How predictive analytics can help you. Case 3: Selling your home
Predictive analytics or the analysis of current and historical data to make predictions about future events is being used to demystify the process of buying and selling real estate. Redfin, the first online brokerage for residential real estate, is using a branch of predictive analytics (data mining) for lessons on how to sell homes. In the Fall of 2007, Redfin’s computer scientists analyzed data from more than 500,000 visitors to their listing of over 275,000 properties. The main finding of their study is that the primary determinant of how fast a home will sell, and for how much, is the home itself. However, by following seven recommendation that appear in their report, home sellers will yield a small but significant improvement in the results.
Below is a summary of Redfin’s seven tactics for selling your home. For additional details, please, refer to the Redfin’s report.
- Don’t overprice your property to avoid that it stays a long time in the market. The longer a property is in the market the more aggressive the buyers become in negotiating.
- Set your prices to show in web searchers. You need to take into account that buyers usually filter prices in $25,000 or $50,000 increments. For instance, a house priced at $300,000 is likely to be seen more than a house priced $301,000 because the $301,000 home will be excluded for buyers that set $300,000 as their maximum price.
- Debut your advertisement campaign on Friday to maximize the number of viewings during the first week.
- Stay engaged to increase your chances of selling your property faster.
- Market the property online using, for example, craiglist.
- Do not move until you have sold your house to avoid giving the impression that you are anxious to sell.
- Wait until neighboring foreclosures are off the market to avoid that low prices in the foreclosures affect your own pricing.
