Why Real Estate Should Utilize Big Data
The entire IT world is abuzz with the emergence of big data. With applications for consumers, enterprises and scientists alike, big data has enormous potential to change the way we do business in the future.
But there are other industries and professions, including real estate, that stand to benefit greatly from the integration of the real-time data analysis, predictive analytics and benchmark reporting offered through big data.
Understanding Big Data at Its Core
Big data is highly useful in financial risk management and assessment. Relevant information is typically received in one of two forms, either unstructured or multi-structured.
- Unstructured data is highly unorganized and rather inefficient when it comes to processing, translating and collating. Such information usually comes via plain text documents, blogs, and social media posts.
- Multi-structured data is far more useful in big data processing and management. This information is generally collected from customer transactions or questionnaires, detailed spreadsheets, and even images.
Although multi-structured data is preferred, both forms can be used in the collection and management of big data. Those who work with big data should place more of a focus on the accuracy and validity of incoming data as opposed to the form it’s presented.
Reducing Financial Risk
Many different factors go into determining the financial risk of an investment or venture in real estate. What once required laborious and tedious calculations can now be completed in a matter of seconds through big data processing.
Big data makes it easier to track details of a potential investment property, including any past renovations or repairs, the status of any outstanding loans or current investments and more. When used in tandem with the Internet of Things, big data is able to complement property management, too.
Creating Accurate Appraisals & Reports
The ability to deliver accurate appraisals is essential to the ongoing success of any realtor. In the past, the bulk of the appraisal process involved the manual collection, organization, and verification of data. Given the enormous datasets, some enterprises are working with today, managing all of this information would be unrealistic. With the prevalence of big data processing, it’s also unnecessary.
Real-time data analytics and automated processing take care of all the legwork for you. This reduces the potential for human error, improves appraisal speeds and ultimately results in submissions that are data-driven and highly accurate.
Benchmark reporting is also strengthened through the application of big data. Multiple cities have recently committed to lowering their energy consumption through building energy benchmarking, and they’re relying on big data for a timely solution. Trade associations such as BOMA International and LEED have benefitted from the increasing prevalence of big data.
Providing Better Buyer Assessments
Getting to know your prospective buyers is another key to success in the real estate industry. This is achievable through relevant data analytics, which happens to be a primary selling point of big data management. By collecting and analyzing past statistics, figures and trends, today’s computers are capable of providing an accurate forecast of their future interests, actions, and activities. Although it’s not perfect, many companies have already begun using predictive analytics with great success.
The resulting data can be used in a myriad of ways. By collecting the email addresses of your prospective buyers, for example, you can usually locate their public profiles on today’s social media sites. This provides you with another avenue to explore with your marketing and advertising campaigns.
Embracing Everything Big Data Has to Offer
Big data is best viewed as a package deal. While it’s possible to use its functions independently of one another, your predictive analytics wouldn’t be as accurate without the capabilities of real-time data processing. It would also be difficult to gauge your success without some form of benchmark reporting. Viewing these services as one unit not only simplifies the entire concept of big data, but it makes it understandable for tech newbies and veterans alike.