Predictive Analytics
The use of historical data and machine learning to forecast future trends or outcomes.
Putting Predictive Analytics in Context:
CRE investors use predictive analytics to identify high-potential markets for multifamily developments by analyzing rental demand trends and population growth.
Frequently Asked Questions about Predictive Analytics in Commercial Real Estate
What is predictive analytics in CRE?
Predictive analytics in commercial real estate (CRE) refers to the use of historical data and machine learning techniques to forecast future trends or outcomes.
How do CRE investors use predictive analytics?
CRE investors use predictive analytics to identify high-potential markets for developments by analyzing factors such as rental demand trends and population growth.
What type of data is used in predictive analytics?
Predictive analytics relies on historical data—such as rental performance, demographic trends, and market activity—to model and forecast future performance.
What is one example of predictive analytics in action?
One example provided is CRE investors using predictive analytics to identify markets with strong rental demand and population growth to support multifamily development decisions.
How is machine learning connected to predictive analytics in CRE?
Machine learning algorithms analyze large datasets to detect patterns and generate forecasts, forming the core of predictive analytics methods in CRE.
Click here to get this CRE Glossary in an eBook (PDF) format.