At the beginning of 2013, we researched and wrote an extensive piece on an up and coming real estate market factor: big data.
The buzzword has already lost some of its cachet, but there’s no denying that big data will drive the future of successful real estate practices.
Here are a few highlights:
“. . .big data in real estate is about presenting a “whole consumer” picture. It’s about using data to find out who buys what, when, where, why and how.”
“The real estate industry today is just evolving from spreadsheets and simple reports. While useful, they’re so…1980s. Right now, we’re on the edge of rapid evolution.”
“Even the most basic analysis could be used to increase the accuracy of mailings and emails which reduces business costs.”
Notice the author’s use of the word “could.”
The fact is, as pressing and forward leaning an issue as big data is, it is still in its infancy and most comments on the topic are hypothetical. Although the author’s article is correct to place emphasis on big data’s importance for future real estate market leaders, it’s still of the long-on-potential, short-on-tangibles status.
Since our opening salvo roughly one year ago, there haven’t been any huge developments on the real estate big data front. What developments have come about tread one of two paths:
- traditional home sales data predictions; or
- innovations in home sales marketing.
Currently, the most robust progress has occurred in the collection and analysis of traditional home sales data such as prices and home sales volume. Companies like House Canary use the same data real estate analysts have been using for years. The big data twist is the proprietary algorithm used to interpret the data and make predictions with a purported 90 percent accuracy.
In the case of House Canary, the interpretive model verges on innovation, but the result is not new — they are still working at predicting prices. As Robertson mentions in his article, the real allure of big data is its potential to predict who will buy and when — a much more daunting and rewarding task.
So far as we can tell at the time of this writing, there are no new services that claim to accurately predict likely real estate prospects. Here’s a list of the noteworthy players, excluding the aforementioned House Canary.
The challenge for the first true innovator in real estate big data is to harness available information and drive it to produce leads. In order to do so, one needs to find some link between traditional real estate sales data and:
- search engine term use;
- big box and grocery store purchase information;
- online store purchase information;
- real time travel and migratory information;
- online job searches;
- real time credit monitoring; and
- the list goes on and on and on.
Being able to predict price bumps based on historical data isn’t new. first tuesday has been doing it with small data (and big analysis) for years. The next step is to find associations in a sea of seemingly disparate information.
You know what they say: big data is for closers only.