRE Business

If you’re ready to use PA to get ahead in the CRE game, here are a few things to keep in mind. 

Start small and start soon. 

The best time to start investing in your company’s data technology is now. The future of the industry is moving toward predictive analytics, so it’s better to jump aboard before getting left behind. Start with one thing at a time, like extracting your data from documents, and then build from there, collecting as much data from different points as you can.

Invest in your predictive analysis strategy.

Predictive data analysis is proven to work and improve ROI. It is important to invest upfront in the time, money, quality tools, and structures to improve your overall data analysis capabilities.


There’s no point in saving time by predicting the future if you’re spending hours combing through documents and data to do so. Find a tool that automates as much data aggregation as possible. One example is plugging in an API.

Ready to Get Started? 

BlueSuit has years of experience helping CRE professionals use data to predict the future and increase ROI. We have a suite of products built to unlock the power of your data and can tailor our partnership based on your needs. Together, we can predict—and build—the future of commercial real estate. Check out a demo to see how!

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