Why Our Accuracy Gains Can Reach 30%
Leading consumer AVM providers like Zillow, Redfin, and Realtor.com have built highly reliable models that perform well across the majority of homes. For properties that have sold recently or are in neighborhoods with steady turnover, their estimates are often close to the mark.
So how can AVM Optimizer claim up to a 30% improvement in accuracy over these already powerful models?
The key lies in who uses AVM Optimizer and why.
Most consumers turn to AVM Optimizer when they suspect their home’s value estimate is missing something important—such as upgraded kitchens, finished basements, new roofs, or other improvements that traditional AVMs typically overlook. In other words, our users are self-selecting into the most challenging category of valuation: homes that differ in meaningful ways from “typical” properties in the data set.
This makes our testing ground fundamentally different. While mass-market AVMs look good on averages—because many homes are easy to model—AVM Optimizer is applied most often where those models are weakest. That’s exactly where we shine.
By incorporating condition and upgrade information directly from the homeowner or professional user, AVM Optimizer can recalibrate the baseline estimate to reflect what the market would actually pay today.
That’s why we can sometimes show such dramatic improvement. We’re not competing against Zillow and Redfin on the easy estimates—they already handle those well. Instead, we’re fixing the hardest ones.
👉 The result: up to 30% more accurate valuations in the cases where consumers need it most.