Renovation Lens starts by identifying comparable sales for the property, then filters those comps based on the target post-repair Condition and Quality scores.
Over the past few months I've talked to a lot of fix-and-flip investors and private lenders about how they estimate After-Repair Value (ARV) today, and I kept hearing some version of the same story.
Someone hand-picks a handful of comps, and half the time those comps aren't quite right, pulled from a street two neighborhoods over, or matched on square footage and bedroom count without accounting for what can be one of the biggest drivers of a property's value: its condition.
Two properties can look comparable on paper and still have very different financial profiles when one needs a full renovation and the other is already updated. For a fix-and-flip investor, that difference affects not only what the property could be worth after renovation, but also how much work and capital it will take to get there.
Yet condition is often the least rigorously evaluated variable in an ARV estimate. When the condition of the subject property and the comps isn't assessed consistently, the resulting ARV can be difficult for a lender or investor to validate.
That's the problem we set out to solve with Renovation Lens, a new capability inside Restb Lens, the property intelligence platform from Restb.ai.
What is ARV?
ARV, or After-Repair Value, is the estimated market value of a property once renovations are complete.
For fix-and-flip investors, ARV is a critical part of determining whether a project makes financial sense. For private and hard money lenders, it is an important input when evaluating renovation loans and the potential value of the underlying property.
The challenge is that an ARV estimate depends heavily on the comparable properties used to support it, and those properties need to reflect the expected post-renovation state of the subject property.
How does a home's condition affect its resale value?
Condition and quality can move a property's value more than most people expect. Two homes with similar locations, square footage and bedroom counts can command very different prices when one needs substantial work and the other is move-in ready.
We wanted to see how much that difference could matter in an actual ARV estimate.
In one example run through Renovation Lens, a property in Atlanta, GA had a current Condition score of 5.4 and Quality score of 4.4, with a current displayed price of $190,000.
When we changed the target scores to reflect a Like New condition and Designer–Upgraded quality, the estimated ARV range came to approximately $281,144 - $333,457 with a midpoint of $318,491.
That's a substantial difference from the property's current displayed price, without changing its location, lot or square footage.
The key point is that the expected post-renovation condition can change which properties should be considered comparable in the first place, and therefore influence the resulting ARV range.
The example above shows how changing the target Condition and Quality scores can materially change the estimated ARV range while the property's core characteristics remain unchanged.
How does Renovation Lens calculate the ARV range?
The key design decision was that conditions couldn't simply be considered after selecting the comps. It had to influence which comps made the cut in the first place.
Renovation Lens starts by identifying comparable sales for the property, then filters those comps based on the target post-repair Condition and Quality scores.
The remaining comparable properties are weighted by similarity rank to produce a weighted price per square foot. That figure is multiplied by the property's living area to calculate the ARV midpoint, while the range is based on the minimum and maximum price per square foot among the comparable properties that meet the target criteria.
The result is an ARV range backed by the comparable sales used to calculate it, rather than a single number without context.
The target Condition and Quality scores are preset, but they can be adjusted along with the comparable search radius and property characteristics. This allows users to rerun the analysis for different renovation scenarios and see how the projected ARV changes.
This is the part we felt was missing from many existing approaches: the renovation scenario should influence the comparable set, not just the final valuation.
How We Validated the ARV Estimates
We've been backtesting Renovation Lens against past fix-and-flip sales, checking what the tool would have estimated against what the property actually sold for. In cases where we had enough comparable data, the results showed that the ARV range was able to capture the actual sale price across a meaningful share of the properties we tested.
Just as important to me, it didn't overestimate in 95.2% of those cases, and that matters more here than raw accuracy, because an ARV that comes in too high is the kind of error that actually costs investors and lenders money.
How do you use Renovation Lens
The workflow is intentionally straightforward.
1. Enter the property address
Start with the property you're evaluating. Renovation Lens uses its current condition as the starting point.
2. Review and adjust the inputs
Update property characteristics, upload photos if needed, and set the target Condition and Quality scores to reflect the post-renovation state you're planning.
3. Get the ARV estimate
Renovation Lens returns an estimated ARV range based on comparable sales that match the target condition and quality. You can then adjust the search parameters and rerun the analysis to explore different renovation scenarios.
The important part isn't simply getting an ARV estimate quickly. It's being able to see the comparable sales behind the range and understand how changing the renovation scenario affects the projected value.
Who Renovation Lens is useful for
Renovation Lens is designed for professionals who need to evaluate a property's potential value after renovation, particularly private and hard money lenders and fix-and-flip investors.
For private and hard money lenders, it provides an independent, evidence-backed ARV check before funding a renovation loan, with a condition-adjusted range and the comparable sales behind the estimate. As the rehab budget or scope changes, the analysis can be rerun to reassess the projected value.
For fix-and-flip investors, it provides a comp-backed ARV range without having to piece together the same analysis across multiple tools. Adjustable Condition and Quality scores also make it possible to model different renovation scenarios and see how each could affect the projected ARV.
Who Renovation Lens is useful for
Renovation Lens is currently available in early access to a limited group of users ahead of its full rollout.
If you're a fix-and-flip investor, private lender, or hard money lender looking for a faster way to evaluate ARV, you can explore condition-adjusted estimates, review the comparable sales behind the range, and model different renovation scenarios.
👉 Interested in seeing how it works for your properties? Get in touch with our team to learn more and request early access.
FAQs
How is After-Repair Value calculated?
ARV is typically estimated using comparable sales that reflect the property's expected post-renovation state. Renovation Lens filters comparable properties based on target Condition and Quality scores, then weights the qualifying comps by similarity to calculate an estimated ARV range.
Why is condition important when estimating ARV?
Condition helps determine which comparable properties are relevant to a property's expected post-renovation state. Two properties can be similar in location, size and bedroom count but have significantly different values when their condition and quality differ.
Why is condition important when estimating ARV? What is a condition-adjusted ARV?
A condition-adjusted ARV considers the expected post-renovation condition and quality of a property when identifying and evaluating comparable sales.
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