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How to Quickly Get Reliable Comps for Investment Properties

Learn how to quickly get reliable comps for investment properties using AI-powered valuation, MLS data, and a repeatable 5-step process.


How can I quickly get reliable comps for investment properties? The fastest, most consistent path is an AI-powered deal-analysis platform that pulls MLS-sourced sold data, automatically adjusts for property differences, and returns a defensible After Repair Value (ARV) range in about 60 seconds — not the 20 to 30 minutes that manual comping usually takes. For wholesalers and investors, that difference in speed often decides who gets the contract and who loses the deal to a faster competitor.

Key Takeaways

  • AI-powered comping tools can produce an ARV range and offer price in roughly 60 seconds, versus 20–30 minutes of manual work.
  • Reliable comps weigh proximity, recency, and condition, then adjust for square footage, beds, baths, and lot size.
  • Non-disclosure states hide public sale prices, so MLS-sourced data matters more there, not less.
  • Repair-scope changes should instantly recalculate ARV, as-is value, and offer — not require a fresh manual pull.
  • A repeatable, documented process protects your margin and gives you a number you can defend to sellers and buyers.

What Are Comps, and Why Does Reliability Matter?

Comparable sales, usually shortened to "comps," are recently sold properties similar enough to a subject property that their prices can estimate what it's worth. In particular, a comp set is only useful if the properties actually resemble the target home in size, age, condition, and location. Unreliable comps are the single biggest cause of blown deals in real estate investing.

Consequently, when comps are pulled carelessly, two things tend to happen. Either the investor overestimates value and overpays, which erodes profit margin, or they underestimate it and lose the deal to a competing offer. As a result, the real goal isn't just speed — it's a number that holds up under scrutiny from sellers, cash buyers, and lenders alike.

How Can I Quickly Get Reliable Comps for Investment Properties?

The short answer: use a tool that automates both the data pull and the adjustment math. Platforms such as ChatARV take a single property address and, within about a minute, surface the top matching sold comps, calculate ARV and as-is value, estimate repair costs, and generate a ready-to-use offer for wholesale, novation, fix-and-flip, buy-and-hold, or BRRRR exits. Rather than piecing together listing sites, spreadsheets, and guesswork, the investor reviews one report.

Above all, speed only matters if the output is trustworthy. That's why a credible system should show its work — the comps used, every adjustment applied, and the resulting ARV range — rather than hand back a single opaque figure. For a closer look at building that kind of documented report, this guide on as-is comp reports walks through what a defensible report should actually contain.

Why Speed Changes the Outcome of a Deal

In wholesaling specifically, the investor who gives the seller a confident number first usually wins the contract. For example, Chris Turney of Fortis Valorem reports giving sellers an offer on the same call, rather than following up after "running the numbers." In contrast, a 20-minute delay is often enough time for a seller to take a second call from a competing buyer.

"I'm on it every day… I can give sellers an offer on the same call."
— Chris Turney, Fortis Valorem

Why Manual Comping Slows Investors Down

Traditional comping depends heavily on who's doing it. One investor might pull six comps from a public listing site; another might call an agent for Multiple Listing Service (MLS) data, the centralized database real estate professionals use to share active and sold listings. Neither approach is wrong, but neither is fast or consistent either.

Furthermore, manual comping usually takes 20 to 30 minutes per property once you include searching, filtering, adjusting for condition, and double-checking the math. For an investor running several leads a day, that adds up to hours lost to a task that software can finish before the seller hangs up the phone. If you've never had direct MLS access, this breakdown of how to run comps without MLS access explains what data sources are realistically available to you.

How to Pull Reliable Property Comps in 5 Steps

Regardless of which tool you use, a repeatable process keeps your numbers consistent from deal to deal. Here's the sequence that produces a defensible ARV and offer.

  1. Enter the subject property's address. Accurate comping starts with precise location data, since proximity is one of the strongest predictors of value similarity between properties.
  2. Review the top six matching sold comps. Check that each comp was weighed for proximity, recency of sale, and overall condition before accepting the suggested set.
  3. Confirm the automatic adjustments. Square footage, bedroom and bathroom count, and lot size differences should already be adjusted for, so verify the logic makes sense for this specific property.
  4. Enter or update the repair scope. Walk the property if possible, then input the real repair needs so the as-is value and ARV recalculate instantly around actual condition.
  5. Generate the offer for your exit strategy. Pull the Maximum Allowable Offer (MAO) for wholesale, or the matching projection for flip, buy-and-hold, or BRRRR, then share the report with the seller or buyer.

Notably, this process stays flexible after the fact. When Chris Turney discovered a property needed a full gut rehab, he updated the repair scope and the report recalculated to $88,000 instantly — numbers he then used to renegotiate and land a $35,000 assignment fee.

Getting Accurate Comps in Non-Disclosure States

In the 12 U.S. non-disclosure states, actual sale prices are not published publicly, which historically forced investors to estimate value from tax records, assessor data, or guesswork. However, that gap doesn't mean comps are impossible — it means the data has to come from somewhere other than the public record.

Specifically, MLS-sourced transaction data pulled across multiple provider relationships can fill that gap, because it draws from the same closed-sale records agents use, rather than relying on a single public source. For a state-by-state breakdown of where this matters most, see this overview of non-disclosure states for real estate investors. In addition, the U.S. Department of Housing and Urban Development publishes general housing market data that can provide helpful context, even where individual sale prices stay private.

AI Comps vs. Manual Comps: A Side-by-Side Comparison

To put the tradeoffs in context, here's how the two approaches typically compare across the factors investors care about most.

Factor Manual / Agent Comping AI-Powered Comping
Typical time per property 20–30 minutes About 60 seconds
Consistency across deals Varies by who runs it Repeatable methodology every time
Requires own MLS access Usually, or a cooperating agent Not required
Non-disclosure state support Difficult without MLS relationships Built-in across all 12 states
Recalculates after a walkthrough Requires starting over Instant recalculation

Common Mistakes That Lead to Unreliable Comps

Even with good intentions, certain habits consistently produce bad comps. For instance, pulling only the three nearest listings without checking condition or sale recency tends to skew the ARV in either direction. Similarly, ignoring square footage or lot size differences without adjusting for them introduces an error that compounds across every exit strategy calculation.

Another frequent mistake is treating the first comp pull as final, even after a walkthrough reveals different repair needs. Because repair scope directly affects as-is value, failing to update it after seeing the property in person can mean leaving money on the table or overpaying by thousands. Finally, relying on a single data source in a non-disclosure state often means working from outdated or incomplete figures rather than true closed-sale data. According to the National Association of Realtors, inconsistent valuation methodology remains one of the most common causes of disputed offers between buyers and sellers in the resale market.

Frequently Asked Questions

What does "reliable comps" mean for an investment property?

Reliable comps are recently sold properties similar in location, size, and condition to the subject property, adjusted consistently for the differences that remain. In short, reliability comes from the adjustments being accurate, not just from the comps being nearby.

How can I quickly get reliable comps for investment properties without MLS access?

To quickly get reliable comps for investment properties without your own MLS access, use a platform that pulls MLS-sourced transaction data across multiple provider relationships on your behalf. This removes the need for a cooperating agent or a personal MLS login entirely.

How long should pulling comps take for a wholesale deal?

With an AI-powered tool, a full comp pull and ARV calculation typically takes about one minute. Manually, the same task usually takes 20 to 30 minutes per property.

What is the difference between ARV and as-is value?

After Repair Value (ARV) estimates what the property is worth once repairs are complete, while as-is value reflects its current, unrepaired condition. Both figures are needed to calculate a maximum offer that still leaves room for profit.

Can I get comps in non-disclosure states?

Yes. Even though sale prices aren't public in non-disclosure states, tools that aggregate MLS-sourced data across multiple providers can still surface closed comparable sales for these markets.

How many comps should I use for an accurate ARV?

Most reliable valuations use around five to six strong comps rather than two or three. A larger, well-matched set reduces the influence of any single outlier sale.

What adjustments matter most when comparing properties?

Square footage, bedroom and bathroom count, lot size, and overall condition matter most. Proximity and sale recency also heavily influence how closely a comp's price reflects current value.

How much does AI-powered comping typically cost compared to hiring an agent?

AI-powered platforms typically charge a flat subscription rather than a per-deal fee, which usually works out cheaper than paying an agent for one-off pulls. This guide on getting accurate comps without paying an agent breaks down the cost comparison in more detail.

What's the biggest mistake investors make when pulling comps?

The biggest mistake is treating the first comp pull as final, even after a walkthrough changes the known repair scope. Updating the analysis after inspection often changes the offer significantly.

Do I need a real estate license to pull my own comps?

No. Investors don't need a license to research property values for their own deal analysis; a license is generally required only to represent another party in a transaction.

How do repair cost estimates factor into an offer price?

Estimated repair costs are subtracted from ARV, along with holding costs, closing costs, and desired profit margin, to produce the Maximum Allowable Offer (MAO). A higher repair estimate directly lowers what an investor can safely offer.

What's the best way to defend a comp-based offer to a seller?

Show the actual comps used and the specific adjustments applied, rather than just stating a final number. Sellers are far more likely to accept an offer when they can see exactly how it was calculated.

Bottom Line: Get Reliable Comps Without the Delay

Ultimately, learning how to quickly get reliable comps for investment properties comes down to replacing guesswork with a repeatable, documented process. Whether you choose an AI-powered platform or a manual workflow, the goal stays the same: a defensible ARV, a confident offer, and a number you can explain to a seller on the very first call. For most wholesalers and investors, pairing broad MLS-sourced data access with instant recalculation after a walkthrough is what finally makes speed and accuracy possible at the same time. You can learn more about building that kind of workflow at chatarv.ai.