Why Real Estate Tech Must Trust the Process
The Industry Should Solve Data Aggregation First then Move to Real Estate Data Analytics
This article was originally published on Tech Estate Today. Check out TET for news and events on the intersection of real estate & tech industries.
Data is all around us. Data has always been around us as humans, but now thanks to breakthroughs in the information technology and the emergence of the Internet of Things space, individuals can capture records like no other time in history. Studies suggest that 90% of all the data in history has been created in the last 5 years since now we can keep records of everything.
Some industries have leveraged this phenomenon, while others have wasted it. This wave of data aggregation has led to the data analytics trend — the science of examining raw data with the purpose of drawing conclusions about that information. Data analytics is used in many industries to allow companies and organization to make better business decisions and in the sciences to verify or disprove existing models or theories. Startups, companies, and industries that have utilized data analytics and machine learning have put themselves in the position to become more efficient and more profitable.
The narrative of why actionable analytics has yet to be really utilized in the real estate industry usually comes down to an old school versus new school argument. It’s very similar to what is going on in sports and how analytics has become an ugly word for seasoned athletes, former athletes, and older sports executives. Should decisions associated with scouting new talent or considering possible trades be determined by a professionals gut or should the numbers/algorithm lead to the decision? I personally think it should be a mixture of boy based on the individual decision makers prior experience and understanding of the data’s results. The biggest obstacle is not that agents and brokers don’t see that there is a need — because real estate transactions depend on a steady flow of data between buyers and sellers, and brokerages with the best data ultimately make the most money — but it’s that they need to trust that your information is accurate and dynamic. If your product can provide them with trustworthy information that they are seeking and accustomed to, then you have made them more efficient. Now the gut decisions can be made only on for decisions that are not clearly a yes or no.
The real estate industry has been hesitant to implement data analytics into the day to day operations of the space for two core reasons:
- Agents and brokers, the gatekeepers to transaction activity, believe this new “Moneyball” approach is completely at odds with the relationship business of real estate and
- The lack of dynamic and transparent data accessible to the greater community. So this equates to real estate tech hopefuls facing two important obstacles to really reaching scale. Ultimately, the founders who are looking to disrupt this multi-trillion dollar industry must fulfill the issue of trust that brokers and realtors have built their long careers on.
During the first wave of innovation in the space, founders understood that real estate insiders were skeptical of the trend and considered it simply a fad. But after the consumer facing success of companies such as Zillow, Trulia, HomeAway and Rent.com, the industry must admit the benefit of bringing real estate data to the internet. Now with the emergence of data analytics, in the B2B spectrum helping enterprises make better decisions when it comes to marketing, advertising, and cost reductions, this next version of real estate tech founders have to opportunity to build upon what was created by the legacy real estate tech companies. There are lots of real estate tech startups focused on collecting data in various sub-sectors of industry (multifamily, residential, office & retail) and sharing (ie. Bloomberg of real estate) but no one has made market leading traction in the sector.
More and more agents are seeing the enterprise value of these products and having data online. They once relied on pen and paper or static Excel spreadsheets and now have access to real-time data in cloud-hosted databases, and collaborate more effectively with colleagues based on a common system of record. This proof point makes it is easy to envision how real estate technology is going to shift from no data to actionable data analytics. But first, the industry needs data aggregation tools or initiatives that can track and help address issues such as changes in building requirements and need for large portfolio owners to become more informed buyers and sellers. So what startup will emerge as the leaders in data aggregators? My prediction is that there will various market leaders within various niches and sub-sectors across the industry but all the startups must have both the relationships within the industry and technology expertise to addresses the trust issues some current portfolio managers have. Data analytics will permeate throughout the industry once realtors and brokers have access to dynamic data that they can trust and make more decisions on. Then it will build the need for tools to quickly analyze the big data.
Earnest Sweat is an Entrepreneurial Engineer for Camelback Ventures and an Investor in Residence for Backstage Capital. If you have any questions or requests please connect with Earnest through LinkedIn or Twitter.
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