Type an address into any deal analysis tool and you'll get a number back in seconds. What you almost never get is the thing that matters more: how much that number deserves your trust on this particular property.
Accuracy in deal analysis isn't one property of a tool. It's several independent things that can each fail separately, and a tool can be excellent at one while being useless at another. Here's what actually drives it — and a way to test any tool yourself before you underwrite a real offer with it.
What accuracy actually depends on
Comp selection, not comp count
Every valuation is a comp problem underneath. A tool that pulls twenty loosely similar sales across a wide radius will produce a confident-looking number built on the wrong evidence, while three genuinely comparable sales within a few blocks will get you closer.
What matters is whether the tool shows you which comps it used and lets you disagree. A number you can't audit is a number you can't defend to a lender, a partner, or yourself at 11pm. See how ARV is actually calculated for what good comp selection looks like manually.
Data recency and the reporting lag
Sales data doesn't appear the instant a deal closes. There's a gap between closing and when a transaction shows up in the records a tool reads, and that gap varies by jurisdiction. In a fast-moving market, a valuation built on data that lags by weeks is describing a market that no longer exists.
This matters most in exactly the situations where you need accuracy most: rapidly appreciating or rapidly softening markets. Ask any tool what its data horizon is, and be skeptical of any that can't answer.
Whether it accounts for condition at all
Most automated valuations assume average condition, because condition is the hardest thing to know remotely. A house with a failed roof and a gutted kitchen is not worth what a records-based model says it's worth, and neither is a fully renovated one.
The gap between as-is value and after-repair value is your deal. A tool that can't distinguish them is doing arithmetic on the wrong property.
Repair estimate granularity
"$35,000 in repairs" is not an estimate — it's a guess with a dollar sign. A useful repair number is built line by line, with quantities and rates you can inspect and override, so you can see what's driving it and correct what's wrong. See estimating repair costs for the manual version of this.
Rates also aren't national. Labor and material costs vary by market, and a tool applying one national number everywhere is going to be systematically wrong in both directions depending on where you're buying.
How many exits it actually models
This one gets overlooked, and it's a different kind of accuracy: a tool can compute a flawless flip return and still give you the wrong answer, because the flip wasn't the best exit on that property.
If a tool only models one or two strategies, its output isn't "the answer" — it's the answer to a question you may not have meant to ask. See all eight exit strategies.
Whether it gives you a range or a false point
Any valuation carries uncertainty. A tool reporting $412,350 is communicating a precision that no valuation method actually has. A tool that gives you a range, or tells you when the comps disagree with each other, is being more honest — and more useful, because your offer strategy should differ when the evidence is thin.
How to test any tool in an afternoon
You don't need to take anyone's word for this, including ours. Here's a protocol you can run on any analyzer:
- Start with a property you know cold. One you've owned, sold, or analyzed to death. You already know the answer, so you can grade the tool instead of trusting it.
- Test a recent closed sale. Pick something that sold in the last 60 days and run it as if it hadn't. Compare the tool's number to the actual price. Do this on five properties, not one — one match proves nothing.
- Open the comps. Are they genuinely comparable? Same neighborhood, similar size, similar vintage, similar condition? If the tool won't show you, that's your answer.
- Break it on purpose. Run a property with something unusual — an odd lot, a converted use, a rural parcel, a heavy rehab. Every tool degrades somewhere. You want to know where before it matters.
- Check the repair estimate against a real bid. If you've got a contractor quote on a property, compare line by line, not just the total.
- Run the same property twice, a week apart. Wild swings without a market event suggest instability in the underlying data.
The tool that survives this isn't the one that's always right. It's the one that's wrong in ways you can see, understand, and correct.
What no tool can do
Every automated valuation is working from records and comparable sales. None of them have been inside the house. None know that the neighbor runs a repair shop out of the garage, or that the block floods, or that the seller's brother is a contractor who'll do the kitchen at cost.
The right way to use any analyzer is as a fast, consistent first pass that tells you whether a deal is worth an hour of your time — and as a structured way to compare exits once it is. It replaces the spreadsheet, not the walkthrough.
Any tool claiming otherwise is selling something.
Where we stand
Appraize is built around the specific failure points above: comps you can inspect and adjust, line-item repair estimates rather than a lump sum, condition handled explicitly, and all eight exit strategies modeled on the same property so the strategy comparison is part of the analysis rather than a separate exercise.
We'd rather you test it against the protocol above than take our word for it. That's what the free analyses are for.
