In today's digital world, individuals and businesses are constantly generating massive amounts of data, providing valuable opportunities to those who understand and can harness it for their benefit. For example, commercial real estate businesses can tap a wide variety of data sources to increase tenant satisfaction and, in turn, improve lease renewals, occupancy rates and profits. This blog reviews how commercial real estate businesses can use data analytics to their advantage.
Related Read: Four Ways That the Coronavirus Is Changing Commercial Real Estate
Data Collection
Real estate businesses have many sources of data that can help them better recruit and serve their tenants. For example, the growing popularity of the so-called Internet of Things - the networking of people, sensors and objects to automatically collect, exchange and apply data - can help owners collect information that can be analyzed to improved tenant satisfaction.
Investors and developers can also employ digital reality (DR) to gauge potential tenants' preferences during pre-development. With DR prototyping tools, prospective tenants can experience 360-degree views of their space with different types of detailing and provide feedback prior to property development. This paves the way for the incorporation of in-demand features and tenant customization.
With artificial intelligence and machine learning, you can also leverage unstructured data that is not organized according to a pre-defined model. That includes documents, metadata, emails, texts and conversations.
And do not forget about more traditional data sources. Data compiled from tenant leads, customer feedback, the media (social and otherwise), government databases, and industry statistics and research remain relevant.
Putting the Data to Work
The volume of data available may seem overwhelming. Fortunately, data analytics provides the tools for evaluating information and converting it to actionable intelligence that can lead to more informed decision-making.
Data analytics can be:
- Descriptive (identifying trends and analyzing behaviors);
- Predictive (forecasting the behavior of, for example, certain types of tenants); and
- Prescriptive (providing advice on features to include during development).
For example, you could use data analytics to research different geographic areas to predict the demand for a project. Or, you could use the data collected from smart technologies that manage lighting, HVAC and security to identify usage patterns and trends to improve facility management and maintenance.
Finally, do not overlook the human element because you will need access to qualified experts. They should have knowledge of not just data analytics, but also the business and industry. Without that perspective, you could end up with irrelevant, useless information.
Use It or Lose It
The data is there for the taking, possibly in far greater amounts than you can imagine. Savvy real estate businesses are increasingly using it to create a competitive advantage in the real estate market. Those that do not take advantage of the information at their fingertips will eventually fall behind.
The content of this article is intended to provide a general guide to the subject matter. Specialist advice should be sought about your specific circumstances.
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