For a long time, the commercial real estate industry has relied on property data and “gut feelings” to make decisions. However, given the magnitude of changes in the real estate market and, by extension, interest rates, it has become extremely risky to make these big decisions based on assumptions. Thanks to advances in technology, commercial real estate investors now have a source of information, especially non-real estate data, to refer to when considering a purchase or planning a development. Of course, to maintain the value of real estate data and supply-side data, a prospective buyer needs to know her NOI, occupancy, tenant strength, etc. However, non-real estate data filtered through cutting-edge technology is playing an increasingly important role in investment decision-making by providing additional forms of analytical intelligence.
Among the various options available to investors in the expanding world of technology-based non-real estate data is sentiment analysis, which can provide insight into the varying attitudes of tenants toward an apartment, office, or retail market. Masu. This data is especially useful to the development community. One of the companies at the forefront of multifamily real estate sentiment analysis is RCKRBX (pronounced “rocker box”). Powered by an AI-powered platform, the company provides real-time information based on responses from thousands of detailed quarterly surveys of prospective renters within a given market. Evolved from the science behind political campaign research, the platform gets into the heart of the rental population and collects critical primary data from actual potential tenants.
By combining primary audience research with secondary market data, investors can essentially test their underwriting assumptions by comparing them to the project’s performance once it’s on the market. I can. “Insights from actual end users – tenants in commercial office buildings and residents in multi-family housing – are critical because their perspectives, priorities and preferences can be leveraged to create a Because we can evaluate all of the secondary source information,” said Michael Broder, CEO of RCKRBX. “It’s really important today to have more information about what people are looking for in their next space, why they’re looking for it, and the premium they’re willing to pay to live in that kind of environment. ” Broder equates making real estate decisions based on supply-side data to looking in the rearview mirror and driving to a new destination.
It’s really important today to have more information about what people are looking for in their next space, why they’re looking for it, and the premium they’ll pay to stay in that kind of environment.
RCKRBX CEO Michael Broder
Sentiment analysis is just one part of the pool of non-real estate data that real estate investors look to to guide their activities. Geospatial data (also known as geolocation data or simply geographic data) is becoming extremely popular in the real estate industry. This GIS-based location intelligence provides a large amount of information about a specific geographic location, providing details about land boundaries, land quality, transportation networks, demographics, and other factors. Collecting and analyzing geographic data essentially provides insight into what changes are likely to materialize in a particular location in the future.
Geographic data can also help real estate investors understand the risks associated with each property, such as climate risk, which much of the industry is currently very focused on. As the world grapples with the effects of climate change, geospatial data that provides information on aspects such as weather patterns, water tables, and fire zones can help when choosing development locations and building resilience features into projects. It can be extremely valuable.
Predictive analytics is also a key component of non-real estate data. Software platforms can sift through detailed historical data and combine it with numerous real-time market data sources to predict changes in market trends and changes in real estate valuations. It’s all about data, and the analysis of a wide variety of data. “It’s not a single piece of information that helps you make decisions; it’s the complex relationships between lots of data,” said Joshua Panknin, director of real estate AI research and innovation at Columbia University’s School of Engineering. “A 311 call gives him one piece of information. A building permit gives us another. Building performance creates new value.” Columbia’s team believes in real estate. We also look at factors such as online data about nearby stores. Investors can leverage powerful software to identify real-time market fluctuations by analyzing ratings, reviews, and new business openings. “No data is that valuable on its own. It’s valuable when you combine all the different datasets, and if they point in the same direction, you get a stronger indicator of change,” Panknin said. Ta.
The more data investors have about prospective tenants, site geospatial factors, potential market changes, and other non-real estate metrics, the more likely they are to achieve long-term success in their acquisition and development efforts. This will put you in a better position to contain it. The current turmoil in the real estate market opens up many opportunities, but it also brings with it many risks. Use demand-side data and predictive analytics to evaluate real estate assumptions in ways never before possible. Investors are increasingly using non-real estate data to make investment decisions, but it won’t be fully embraced by the industry overnight. Old habits die hard and yesterday’s habits of making decisions based on location, location, location have evolved. “It’s all about location, demand and analysis,” he explains. “And I think you’re seeing people moving towards that, but it’s going to take time.”
