Previously, real estate investments were based on speculation, informed estimates, and assumptions, which frequently repeated the same mistakes. Real estate data science provides insight to help people make better-informed decisions about their investments, thereby significantly reducing their risk. The result is that investors are increasingly leveraging data to strengthen their competitive advantage.
Data Analytics for the Real Estate Sector
In descriptive analytics, historical data is analyzed to create valuable historical insights. For example, what is the yearly growth rent in real estate over the next five years?
The primary purpose of this type of analysis is to establish what activities need implementing to take advantage of an opportunity or to avoid a future problem, such as determining the recommended number of beds for an Airbnb house. Airbnb’s analytics can be used to help determine what needs improvement to increase occupancy.
This involves analyzing historical data to determine what caused a specific event. Diagnosing rental properties, for example, can reveal why they have a very high turnover rate.
Predictive Data Analytics
These analytics predict future events, as its name implies. For example, diagnostic and descriptive analytics enables users to detect clusters, exceptions, and trends in the housing market, such as how much rent will rise over the next two years.
What Is Big Data
Big data in commercial real estate includes everything from leasing, financial, and demographic data to building system information and tenant movements inside buildings. Big data also include monitoring social media and news feeds.
Most of this information is gathered by sensors and cameras connected to the internet of things (IoT), which embeds internet connectivity into objects and devices. Consequently, the internet of things plays a significant role in the commercial real estate sector.
With big data technology progressing at such a rapid pace, no sector has been left untouched. However, when compared to other sectors, the commercial real estate sector has been slow to adopt big data while the retail sector, in particular, has gone through a significant transformation.
How Big Data Analytics Is Being Leveraged in Real Estate
Wider Scope of Analysis
Big data is now used in real estate development, including to improve the accuracy of predictive algorithms. Big data analysis can provide insight into the mortgage industry, insurance risks, actuarial calculations, and the purchasing power of each household based on its location.
Property appraisers may base their valuations on current market patterns by combining data sets into AI models and predictive algorithms. Relevant factors may include supply and demand, sales volume, property characteristics, and fluctuating construction costs.
Home Research, Marketing, and Sales
Big data is also applied to improve marketing properties. For example, using tools designed for realtors, they can refine their audience and target relevant buyers using search engines and digital advertising data.
Real estate industry players are adopting analytics tools that change how they do business and make decisions. This model analyzes visitor behavior on competitors’ websites and user interactions and messaging from relevant ads.
Alternative data sets can also be used to examine buyer preferences, finances, and even their commitment to completing the transaction. For example, scanning the internet can look for signs like mortgage preapprovals, credit scores, and historical consumer behavior.
The Impact of Big Data on Current Commercial Real Estate and Property Management on Real Estate
The big data market is forecast to grow considerably over the next decade, and the industry is likely to develop even more data-driven solutions for commercial landlords. Landlords may now employ data and IoT technologies to manage their properties.
Using the right information, building owners can adjust and optimize systems to reduce wasteful energy use, reduce costs, or even automate entire buildings, helping to make them more eco-friendly.
Technological innovation in big data constantly introduces new trends, which is why realtors need to keep up with them to remain competitive. Furthermore, in an era when big data analytics is becoming more accessible, it is impossible to operate successfully on the market without fully utilizing its benefits.
What’s in Store for the Future?
The future of the commercial real estate industry lies in big data and predictive analytics. The industry is transformed through real estate data science by creating a powerful new asset. The result is that a new industry category of players is emerging, explicitly focused on data-driven solutions.
The industry is driving a shift from internal databases to large open data platforms to maximize the use of this information throughout the industry.
As a company, UnitConnect places great value on providing our customers with cutting-edge lease, management, and sales technology. We use analytics to achieve our goals, and we are constantly innovating new technologies in Commercial and Residential Property Management. Our goal is to continue providing the highest level of service to our clients in the communities that matter most to them.