More Real Estate Science! Finding the Sweetest Deals

Redfin’s real estate scientists published a big, glorious new report today on when homes will sell for a big discount and when they won’t, based on thousands of home sales across the country.

We spent two months grinding through the data because every day, we see buyers with born-to-lose tattoos on their foreheads making lowball offers doomed to instant failure. And then sometimes they win.

Nuts! Figuring out fast when a deal will fly and when it won’t is the key to making our margins work.

We’ve tried to sort out when a seller will give ground, a posting that immediately set off a discussion at Newsweek and U.S. News & World Report and across the blogs. We’ve talked about it on TV.Diane Sawyer, GMA

Meanwhile, pricing discussions have been all the rage in our discussion forums, with visitors asking how negotiable new construction is, or even what to offer on an individual property.

Enter the real estate scientist, who shreds MLS data, website logs, academic research and tax records to provide reliable answers to practical questions: what really works when marketing a listing, what type of listings sell in less than seven days, whether high commissions lead to faster sales (they don’t).

Today’s report is about how to find the sweetest deals. Redfin’s Rob McGarty and Mzany mad real estate scientistose Andre crunched the numbers for all 9,053 sales of single-family homes in Fairfax (Virginia ‘burbs), King (Seattle area) and Los Angeles counties, between April 15 and June 15 this year, to look at homes that sold for a lot less than the asking price.

What surprised us right off the bat was how small the average discount was: after all the bad news about the housing market, it was still less than 2.5%. We were also surprised to see that a small fraction of listings got a huge discount, of more than 10% off list price.

This means that 90% of the time, lowballers are wasting their time. But that 10% of the time, they’re saving $50,000. The trick is finding the listings ripe for a discount.

So for each market we split the sales into two buckets: those that got the biggest discount (top ten percentile, an average of 11.4% off the final asking price), and all the rest (the 90th percentile and below, which got an average discount of 1.5%).

Then we compared the two groups to see what the sales involving a big discount had in common:

1.    83% more likely to have been on the market for 90+ days.
2.    73% more likely to be marketed as fixer-uppers.
3.    20% less likely to feature a noteworthy remodel.
4.    28% more likely to have already been price-reduced (though there were some confounding factors).
5.    52% more likely to have been seller-owned for 20 years or more.
6.    9% more likely to have been seller-owned for less than five years, a slight but surprising correlation.
7.    Only 9% more likely to be a short sale or bank-owned. Most consumers expect this correlation to be much stronger.

The portrait that emerged is  of a bimodal market (much like the VC market right now) — a few homes in the most sought-after neighborhoods sell for well above asking price, most sell near the asking price and anything distressed or run-down (more homes are run-down now than before so the drop in prices is in part a reflection of the drop in the quality of the homes being sold) just keeps dropping and dropping.

The bottom-line is that the condition of the home and its length of time on the market — surprise, surprise — are the main drivers for discounting — but how long the seller has owned the home is a big factor too. And foreclosures aren’t as negotiable as people think.

The report has already gotten picked up by the LA Times and now the Seattle Times too (FRONT PAGE!!!).

Get the full paper (PDF), which breaks out all the data by county, and goes into the methodology too.

Discussion

  • menlo park denizen

    Love this study, Thanks!!!

    Can you do one on which MONTH and/or season nets the biggest discount? I can theorize, but you have the data.

  • http://blog.redfin.com/blog/author/cynthia.pang Cynthia Pang

    menlo park denizen,
    We’re glad you enjoyed the study! Interesting idea for a future topic. I’m going to add your suggestion to the science of real estate forum to start a discussion: http://forums.redfin.com/rf/board?board.id=RealEstateScientist

    Regards,
    Cynthia
    Redfin

  • http://http//blog.Franklyrealty.com Frank Borges LL0SA= Broker FranklyRealty.com

    Ok, back up (insert sound of a large truck backing up)

    Does your data include seller subsidy? That can be as high as 2% on average, and if you forget that, all your numbers will be off. Numbers should be based on the NET price.

    And when you calculated “off list” , are you using the current list price or the original list price?

    Our local association NVAR continues to use, in my opinion, this incorrect math. They do it based on closed price as a % off current list price. When they did this, it was the same average “2% off.”

    Add back in seller subsidy… and the average is 4% off. Add back in the Original list price and it grows to 6%. Add back in the original list price of the prior listing (DOMP) and you get 8% off.

    So numbers are great and all, but it really depends on how you run the numbers.

    Great marketing though.

    Frank

  • Nick

    Thanks for stating the obvious. The outcome would be logical to anyone who has any sense, and certainly anyone even subconsciously aware of basic economics. This study just goes to show two things:

    1. Repackaged information will still get you attention, just because the topic is relevant and of interest.
    2. There are still a bunch of dummies out there who don’t know how to buy real estate.

  • http://www.bluecollaragents.com Trevor Smith

    Frank,

    I think you have an excellent point regarding closing costs. Ideally, all of this data should be based on the net sales price, not the gross sales price. However, I know here in Seattle (and I believe its similar elsewhere), seller paid closing costs are not noted either in the MLS sales price or the sales price found on the tax records. This is wrong for so many reasons.

    1.) Apart from calling the buyer or buyer’s agent of every home sold to see if closing costs were built in, there is no way to tell what a home actually sold for.
    2.) This also affects appraisals. Unless you have an appraiser who is willing to go the extra mile when doing his homework, built in closing costs can artificially inflate sales prices.
    3.) Some sellers, especially builders, will negotiate 3-6% off of the sales price as long as it’s taken in the form of the seller paying the closing costs. As long as the top end number looks good, the builder’s happy. High sales price = high comps for the next deal.

    I think MLS’s across the country should begin recording seller paid closing costs along with the sales price. This will allow all consumers to make a more informed decision when purchasing a home.

    All the best ~
    Trevor @ Redfin

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