Artificial Intelligence and data science are impacting nearly every business sector. The real estate industry has a reputation as a slow adopter of sophisticated technologies, and some businesses have been quicker to embrace technological innovation than others. VirginLand by Ringley has been a data-led business from the outset and developed a unique land search & acquisition model centered around data science and digital disruption.
Data science is the process of obtaining insights and meaning from data patterns. In the modern world, even a business of average size generates enormous volumes of data through diverse sources. And those numbers keep growing exponentially. Detailed and proper data analysis can help detect specific patterns and trends. They help businesses make the right decisions and provide their customers with better experiences.
As mentioned, the real estate industry has rarely been an early adopter of new technologies with potential disruption. Even today, many tasks are carried out manually despite the availability of alternatives. That trend is changing, and it is seen that real estate is now keen to embrace data science. For instance, online software systems have been built with millions of data points across the UK for developers, housebuilders, agents, consultants, and whoever else to navigate to bring forward-compatible development opportunities. This software picks up data from several other digital sources, allowing people access to vast data at their fingertips that was previously a painstakingly manual process to acquire.
VirginLand by Ringley use several software similar to the aforementioned example and can overlay the land requirements of property developers and housebuilders to identify their next land acquisition opportunities. We can pull relevant data and using in-house developed technology write personalized letters to landowners that typically achieve 4-5x industry average response rates.
There are other ways available of applying data science to the real estate industry here are a few examples:
Investors in real estate often have to take huge risks as there are elements of uncertainty associated with real estate deals. Now, they can base their decision on insights provided by high-quality data. Real estate investors can make highly accurate predictions about their property investment and make good profits. Data science methods involve pulling in large data sets from various sources and factoring in the risk elements and potential changes. It can help analyze the unique characteristics of the property and its demographics. Data science can even help in predicting property returns in specific areas.
Property valuation is often resource-intensive and time-consuming. The advent of automated property valuation has changed the picture dramatically. The software works by harnessing critical data and creating a realistic estimate of its market value. The automated system for property valuation offers several benefits:
Enhanced Forecasting
Data science models can easily handle massive amounts of data emerging from different data sources to provide better forecasts for investments and developments. Investors can look forward to greater financial returns.
Real estate performs differently in different locations. You may have to pay a premium for an apartment in London, but a similar apartment in Scotland will cost you less. Conversely, you can spend less for more space in Wales. However, this analysis is a complex task. Some properties, even within a neighborhood, may perform differently for various reasons.
Data science can help uncover such anomalies in a matter of seconds.
Undoubtedly, data science and its related fields will play a massive role in shaping the real estate sector's future. With AI, machine learning, IoT, and automation becoming part of the industry process, the future looks exciting and promising.