Zestimate vs CMA: how accurate are online estimates?

What an automated estimate can see

Automated valuation models work from what is recorded: past sale prices, tax assessments, lot size, bedroom and bathroom counts, year built, and the prices of nearby sales. On a street of similar homes built in the same decade, that is a lot to work with, and the estimates can land close.

They also update constantly and cost nothing, which is why they are a reasonable first stop. Treated as a bracket rather than a number, they tell a homeowner roughly which part of the market they are in.

What it cannot see

It cannot see condition. A model has no way to distinguish a home with an original 1980s kitchen from the identical floor plan next door that was taken back to the studs last year. Public records record the transaction, not the renovation.

It cannot see the things that move South Florida prices in particular. Whether the roof has been replaced and when. Whether the windows are impact rated. What the flood zone designation is and what that does to insurance. Whether the water view is open or obstructed. Whether a condo has a funded reserve or a pending assessment.

It also cannot see the lot. Backing onto a preserve rather than a six-lane road is worth real money and is invisible in a record that lists only square footage.

Where estimates drift furthest

Accuracy is not uniform. Automated estimates do best where sales are frequent and homes are alike, and worst where either condition fails.

That means they struggle in exactly the places much of South Florida sits: waterfront, where two homes on the same street can differ by the width of a canal and the presence of a dock; luxury, where every property is unusual and comparable sales are sparse; and small condo buildings, where a handful of sales a year cannot support a confident model.

Renovated homes are the other systematic case. A model tends to price the recorded house rather than the current one, so a seller who has invested heavily often sees an estimate well below what the home will actually attract.

Using both properly

Start with the estimate. Note the range if the site publishes one, because that spread is the model telling you how confident it is, and a wide spread is a signal in itself.

Then get an analysis from someone who has been inside comparable homes and can adjust for what the model missed. If the two land close together, you have corroboration. If they diverge sharply, the divergence usually points at something specific, and identifying it is the useful part.

Why estimates disagree with each other

Different sites publish different numbers for the same home, sometimes by a wide margin, and the reason is that they use different models and different inputs. One may weight tax assessment heavily, another recent nearby sales, another its own prior estimate.

That disagreement is informative. Where several estimates cluster, the underlying data is probably good. Where they scatter, it usually means the model has little to work with, which is itself a signal that your home is unusual for its area or that comparable sales are thin.

Checking two or three rather than one costs nothing and gives you a sense of the spread that no single headline number conveys.

What to do when your estimate is badly wrong

Start by checking the facts the model holds. Bedroom and bathroom counts, square footage, and lot size are frequently wrong in public records, and most sites let an owner correct them. A home recorded as two bedrooms when it is three will be estimated as a two bedroom.

Then look at what it has used as comparables, where the site shows them. An estimate dragged down by a distressed sale two streets away is a specific, correctable problem rather than a mystery.

Correcting the record helps, but it will not close a gap caused by condition, view, or renovation, because those are not fields in any database. That gap closes with a real analysis and, when you list, with photographs and a description that make the difference visible.

What automated estimates are genuinely good for

Dismissing them entirely is as unhelpful as trusting them completely. They do several things well and it is worth using them for those.

They are a good first bracket. An owner with no idea whether their home sits at four hundred thousand or seven hundred thousand gets a useful orientation in seconds and for nothing.

They are useful for tracking direction over time. The absolute number may be off, but if the same model shows an area rising or falling over eighteen months, that trend is informative even where the level is not.

They are useful for comparing broadly. Looking at estimates across several neighbourhoods gives a reasonable sense of relative price levels, and relative error tends to be smaller than absolute error.

They are useful for spotting a data problem. An estimate wildly out of line with the street often means the public record holds something wrong, and that is worth finding and correcting whether or not you are selling.

What they are not good for is the one thing owners most want to use them for, which is setting an asking price on a specific home. That requires seeing the property, and no model does.