HOUSINGNEWS REPORT
HOUSING PRECOGS: BIG DATA PREDICTIONS BEYOND HEURISTIC HUNCHES
are listed on an exclusive right-to- sell basis, there is non-MLS inventory available for sale. Sales outside the brokerage system can be significant. NAR esitmates that “8 percent of recent home sales were FSBO sales.” That’s not a big percentage but it does represent roughly 450,000 properties. Also, pocket listings are effectively outside the MLS system because they discourage, if not eliminate, cooperative sales. “Real estate is also highly competitive industry, compounded by low inventories across most major markets,” said Avi Gupta with SmartZip Analytics. “Homeowners are inundated with marketing from tens of agents in their area — so, agents have to find ways to cut through the clutter and stand out, be pre-emptive, and relate to the homeowner’s personal situation and needs/desires. Data and analytics are no longer a nice to have, they are essential to focus on the best prospects when it matters most.”
The lack of inventory is pushing up prices and reducing purchase opportunities in many areas. This may be one area where big data can be used to give homeowners a better understanding of the marketplace according to HouseCanary’s Alex Villacorta. “Many existing homeowners have chosen to remain in their homes in a ‘wait and see’ approach,” Villacorta said. “Big data can play a big role in helping consumers understand their local market and make informed decisions about whether now is indeed a safe time to sell a home, refinance, or make home improvements. In this age of economic and political uncertainty, big data and the insights gleaned from it can help to give context to the headlines and provide assurance to homeowners and buyers that they are making a decision that aligns with their risk appetites.”
One such example is a recent analysis of 14.7 million home sales from 2011 to 2017 that reveals the best month and day to sell a home based on the average premium above estimated market value sellers get when selling on each month and day. While the results of the analysis at the national level support cWonventional wisdom of selling in the spring or summer — best month to sell is May and the best day to sell is June 28 — the best times to sell vary by local market influenced by weather, retiree migration and other factors. (See more details in this issue on Page 27.) Likely.AI’s Brad McDaniel explains that “I don’t think big data will impact inventory shortages in the short term, but combined with AI prediction forecasting tools, it will be a huge help to developers moving forward when conducting feasibility studies to making final decisions about what product mix they should build, and where they “Many existing homeowners have chosen to remain in their homes in a ‘wait and see’ approach. Big data can play a big role in helping consumers understand their local market and make informed decisions about whether now is indeed a safe time to sell a home, refinance, or make home improvements.”
AVERAGE U.S. HOMEOWNERSHIP TENURE (YEARS)
8.00
9.00
8.00
7.00
6.00
5.00
4.00
3.00
2.00
ALEX VILLACORTA EVP AND CHIEF ECONOMIST, HOUSECANARY
1.00
0.00
Q1 2000
Q1 2008
Q1 2010
Q1 2012
Q1 2014
Q1 2016
Q1 2018
5
MAY 2018 | ATTOM DATA SOLUTIONS
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