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What Are Comparable Sales (Comps)?

Comparable sales, commonly referred to as "comps," are recently sold properties that are similar to a subject property in terms of location, size, condition, and features. They form the backbone of every real estate valuation, whether you are an investor calculating after repair value, an agent pricing a listing, or an appraiser completing a formal appraisal report.

Comps matter because real estate is inherently local and heterogeneous -- no two properties are exactly alike. Unlike stocks or commodities, there is no centralized exchange that sets a real-time price for a given property. Instead, value is determined by what similar properties have actually sold for in the recent past. According to the National Association of Realtors (NAR), 99% of real estate agents use comparative market analyses (CMAs) to advise clients on pricing, making comps the universal language of property valuation across the industry.

How to Find Good Comps: The Three Key Criteria

Not all comps are created equal. The quality of your valuation depends on selecting comps that are truly comparable. There are three primary criteria that determine whether a sale qualifies as a good comp:

1. Distance (Proximity). The closer a comp is to the subject property, the more relevant it is. Ideally, comps should be within 0.5 miles in suburban areas or within the same neighborhood in urban markets. Crossing major roads, school district boundaries, or entering a different subdivision can introduce significant value differences even over short distances. The goal is to find sales that share the same micro-market dynamics -- the same buyer pool, the same school ratings, the same walkability profile.

2. Recency. Real estate markets move, and a comp from 12 months ago may not reflect current conditions. In active markets, prioritize sales from the last 90 days. In slower markets, you may need to extend the window to 6 months. Sales older than 6 months should only be used as supplementary data and adjusted for market appreciation or depreciation. As a rule of thumb, if the market has appreciated 5% year-over-year, a comp from 6 months ago needs roughly a 2.5% upward time adjustment.

3. Similarity. A good comp should match the subject property in type (single-family to single-family, not condo to single-family), approximate size (within 20% of square footage), similar bed/bath count, and comparable construction style and age. The more adjustments you need to make, the less reliable the comp becomes. A comp requiring a $50,000 adjustment for size differences is inherently less trustworthy than one needing only a $5,000 adjustment.

Standard Adjustment Factors for Comp Analysis

Once you have selected your comps, you need to adjust their sale prices to account for differences from the subject property. The principle is simple: if the comp has a feature the subject lacks, subtract value; if the subject has a feature the comp lacks, add value. Here are the most common adjustment categories:

• Square footage: Typically $50-$150 per square foot depending on the market. If a comp is 200 sqft larger than the subject, subtract 200 x the local $/sqft adjustment factor.
• Bedrooms: $5,000-$15,000 per bedroom difference in most markets. An extra bedroom adds functional utility and appeals to a larger buyer pool.
• Bathrooms: $5,000-$10,000 per full bathroom, $2,500-$5,000 per half bath. Bathrooms are one of the highest-ROI features in residential real estate.
• Condition: The most subjective adjustment. The difference between a fully renovated property and one in average condition can range from $10,000 to $50,000+ depending on size and market. This is where photo analysis becomes critical.
• Garage: $10,000-$25,000 for a 2-car garage versus no garage. In cold-weather and suburban markets, this premium is typically at the higher end.
• Lot size: Varies widely by market. In dense urban areas, lot premiums are minimal. In suburban and rural areas, lot size differences of 0.25 acres or more can add $10,000-$30,000.

How AI-Powered Comp Analysis Saves Time

The traditional comp analysis process is labor-intensive. An investor or agent must search MLS for recent sales, filter by property type and location, pull up each listing individually, review photos and details, calculate adjustments for each comp, and compile everything into a presentable format. This process typically takes 30-60 minutes per property and requires access to MLS, which is not available to all investors.

AI-powered comp analysis automates every step. The algorithm searches all available data sources simultaneously, scores each potential comp on a relevance index (considering proximity, recency, and similarity in a weighted formula), applies market-specific adjustment factors rather than generic rules of thumb, and delivers a ranked list of comps with adjustments already calculated -- all in under 60 seconds.

This matters at scale. An investor analyzing 10 potential deals per week spends 5-10 hours on manual comp research alone. AI reduces that to minutes, freeing up time for property visits, contractor coordination, and deal negotiation -- the activities that actually generate returns. The speed advantage also matters in competitive markets where being first with an offer can make or break a deal.

Common Comp Analysis Pitfalls to Avoid

Even with good data, several mistakes can undermine the accuracy of a comp analysis. Avoid using distressed sales (foreclosures, short sales) as direct comps unless the subject is also distressed -- these sales typically close 10-20% below market value and will skew your estimate downward. Similarly, exclude intrafamily transfers and sales between related parties, as these do not reflect arm's-length market transactions.

Another common error is relying on too few comps. While three comps is the standard minimum for an appraisal, using five to eight provides a more statistically reliable estimate. If you can only find one or two comps that meet your criteria, the market may be too thinly traded for a confident valuation, and you should either widen your search parameters or proceed with extra caution.