Zillow vs. Reality: How Accurate Are Automated Home Valuations in Kona, Hawaii?
If you've ever looked up your home's value on Zillow or Redfin, you've experienced an automated valuation model (AVM) — an algorithm that estimates what your property is worth using publicly available data. But how accurate are these estimates when it really counts?
As a realtor in the Kona, Hawaii market, I wanted to find out. So I conducted a study comparing Zillow's "Zestimate" against MLS (Multiple Listing Service) asking prices and final sale prices across 20 recent single-family residential sales.
The Methodology
To keep the study clean and unbiased, I didn't cherry-pick properties by price range or neighborhood — I simply took the last 20 qualifying sales from the MLS. I excluded:
Private (non-MLS) sales — because there's no way to know if they were true arms-length transactions.
Pre-market sales — properties listed on the MLS but sold before any days on market, where the asking price typically equals the sale price and offers no negotiation insight.
One important nuance: Zillow adjusts its estimate the moment a property is listed, incorporating the asking price. To avoid this bias, I recorded the Zestimate from just before the listing date — capturing what the algorithm predicted on its own, without any human-set pricing signal.
The Results
| Metric | Average Difference from Final Sale Price |
| Realtor/Owner Asking Price | -3% |
| Zillow Zestimate | -5% |
On average, the realtor- and owner-set asking price was 3% below the final sale price — a very typical figure for the Kona market. The Zillow Zestimate came in at 5% below the final sale price on average. That's not a dramatically large gap, and frankly, for an algorithm working solely off public data — without ever setting foot in any of these homes — a 5% average deviation is impressive.
But the Average Doesn't Tell the Whole Story
When I looked beyond the averages, the standard deviation told a more revealing tale. Think of it this way: two groups of people can both average five feet six inches in height, but one group might range from five-five to five-seven, while another ranges from five-two to five-ten. The average is the same, but the spread is very different.
The Zillow estimates showed substantially higher variability, with some individual properties swinging as much as 21% to 39% off the final sale price. The realtor/owner asking prices clustered much more tightly around the eventual outcome.
The Bottom Line
This study isn't a criticism of Zillow or online valuations — it's genuinely remarkable what a well-built algorithm can do with public data. But if you're a homeowner preparing to sell, precision matters. Your proceeds, your tax planning, and your timing decisions all depend on having the most accurate picture possible of what your home will actually sell for.
In this study, the owner-realtor asking price proved to be a significantly better predictor of the final sale price. For sellers who need reliable numbers, working with a local real estate professional remains a distinct advantage.
Austin Ashley | Action Team Realty | Kona, Hawaii
